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Energies, Volume 15, Issue 2 (January-2 2022) – 279 articles

Cover Story (view full-size image): The current power production capacity is being replaced by renewable energy sources, and it is vital that this new capacity is located rationally. The positioning of this capacity can be affected by energy market policies and pricing schemes. Synthetic networks and graph theory provide tools to assess how these policies can affect power production positioning and power system performance. For example, windy coasts can be an attractive location for wind turbines due to weather conditions, but socioeconomic costs might increase if transmission distances get too long. View this paper
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18 pages, 4587 KiB  
Article
Analysis of Available Conditions for InSAR Surface Deformation Monitoring in CCS Projects
by Tian Zhang, Wanchang Zhang, Ruizhao Yang, Huiran Gao and Dan Cao
Energies 2022, 15(2), 672; https://doi.org/10.3390/en15020672 - 17 Jan 2022
Cited by 10 | Viewed by 3180
Abstract
Carbon neutrality is a goal the world is striving to achieve in the context of global warming. Carbon capture and storage (CCS) has received extensive attention as an effective method to reduce carbon dioxide (CO2) in the atmosphere. What follows is [...] Read more.
Carbon neutrality is a goal the world is striving to achieve in the context of global warming. Carbon capture and storage (CCS) has received extensive attention as an effective method to reduce carbon dioxide (CO2) in the atmosphere. What follows is the migration pathway and leakage monitoring after CO2 injection. Interferometric synthetic aperture radar (InSAR) technology, with its advantages of extensive coverage in surface deformation monitoring and all-weather traceability of the injection processes, has become one of the promising technologies frequently adopted in worldwide CCS projects. However, there is no mature evaluation system to determine whether InSAR technology is suitable for each CO2 sequestration area. In this study, a new evaluation model is proposed based on the eight factors that are selected from the principle of the InSAR technique and the unique characteristics of the CO2 sequestration area. According to the proposed model, the feasibility of InSAR monitoring is evaluated for the existing typical sequestration areas in the world. Finally, the challenges and prospects of InSAR in the CCS project are discussed. Full article
(This article belongs to the Special Issue Advances in Methane Production from Coal, Shale and Other Tight Rocks)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>CCS project distribution map.</p> Full article ">Figure 2
<p>The graphs show the vegetation coverage of Salah, Jingbian, and Ketzin. The base map is the true color composite image of LANDSAT 8 OLI. (<b>a1</b>–<b>c1</b>) show the location of the injection wells and their buffers in the study area. (<b>a2</b>–<b>c2</b>) show their corresponding FVC index with a resolution of 500 m. (<b>a3</b>–<b>c3</b>) illustrate the proportion of the vegetation coverage classification in each study area, and their <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mrow> <mi>F</mi> <mi>V</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math> scores.</p> Full article ">Figure 3
<p>The graphs show the topographic parameters of Shizhuang, Shaanxi Province, China. (<b>a</b>) shows the DEM extracted using a UAV. (<b>b</b>) and (<b>c</b>) show the slope and aspect parameters extracted from the DEM. (<b>d</b>) illustrates the <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>I</mi> <mi>n</mi> <mi>d</mi> <mi>e</mi> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math> of the injection area and the <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mrow> <mi>t</mi> <mi>e</mi> <mi>r</mi> <mi>r</mi> <mi>a</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> score calculated from the distribution.</p> Full article ">Figure 4
<p>The graphs show the LULC of Scurry and San Juan. The base map is the true color composite image of LANDSAT 8 OLI. (<b>a1</b>,<b>b1</b>) show the location of the injection wells and their buffers in the study area. (<b>a2</b>,<b>b2</b>) show their LULC classification with a resolution of 30 m. (<b>a3</b>,<b>b3</b>) illustrate the proportion of the LULC classification in each study area, and the calculated <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mrow> <mi>L</mi> <mi>U</mi> <mi>L</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math> score.</p> Full article ">Figure 5
<p>A multi-method monitoring system.</p> Full article ">
15 pages, 1943 KiB  
Article
An Improved Charge-Based Method Extended to Estimating Appropriate Dead Time for Zero-Voltage-Switching Analysis in Dual-Active-Bridge Converter
by Haoyu Zhang and Takanori Isobe
Energies 2022, 15(2), 671; https://doi.org/10.3390/en15020671 - 17 Jan 2022
Cited by 4 | Viewed by 1860
Abstract
This paper presents a comprehensive analysis of zero-voltage-switching (ZVS) realization with an improved charge-based method by considering both voltage dependency parasitic capacitance and dead time in dual-active-bridge (DAB) converters, when the voltage ratio between the primary and secondary sides does not match the [...] Read more.
This paper presents a comprehensive analysis of zero-voltage-switching (ZVS) realization with an improved charge-based method by considering both voltage dependency parasitic capacitance and dead time in dual-active-bridge (DAB) converters, when the voltage ratio between the primary and secondary sides does not match the turn ratio of the transformer. For this purpose, a unified equivalent circuit is proposed to represent the switching motions at all possible switching instances under the condition of one-leg manipulation. The combinations of switching cases can be presented in a table to build the corresponding equivalent circuit for ZVS analysis. Combined with the improved charge-based method, the common solutions of the minimum required switching current and the appropriate dead-time range for each equivalent circuit to realize ZVS are deduced. The allowable range of the dead time for ZVS as a function of the switching current is analyzed to determine the appropriate dead time. Once the switching current and dead-time range are derived, the model-based lowest switching current control method can be used to achieve ZVS by using the appropriate amount of both factors. Experiments using a 4 kW DAB prototype were conducted to verify the theoretical analyses. Full article
(This article belongs to the Special Issue Power Converters: Modeling, Design and Applications)
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Figure 1
<p>Configuration of the dual-active-bridge (DAB) converter.</p> Full article ">Figure 2
<p>Schematic waveforms of the DAB converter with the (<b>a</b>) SPS modulation, (<b>b</b>) EPS modulation, and (<b>c</b>) TPS modulation.</p> Full article ">Figure 3
<p>Unified equivalent circuit of the DAB converter, in which all the possible switching instances can be analyzed.</p> Full article ">Figure 4
<p>Equivalent circuits for analyzing ZVS: (<b>a</b>) for <math display="inline"><semantics> <msub> <mi>S</mi> <mi mathvariant="normal">U</mi> </msub> </semantics></math> turning on and (<b>b</b>) for <math display="inline"><semantics> <msub> <mi>S</mi> <mi mathvariant="normal">L</mi> </msub> </semantics></math> turning on. The required initial directions of currents to achieve ZVS are also shown in the circuits.</p> Full article ">Figure 5
<p>Schematic waveforms of the drain–source voltages and the inductor current with a long enough dead-time period of critical switchings, (<b>a</b>) for the condition of <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>dc</mi> </msub> <mo>&gt;</mo> <mn>0</mn> </mrow> </semantics></math>, and (<b>b</b>) for the condition of <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>dc</mi> </msub> <mo>&lt;</mo> <mn>0</mn> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>Schematic view of the range of dead-time durations, <math display="inline"><semantics> <msub> <mi>t</mi> <mi mathvariant="normal">d</mi> </msub> </semantics></math>, as function of <math display="inline"><semantics> <msup> <mrow> <msub> <mi>I</mi> <mi mathvariant="normal">m</mi> </msub> </mrow> <mo>*</mo> </msup> </semantics></math> in the conditions of (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>dc</mi> </msub> <mo>&gt;</mo> <mn>0</mn> </mrow> </semantics></math> and (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>dc</mi> </msub> <mo>&lt;</mo> <mn>0</mn> </mrow> </semantics></math>.</p> Full article ">Figure 7
<p>Overview of (<b>a</b>) fabricated 4 kW experimental setup and (<b>b</b>) back side of the single DAB board.</p> Full article ">Figure 8
<p>Lower and upper limits of the dead-time duration for ZVS shown as solid lines, and experimentally measured boundary operating points shown as star marks in the conditions of (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>0.67</mn> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>dc</mi> </msub> <mo>&gt;</mo> <mn>0</mn> </mrow> </semantics></math>), and (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>1.5</mn> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>dc</mi> </msub> <mo>&lt;</mo> <mn>0</mn> </mrow> </semantics></math>). Some example operating points discussed in this section are marked as A, B, C, and D, and resulting settings for operations are marked as E and F.</p> Full article ">Figure 9
<p>Zoomed waveforms around critical switching transients with the operating points outside of dead-time range for ZVS as example points, (<b>a</b>) marked as A, (<b>b</b>) marked as B, and (<b>c</b>) marked as C in <a href="#energies-15-00671-f008" class="html-fig">Figure 8</a>.</p> Full article ">Figure 10
<p>Zoomed waveforms around critical switching transient with the operating point at the experimental minimal switching current indicated as point D in <a href="#energies-15-00671-f008" class="html-fig">Figure 8</a>a.</p> Full article ">Figure 11
<p>Zoomed waveforms around critical switching transients with enough margin of initial switching current and dead-time as example points (<b>a</b>) marked as E, (<b>b</b>) marked as F in <a href="#energies-15-00671-f008" class="html-fig">Figure 8</a>.</p> Full article ">
16 pages, 6549 KiB  
Article
Modal Analysis of Tubing Considering the Effect of Fluid–Structure Interaction
by Jiehao Duan, Changjun Li and Jin Jin
Energies 2022, 15(2), 670; https://doi.org/10.3390/en15020670 - 17 Jan 2022
Cited by 10 | Viewed by 2582
Abstract
When tubing is in a high-temperature and high-pressure environment, it will be affected by the impact of non-constant fluid and other dynamic loads, which will easily cause the tubing to vibrate or even resonate, affecting the integrity of the wellbore and safe production. [...] Read more.
When tubing is in a high-temperature and high-pressure environment, it will be affected by the impact of non-constant fluid and other dynamic loads, which will easily cause the tubing to vibrate or even resonate, affecting the integrity of the wellbore and safe production. In the structural modal analysis of the tubing, the coupling effect of the fluid and the tubing needs to be considered at the same time. In this paper, a single tubing is taken as an example to simulate and analyze the modal changes of the tubing under dry mode and wet mode respectively, and the effects of fluid solid coupling effect, inlet pressure, and ambient temperature on the modal of the tubing are discussed. After considering the fluid–structure interaction effect, the natural frequency of tubing decreases, but the displacement is slightly larger. The greater the pressure in the tubing, the greater the equivalent stress on the tubing body, so the natural frequency is lower. Furthermore, after considering the fluid–solid coupling effect, the pressure in the tubing is the true pulsating pressure of the fluid. The prestress applied to the tubing wall changes with time, and the pressures at different parts are different. At this time, the tubing is changed at different frequencies. Vibration is prone to occur, that is, the natural frequency is smaller than the dry mode. The higher the temperature, the lower the rigidity of the tubing and the faster the strength attenuation, so the natural frequency is lower, and tubing is more prone to vibration. Both the stress intensity and the elastic strain increase with the increase of temperature, so the displacement of the tubing also increases. Full article
(This article belongs to the Collection State of the Art Geo-Energy Technology in China)
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Figure 1

Figure 1
<p>Mesh of single tubing model.</p> Full article ">Figure 2
<p>Three dimensional stress diagram of hexahedral element of tubing.</p> Full article ">Figure 3
<p>Comparison of natural frequencies of tubing under two constraints.</p> Full article ">Figure 4
<p>First-order Y-direction bending state of tubing under two constraints.</p> Full article ">Figure 5
<p>First-order X-direction bending state of tubing under two constraints.</p> Full article ">Figure 6
<p>First-order torsional mode of tubing under two constraints.</p> Full article ">Figure 7
<p>Second-order X-direction bending modes of tubing under two constraints.</p> Full article ">Figure 8
<p>Third-order X-direction bending modes of tubing under two constraints.</p> Full article ">Figure 9
<p>Finite element model of the tubing and the fluid in the tubing. ((<b>a</b>) is the tubing model and (<b>b</b>) is the fluid model).</p> Full article ">Figure 10
<p>Mesh generation of the tubing and the fluid in the tubing ((<b>a</b>) is the tubing mesh and (<b>b</b>) is the fluid mesh).</p> Full article ">Figure 11
<p>Pressure load caused by fluid flow in tubing inner wall.</p> Full article ">Figure 12
<p>Natural frequencies of tubing under two modal analysis methods ((<b>a</b>) is natural frequencies of tubing under two modal analysis methods, (<b>b</b>) is difference of natural frequency of tubing under two modal analysis methods).</p> Full article ">Figure 13
<p>Maximum displacement of tubing under two modal analysis methods.</p> Full article ">Figure 14
<p>Influence of fluid-structure interaction effect on natural frequency of tubing under different inlet pressure.</p> Full article ">Figure 15
<p>Maximum displacement of tubing under different inlet pressure.</p> Full article ">Figure 16
<p>Maximum displacement of tubing under different temperatures.</p> Full article ">Figure 17
<p>Stress intensity and strain of tubing at different temperatures.</p> Full article ">
16 pages, 1772 KiB  
Article
Analysis and Evaluation of the Photovoltaic Market in Poland and the Baltic States
by Ewa Chomać-Pierzecka, Andrzej Kokiel, Joanna Rogozińska-Mitrut, Anna Sobczak, Dariusz Soboń and Jacek Stasiak
Energies 2022, 15(2), 669; https://doi.org/10.3390/en15020669 - 17 Jan 2022
Cited by 37 | Viewed by 3550
Abstract
The household, industrial, and service sectors in Poland and the Baltic States have been facing ever-higher bills for their electricity consumption at a time when a number of them have been hit hard financially by the pandemic. Rising inflation, the border crisis—with its [...] Read more.
The household, industrial, and service sectors in Poland and the Baltic States have been facing ever-higher bills for their electricity consumption at a time when a number of them have been hit hard financially by the pandemic. Rising inflation, the border crisis—with its set of restrictions, or the spread of the fourth wave of the COVID-19 coronavirus pandemic, is causing strong concerns in the social and economic sphere, with significant increases in electricity prices. Many countries are implementing measures to reduce the adverse effects of rising electricity prices in response to this complex situation. The main orientation is towards obtaining energy from renewable sources, such as the sun. The current situation in the energy market determines the price per 1 KW. Among the countries under study, the price of electricity has increased the most in Poland. On the other hand, the development of the photovoltaic segment in Poland is undergoing a strong, upward trend. The above inspired the authors to explore the energy market situation in Poland and the Baltic States in the current economic conditions, along with an analysis of its development potential in light of the coronavirus pandemic. The main research problem of this study is an attempt to answer the question of what should be changed in the development of the renewable energy market in Poland, with particular emphasis on photovoltaics, to accelerate the process of reducing CO2 emissions, leading to a reduction in dramatically rising electricity prices. Which solutions implemented in the Baltic countries can inspire strengthening Poland’s energy market development? Full article
(This article belongs to the Special Issue The Effect of COVID-19 Pandemic on the Energy Economics and Markets in Central and Eastern Europe)
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Figure 1

Figure 1
<p>Research algorithm [<a href="#B38-energies-15-00669" class="html-bibr">38</a>].</p> Full article ">Figure 2
<p>The evolution of average electricity prices per 100 KWh between 2019 and 2021 in the European Union [<a href="#B41-energies-15-00669" class="html-bibr">41</a>].</p> Full article ">Figure 3
<p>The growth trend in electricity exchange prices in Poland is October 2020–September 2021 [<a href="#B45-energies-15-00669" class="html-bibr">45</a>].</p> Full article ">Figure 4
<p>The trend in electricity exchange prices in the European Union from January 2011 to September 2021. [<a href="#B46-energies-15-00669" class="html-bibr">46</a>].</p> Full article ">Figure 5
<p>Distribution of the share of solar energy in the total volume of electricity production in Poland and the Baltic States [<a href="#B60-energies-15-00669" class="html-bibr">60</a>,<a href="#B61-energies-15-00669" class="html-bibr">61</a>].</p> Full article ">Figure 6
<p>The change average exchange rate of the Polish currency (PLN) against the currency of the Baltic countries (Euro) in the period 1 December 2019–1 September 2021 [<a href="#B68-energies-15-00669" class="html-bibr">68</a>].</p> Full article ">
21 pages, 6651 KiB  
Article
Elliptical-Shaped Fresnel Lens Design through Gaussian Source Distribution
by Dário Garcia, Dawei Liang, Joana Almeida, Bruno D. Tibúrcio, Hugo Costa, Miguel Catela and Cláudia R. Vistas
Energies 2022, 15(2), 668; https://doi.org/10.3390/en15020668 - 17 Jan 2022
Cited by 2 | Viewed by 3300
Abstract
A novel three-dimensional elliptical-shaped Fresnel lens (ESFL) analytical model is presented to evaluate and maximize the solar energy concentration of Fresnel-lens-based solar concentrators. AutoCAD, Zemax and Ansys software were used for the ESFL design, performance evaluation and temperature calculation, respectively. Contrary to the [...] Read more.
A novel three-dimensional elliptical-shaped Fresnel lens (ESFL) analytical model is presented to evaluate and maximize the solar energy concentration of Fresnel-lens-based solar concentrators. AutoCAD, Zemax and Ansys software were used for the ESFL design, performance evaluation and temperature calculation, respectively. Contrary to the previous modeling processes, based on the edge-ray principle with an acceptance half-angle of ±0.27° as the key defining parameter, the present model uses, instead, a Gaussian distribution to define the solar source in Zemax. The results were validated through the numerical analysis of published experimental data from a flat Fresnel lens. An in-depth study of the influence of several ESFL factors, such as focal length, arch height and aspect ratio, on its output performance is carried out. Moreover, the evaluation of the ESFL output performance as a function of the number/size of the grooves is also analyzed. Compared to the typical 1–16 grooves per millimeter reported in the previous literature, this mathematical parametric modeling allowed a substantial reduction in grooves/mm to 0.3–0.4, which may enable an easy mass production of ESFL. The concentrated solar distribution of the optimal ESFL configuration was then compared to that of the best flat Fresnel lens configuration, under the same focusing conditions. Due to the elliptical shape of the lens, the chromatic aberration effect was largely reduced, resulting in higher concentrated solar flux and temperature. Over 2360 K and 1360 K maximum temperatures were found for ESFL and flat Fresnel lenses, respectively, demonstrating the great potential of the three-dimensional curved-shaped Fresnel lens on renewable solar energy applications that require high concentrations of solar fluxes and temperatures. Full article
(This article belongs to the Special Issue Challenge and Research Trends of Solar Concentrators)
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Figure 1

Figure 1
<p>(<b>a</b>) Cross-sectional representation of an elliptical-shaped Fresnel lens (ESFL). <span class="html-italic">2θa</span> represents the subtended angle of the Sun to the Earth and <span class="html-italic">2θ<sub>E</sub></span> the solar–terrestrial angle after the passage of the solar rays through the atmosphere. (<b>b</b>) 3D representation of the ESFL.</p> Full article ">Figure 2
<p>Segment of an ellipse used as an outline for ESFL. “<span class="html-italic">a</span>” and “<span class="html-italic">b</span>” are the major and minor axis of the ellipse. “<span class="html-italic">b</span>” is the sum of the height of the arch (<span class="html-italic">h<sub>l</sub></span>) and the focal length (<span class="html-italic">h<sub>f</sub></span>) and <span class="html-italic">ω</span> is the rim angle of the Fresnel lens.</p> Full article ">Figure 3
<p>(<b>a</b>) Representation of a half-segment of an ESFL. The region defined by point A to B represents the first segment of the ellipse and the input facet of the first prism. The size of the prism is defined by angle <span class="html-italic">δω</span>. The point <span class="html-italic">O</span> represents the origin point and focal zone. <span class="html-italic">AO</span> and <span class="html-italic">BO</span> are the distances between the focal zone with the vertexes <span class="html-italic">A</span> and <span class="html-italic">B</span> of the prism, respectively. (<b>b</b>) Detailed visualization of a single prism. The incoming solar rays are refracted by the prism, outputting an angle ω in relation to the normal of its output facet, thus guaranteeing the concentration of light to the focal zone. <span class="html-italic">AB</span> segment is the input facet. Both <span class="html-italic">AC</span> and <span class="html-italic">AD</span> segments represent the output facet, whereas both <span class="html-italic">BC</span> and <span class="html-italic">BD</span> represent the back facet. The pitch angle (<span class="html-italic">θ<sub>p</sub></span>) defines the unused part of the prism.</p> Full article ">Figure 4
<p>Chaining process of the first three prisms of the ESFL. The thickness of the concentrator is attributed by offsetting the input facet by <span class="html-italic">d<sub>t</sub></span> from its original coordinate position.</p> Full article ">Figure 5
<p>Flowchart of ESFL modeling process.</p> Full article ">Figure 6
<p>Sequence diagram of a single numerical simulation.</p> Full article ">Figure 7
<p>3D view of the ESFL in AutoCAD.</p> Full article ">Figure 8
<p>Global and direct solar spectra ASTMG173 at AM1.5, with the selected wavelength used for ray tracing in Zemax and its respective weight value.</p> Full article ">Figure 9
<p>(<b>a</b>) Light propagation from a small light source towards a detector of size <span class="html-italic">d</span> at distance <span class="html-italic">L</span>. (<b>b</b>) Solar–terrestrial image with solar half-angle (<span class="html-italic">θ<sub>E</sub></span>) of 0.52°.</p> Full article ">Figure 10
<p>The focal image formed by ESFL modeled at 1000 W/mm<sup>2</sup> irradiance with the (<b>a</b>) Gaussian source and (<b>b</b>) collimated source.</p> Full article ">Figure 11
<p>(<b>a</b>) The ESFL and (<b>b</b>) the Ferriere Fresnel lens irradiated by five concentric solar sources with identical area and power. (<b>c</b>,<b>d</b>) Respective concentrated solar fluxes for the ESFL and the Ferriere lens, respectively; the combined solar fluxes are also given.</p> Full article ">Figure 12
<p>ESFL configuration with a combination of <span class="html-italic">h<sub>f</sub></span> and <span class="html-italic">h<sub>d</sub></span> for a total height of 700 mm.</p> Full article ">Figure 13
<p>Concentrated solar flux of the ESFL with a combined <span class="html-italic">h<sub>f</sub></span> + <span class="html-italic">h<sub>d</sub></span> of 700 mm as a function of <span class="html-italic">h<sub>l</sub></span> and aspect ratio.</p> Full article ">Figure 14
<p>(<b>a</b>) Concentrated solar flux, (<b>b</b>) optical efficiency and (<b>c</b>) FWHM of the ESFL configurations with <span class="html-italic">D</span> = 1 m at various <span class="html-italic">h<sub>f</sub></span> and <span class="html-italic">h<sub>l</sub></span> combinations.</p> Full article ">Figure 15
<p>Characteristics of the Gaussian distribution source at the focal zone: (<b>a</b>) number of grooves per <span class="html-italic">δω</span>, (<b>b</b>) concentrated solar flux, (<b>c</b>) optical efficiency and (<b>d</b>) FWHM.</p> Full article ">Figure 16
<p>Characteristic of the Gaussian distribution source at the focal zone: (<b>a</b>) <span class="html-italic">δω</span>, (<b>b</b>) concentrated solar flux, (<b>c</b>) optical efficiency and (<b>d</b>) FWHM as a function of the number of grooves.</p> Full article ">Figure 17
<p>(<b>a</b>) Three-dimensional focal distribution of the ESFL. (<b>b</b>) Top view of the light distribution at the focal point (Z = 0 mm). (<b>c</b>) Top view of the light distribution with the highest concentrated solar flux (Z = −5 mm).</p> Full article ">Figure 18
<p>(<b>a</b>) Three-dimensional focal distribution of the flat Fresnel lens. (<b>b</b>) Top view of the light distribution at the focal point (Z = 0 mm). (<b>c</b>) Top view of the light distribution with the highest concentrated solar flux (Z = 30 mm).</p> Full article ">Figure 19
<p>Focal temperature of ESFL (<b>a</b>) and flat Fresnel lens (<b>b</b>).</p> Full article ">
20 pages, 17197 KiB  
Article
A Transformerless AC-AC Converter with Improved Power Quality Employed to Step-Down Power Frequency at Output
by Naveed Ashraf, Ghulam Abbas, Nasim Ullah, Ahmad Aziz Al-Ahmadi, Abdul Rehman Yasin, Ahmed Bilal Awan and Mohsin Jamil
Energies 2022, 15(2), 667; https://doi.org/10.3390/en15020667 - 17 Jan 2022
Cited by 6 | Viewed by 3090
Abstract
Variable voltage and frequency are required to govern the torque-speed characteristics of many industrial drive systems. Traditionally, this is achieved with a power converting system implemented with multistage converters. This technology is based on rectifying AC power into DC and then DC into [...] Read more.
Variable voltage and frequency are required to govern the torque-speed characteristics of many industrial drive systems. Traditionally, this is achieved with a power converting system implemented with multistage converters. This technology is based on rectifying AC power into DC and then DC into AC with an inverter circuit. The power quality concerns of both conversion stages are tackled by selecting high switching frequency PWM control and harmonics mitigation filters. Also, using a bulky DC-link capacitor is one of the big sources of low system reliability, so this approach increases the conversion losses, circuit, and control complications. The frequency step-down conversion is very attractive with direct AC-AC converters as it has a simple control and circuit structure, but these converters face poor power quality challenges once the output frequency is decreased with respect to an input. In these converters, the total harmonic distortion (THD) of the output voltage becomes very poor once the output frequency is reduced. The problem of high THD of the output is addressed in the power converting circuits implemented with line frequency multi-winding transformers. The required number of output winding and switching devices (diodes and thyristors) increases once the value of the output frequency is decreased. This will increase the overall volume, cost, and losses. The use of a bulky and costly line frequency transformer may be eliminated if AC voltage controllers have non-inverted and inverted voltage buck capabilities, such existing topologies either have complex control schemes or require a large number of operating devices. Therefore, in this research article, a new transformerless frequency step-down converter employing fewer devices is proposed. This approach is realized with a high-frequency controlled rectifier for the required voltage stabilization and a low-frequency inverter bridge for frequency control. Its validation is supported by the results attained from Simulink and practical-based prototypes. Full article
(This article belongs to the Special Issue Design and Investigation of Power Electronics Converters and Its Control)
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Figure 1
<p>Frequency converter established in [<a href="#B25-energies-15-00667" class="html-bibr">25</a>].</p> Full article ">Figure 2
<p>Created circuit’s arrangement.</p> Full article ">Figure 3
<p>Expected outputs of (<b>a</b>) absolute value voltage controller and (<b>b</b>) frequency controller.</p> Full article ">Figure 4
<p>Control inputs applied to switching transistors of (<b>a</b>) absolute value voltage controller circuit and (<b>b</b>) frequency controller circuit.</p> Full article ">Figure 5
<p>Power transferring loops to obtain the non-inverted form at the output with (<b>a</b>,<b>b</b>) positive input value; (<b>c</b>,<b>d</b>) negative input value.</p> Full article ">Figure 6
<p>Power transferring loops to obtain the inverted form at the output for (<b>a</b>,<b>b</b>) positive input value; (<b>c</b>,<b>d</b>) negative input value.</p> Full article ">Figure 6 Cont.
<p>Power transferring loops to obtain the inverted form at the output for (<b>a</b>,<b>b</b>) positive input value; (<b>c</b>,<b>d</b>) negative input value.</p> Full article ">Figure 7
<p>Decomposition of the output voltage into its parent sinusoidal pulses.</p> Full article ">Figure 8
<p>Output voltage waveform with <span class="html-italic">D</span> = 1.</p> Full article ">Figure 9
<p>Output voltage waveform with <span class="html-italic">D</span> = 0.5.</p> Full article ">Figure 10
<p>Generation of control signals: (<b>a</b>) proposed circuit; (<b>b</b>) circuit in [<a href="#B26-energies-15-00667" class="html-bibr">26</a>]; (<b>c</b>) circuit in [<a href="#B23-energies-15-00667" class="html-bibr">23</a>].</p> Full article ">Figure 11
<p>Simulated results of frequency controller without voltage regulation: (<b>a</b>) input voltage; (<b>b</b>) output voltage; (<b>c</b>) FFT of the output voltage.</p> Full article ">Figure 12
<p>Simulated results of frequency controller with voltage regulation: (<b>a</b>) Input voltage; (<b>b</b>) output voltage; (<b>c</b>) FFT of the output voltage.</p> Full article ">Figure 13
<p>Photograph of practical setup.</p> Full article ">Figure 14
<p>Output (red) of voltage sensing circuit with respect to input AC voltage (blue).</p> Full article ">Figure 15
<p>Generation of the control signals: (<b>a</b>) low-frequency signal (red) with respect to input AC voltage (blue); (<b>b</b>) high-frequency PWM signal (red) with respect to low frequency signal (blue); (<b>c</b>) high-frequency PWM signals; (<b>d</b>) low- frequency signals.</p> Full article ">Figure 16
<p>Real value results of frequency controller without voltage regulation capability: (<b>a</b>) Input (blue) and output (red) voltage; (<b>b</b>) FFT of output voltage pulses.</p> Full article ">Figure 17
<p>Real value results of frequency controller with voltage regulation capability: (<b>a</b>) input (blue) and output (red) voltage; (<b>b</b>) FFT of output voltage pulses.</p> Full article ">
22 pages, 1336 KiB  
Article
An Analysis-Supported Design of a Single Active Bridge (SAB) Converter
by Rupesh Jha, Mattia Forato, Satya Prakash, Hemant Dashora and Giuseppe Buja
Energies 2022, 15(2), 666; https://doi.org/10.3390/en15020666 - 17 Jan 2022
Cited by 5 | Viewed by 3320
Abstract
Currently, due to its various applications, the high-performance isolated dc-dc converter is in demand. In applications where unidirectional power transfer is required, the single active bridge (SAB) is the most suitable one due to its simplicity and ease of control. The general schematic [...] Read more.
Currently, due to its various applications, the high-performance isolated dc-dc converter is in demand. In applications where unidirectional power transfer is required, the single active bridge (SAB) is the most suitable one due to its simplicity and ease of control. The general schematic of the SAB converter consists of an active bridge and a passive bridge, which are connected through a high-frequency transformer thus isolated. The paper summarizes the behavior of this converter in its three operation modes, namely the continuous, discontinuous, and boundary modes. Later, the features of this converter, such as its input-to-output and external characteristics are discussed. Input-to-output characteristics include the variation of converter output power, voltage, and current with an input control variable i.e., phase-shift angle, whereas the external characteristic is the variation of the output voltage as a function of output current. In this discussion, the behavior of this converter in its extreme operating conditions is also examined. The features of the characteristics are elucidated with the help of suitable plots obtained in the MATLAB environment. Afterward, the specifications of a SAB converter are given and, based on the results of the analysis, a detailed design of its electrical elements is carried out. To validate the features and the design procedures presented in this paper, a prototype is developed. An element-wise loss estimation is also carried out and the efficiency of the converter has been found to be approximately equal to 93%. Lastly, the test was executed on this prototype, confirming the theoretical findings concerning this converter. Full article
(This article belongs to the Collection Electrical Power and Energy System: From Professors to Students)
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<p>General schematic of an isolated dc-dc converter.</p> Full article ">Figure 2
<p>Methodology used for the article.</p> Full article ">Figure 3
<p>Circuit diagram of a SAB converter.</p> Full article ">Figure 4
<p>Voltages and currents waveforms of the SAB converter operating in (<b>a</b>) CCM (<b>b</b>) BCM (<b>c</b>) DCM.</p> Full article ">Figure 5
<p>Currents paths and devices conduction of the SAB converter during (<b>a</b>) interval 1 [0 <span class="html-italic">÷ φ</span>], (<b>b</b>) interval 2 [<span class="html-italic">φ</span> ÷ <span class="html-italic">β</span>] (<b>c</b>) interval 3 [<span class="html-italic">β</span> ÷ <span class="html-italic">π</span>].</p> Full article ">Figure 6
<p>SAB converter output power vs. the phase-shift angle for different values of the output voltage. Continuous curves refer to CCM whereas the dashed ones refer to DCM.</p> Full article ">Figure 7
<p>SAB converter output voltage vs. the phase-shift angle for different values of load resistance. Continuous curves refer to CCM, whereas the dashed ones refer to DCM.</p> Full article ">Figure 8
<p>SAB converter output current vs. the phase-shift angle for different values of the output voltage. Continuous curves refer to CCM whereas the dashed ones refer to DCM.</p> Full article ">Figure 9
<p>External characteristic of the SAB converter. Continuous curves refer to CCM whereas the dashed ones refer to DCM.</p> Full article ">Figure 10
<p>Value of <span class="html-italic">i<sub>L,pu</sub>(β)</span> as a function of the average current delivered by the SAB converter for different values of the output voltage. Continuous curves refer to CCM, whereas the dashed ones refer to DCM.</p> Full article ">Figure 11
<p>Waveform of the current i<sub>out</sub>; colored areas represent the charge ∆Q.</p> Full article ">Figure 12
<p>Plot of <span class="html-italic">I<sub>L,rms</sub></span> (primary and secondary referred) vs. transformer turn ratio <span class="html-italic">n</span> for L equal to 168 µH. The sum of the two currents is also shown.</p> Full article ">Figure 13
<p>Nominal working point of the prototypal SAB converter.</p> Full article ">Figure 14
<p>Flow chart for SAB elements design.</p> Full article ">Figure 15
<p>Experimental waveforms for SAB in CCM mode; (<b>a</b>) <span class="html-italic">v</span><sub>2</sub> (channel 1) and <span class="html-italic">v</span><sub>1</sub> (channel 2). (<b>b</b>) <span class="html-italic">v</span><sub>2</sub> (channel 1) and <span class="html-italic">i<sub>L</sub></span> (channel 2, 1 V correspond to 2 A).</p> Full article ">Figure 16
<p>Experimental waveforms for SAB in DCM mode; (<b>a</b>) <span class="html-italic">v</span><sub>2</sub> (channel 1) and <span class="html-italic">v</span><sub>1</sub> (channel 2). (<b>b</b>) <span class="html-italic">v</span><sub>2</sub> (channel 1) and <span class="html-italic">i<sub>L</sub></span> (channel 2, 1 V correspond to 2 A).</p> Full article ">Figure 17
<p>Validation of theoretical findings: (<b>a</b>) <span class="html-italic">P<sub>o,pu</sub></span> vs. <span class="html-italic">β<sub>pu</sub></span>, (<b>b</b>) <span class="html-italic">V<sub>o,pu</sub></span> vs. <span class="html-italic">β<sub>pu</sub></span>, (<b>c</b>) <span class="html-italic">I<sub>o,pu</sub></span> vs. <span class="html-italic">β<sub>pu</sub></span>, (<b>d</b>) <span class="html-italic">V<sub>o.pu</sub></span> vs. <span class="html-italic">β<sub>pu</sub></span>. The continuous curves refer to CCM, the dashed ones refer to DCM and the stars represent experimental results.</p> Full article ">
18 pages, 8477 KiB  
Article
Reliability-as-a-Service Usage of Electric Vehicles: Suitability Analysis for Different Types of Buildings
by Akhtar Hussain and Petr Musilek
Energies 2022, 15(2), 665; https://doi.org/10.3390/en15020665 - 17 Jan 2022
Cited by 5 | Viewed by 1791
Abstract
The use of electric vehicles (EVs) to provide different grid services is becoming possible due to the increased penetration levels, mileage efficiencies, and useable battery sizes of EVs. One such application is providing reliability-as-a-service (RaaS) during short-term power outages. Instead of using a [...] Read more.
The use of electric vehicles (EVs) to provide different grid services is becoming possible due to the increased penetration levels, mileage efficiencies, and useable battery sizes of EVs. One such application is providing reliability-as-a-service (RaaS) during short-term power outages. Instead of using a dedicated backup power source, EVs can be contracted to provide RaaS, which is an environmentally friendly solution with benefits for both building owners and EV owners. However, the presence of EVs at a particular location during different hours of the day and the availability of energy from EVs is uncertain. Therefore, in this study, a suitability analysis is performed concerning the use of EVs to provide RaaS for different types of buildings. First, the National Household Travel Survey (NHTS) survey data are used to estimate driver behavior, such as arrival/departure times, daily mileage, and traveling duration. Then, the usable battery size and mileage efficiency of EVs is extracted from the database of commercially available EVs. Based on these parameters, the daily energy consumption and available energy of EVs to provide RaaS are estimated. A suitability analysis is conducted for residential, commercial/industrial, and mixed buildings for both weekdays and holidays. The participation ratio of EV owners is varied between 10 and 90%, and nine cases are simulated for commercial/industrial buildings and multi-unit residential buildings. Similarly, the ratio of home-based EVs is varied between 5 and 50%, and 10 cases are tested for mixed buildings. The analysis shows that mixed buildings are the most suitable, while commercial/industrial buildings are the least suitable for using EVs to provide RaaS. To this end, an index is proposed to analyze and determine the desired ratio of EVs to be contracted from homes and workplaces for mixed buildings. Finally, the impact of EV fleet size on the available energy for RaaS is also analyzed. Full article
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<p>Flowchart for parameter extraction and suitability analysis of RaaS usage of EVs.</p> Full article ">Figure 2
<p>Daily mileage and per-trip travelling-duration histograms for vehicles.</p> Full article ">Figure 3
<p>Probability densities of arrival and departure times: (<b>a</b>) home; (<b>b</b>) workplace.</p> Full article ">Figure 4
<p>Cumulative densities for arrival/departure time for home/workplace.</p> Full article ">Figure 5
<p>Percent of vehicles staying at home/workplace during different hours of day.</p> Full article ">Figure 6
<p>Energy consumption and useable battery size of commercially available EVs.</p> Full article ">Figure 7
<p>Daily energy consumption of EVs during weekdays and holidays.</p> Full article ">Figure 8
<p>Useable energy for RaaS in EVs: (<b>a</b>) home; (<b>b</b>) workplace.</p> Full article ">Figure 9
<p>Results of useable energy in residential buildings for RaaS during weekdays.</p> Full article ">Figure 10
<p>Results of useable energy in residential buildings for RaaS during holidays.</p> Full article ">Figure 11
<p>Useable energy in resintial buildings for 50% participation case: (<b>a</b>) weekdays; (<b>b</b>) holidays.</p> Full article ">Figure 12
<p>Results of useable energy in commercial/industrail buildings for RaaS during weekdays.</p> Full article ">Figure 13
<p>Results of useable energy in commercial/industrial buildings for RaaS during holidays.</p> Full article ">Figure 14
<p>Useable energy in commercial/industrial buildings for 50% participation case: (<b>a</b>) weekdays; (<b>b</b>) holidays.</p> Full article ">Figure 15
<p>Results of useable energy in mixed buildings for RaaS during weekdays.</p> Full article ">Figure 16
<p>Results of useable energy in mixed buildings for RaaS during holidays.</p> Full article ">Figure 17
<p>Useable energy in mixed buildings for 50% participation with 35% home-based EVs case: (<b>a</b>) weekdays; (<b>b</b>) holidays.</p> Full article ">Figure 18
<p>Variation index for different EV fleet sizes.</p> Full article ">Figure 19
<p>Available energy for RaaS under different EV fleet sizes.</p> Full article ">
14 pages, 1049 KiB  
Article
Structural Model of Power Grid Stabilization in the Green Hydrogen Supply Chain System—Conceptual Assumptions
by Marzena Frankowska, Marta Mańkowska, Marcin Rabe, Andrzej Rzeczycki and Elżbieta Szaruga
Energies 2022, 15(2), 664; https://doi.org/10.3390/en15020664 - 17 Jan 2022
Cited by 11 | Viewed by 3352
Abstract
The paper presents the conceptual assumptions of research concerning the design of a theoretical multi-criteria model of a system architecture to stabilize the operation of power distribution networks based on a hydrogen energy buffer, taking into account the utility application of hydrogen. The [...] Read more.
The paper presents the conceptual assumptions of research concerning the design of a theoretical multi-criteria model of a system architecture to stabilize the operation of power distribution networks based on a hydrogen energy buffer, taking into account the utility application of hydrogen. The basis of the research process was a systematic literature review using the technique of in-depth analysis of full-text articles and expert consultations. The structural model concept was described in two dimensions in which the identified variables were embedded. The first dimension includes the supply chain phases: procurement and production with warehousing and distribution. The second dimension takes into account a comprehensive and interdisciplinary approach and includes the following factors: technical, economic–logistical, locational, and formal–legal. Full article
(This article belongs to the Special Issue Financial Development and Energy Consumption Nexus)
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<p>Scheme of the research process.</p> Full article ">Figure 2
<p>Energy supply chain with hydrogen supply chain. Source: own elaboration.</p> Full article ">
20 pages, 4681 KiB  
Article
A Quantile Regression Random Forest-Based Short-Term Load Probabilistic Forecasting Method
by Sanlei Dang, Long Peng, Jingming Zhao, Jiajie Li and Zhengmin Kong
Energies 2022, 15(2), 663; https://doi.org/10.3390/en15020663 - 17 Jan 2022
Cited by 17 | Viewed by 2905
Abstract
In this paper, a novel short-term load forecasting method amalgamated with quantile regression random forest is proposed. Comprised with point forecasting, it is capable of quantifying the uncertainty of power load. Firstly, a bespoke 2D data preprocessing taking advantage of empirical mode decomposition [...] Read more.
In this paper, a novel short-term load forecasting method amalgamated with quantile regression random forest is proposed. Comprised with point forecasting, it is capable of quantifying the uncertainty of power load. Firstly, a bespoke 2D data preprocessing taking advantage of empirical mode decomposition (EMD) is presented. It can effectively assist subsequent point forecasting models to extract spatial features hidden in the 2D load matrix. Secondly, by exploiting multimodal deep neural networks (DNN), three short-term load point forecasting models are conceived. Furthermore, a tailor-made multimodal spatial–temporal feature extraction is proposed, which integrates spatial features, time information, load, and electricity price to obtain more covert features. Thirdly, relying on quantile regression random forest, the probabilistic forecasting method is proposed, which exploits the results from the above three short-term load point forecasting models. Lastly, the experimental results demonstrate that the proposed method outperforms its conventional counterparts. Full article
(This article belongs to the Special Issue Modeling, Analysis and Control of Power System Distribution Networks)
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<p>Structure diagram of point forecasting model based on VGGNet and LSTM.</p> Full article ">Figure 2
<p>Structure diagram of point forecasting model based on Inception and LSTM.</p> Full article ">Figure 3
<p>Inception module internal structure diagram.</p> Full article ">Figure 4
<p>Structure diagram of point forecasting model based on ResNet and LSTM.</p> Full article ">Figure 5
<p>The frame diagram of the short-term load probabilistic forecasting method based on quantile regression random forest.</p> Full article ">Figure 6
<p>Short-term load probabilistic forecasting results within 48 h on weekdays.</p> Full article ">Figure 7
<p>Short-term load probabilistic forecasting results within 48 h on weekend.</p> Full article ">Figure 8
<p>Short-term load probabilistic forecast for the week from 2 August 2019 to 8 August 2019.</p> Full article ">
23 pages, 7794 KiB  
Article
Development of Photovoltaic Energy in EU Countries as an Alternative to Fossil Fuels
by Radosław Wolniak and Bożena Skotnicka-Zasadzień
Energies 2022, 15(2), 662; https://doi.org/10.3390/en15020662 - 17 Jan 2022
Cited by 33 | Viewed by 4070
Abstract
The aim of the article is to present the development of photovoltaic energy in the EU countries as one of the alternatives to fossil fuels. The article was prepared on the basis of secondary information and statistical data on the photovoltaic energy market [...] Read more.
The aim of the article is to present the development of photovoltaic energy in the EU countries as one of the alternatives to fossil fuels. The article was prepared on the basis of secondary information and statistical data on the photovoltaic energy market in EU countries, and three hypotheses were formulated: H1—There is a statistically significant correlation between a country’s long-term orientation and its use of photovoltaic energy in European Union countries; H2—There is a statistically significant correlation between GDP per capita and photovoltaic energy use in European Union countries; and H3—There is a relationship between climate and photovoltaic energy use in European Union countries. Correlation coefficients and the Guilford classification were used to analyse the data. Data analysis has shown that photovoltaic energy is the second fastest-growing energy source in the EU, after wind energy. In 2020, 134 TWh of solar energy was produced in the EU countries. Based on the analysis, it can be concluded that there is a statistically significant correlation between the production of photovoltaic energy per person and the level of GDP per capita in the EU countries (Hypothesis 2). Germany and the Netherlands produce the most solar energy. The studies did not confirm Hypothesis 3; however, it can be seen that countries such as Germany, Belgium and the Netherlands have the highest PV energy efficiency compared to average temperature values. A data analysis showed statistically significant correlations between the country’s long-term orientation in the use of photovoltaic energy (Hypothesis 1). In the case of Germany and Belgium, the long-term orientation indicator is very high above 80, while Portugal, Poland and Finland have the lowest indicator, from 30 to 40. Full article
(This article belongs to the Special Issue Economics and Management in Extractive and Energy Industry)
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<p>Photovoltaic capacity additions in the European Union countries in 2019 (MW). Source: Own analyses based on data: [<a href="#B21-energies-15-00662" class="html-bibr">21</a>,<a href="#B22-energies-15-00662" class="html-bibr">22</a>,<a href="#B23-energies-15-00662" class="html-bibr">23</a>,<a href="#B24-energies-15-00662" class="html-bibr">24</a>,<a href="#B25-energies-15-00662" class="html-bibr">25</a>,<a href="#B26-energies-15-00662" class="html-bibr">26</a>,<a href="#B27-energies-15-00662" class="html-bibr">27</a>].</p> Full article ">Figure 2
<p>The photovoltaic capacity addictions in EU countries in the years 2014–2019 (MW). Source: Own analyses based on data: [<a href="#B21-energies-15-00662" class="html-bibr">21</a>,<a href="#B22-energies-15-00662" class="html-bibr">22</a>,<a href="#B23-energies-15-00662" class="html-bibr">23</a>,<a href="#B24-energies-15-00662" class="html-bibr">24</a>,<a href="#B25-energies-15-00662" class="html-bibr">25</a>,<a href="#B26-energies-15-00662" class="html-bibr">26</a>,<a href="#B27-energies-15-00662" class="html-bibr">27</a>].</p> Full article ">Figure 3
<p>Photovoltaic capacity installed in European Union countries in year 2019. Source: Own analyses based on data: [<a href="#B21-energies-15-00662" class="html-bibr">21</a>,<a href="#B22-energies-15-00662" class="html-bibr">22</a>,<a href="#B23-energies-15-00662" class="html-bibr">23</a>,<a href="#B24-energies-15-00662" class="html-bibr">24</a>,<a href="#B25-energies-15-00662" class="html-bibr">25</a>,<a href="#B26-energies-15-00662" class="html-bibr">26</a>,<a href="#B27-energies-15-00662" class="html-bibr">27</a>,<a href="#B54-energies-15-00662" class="html-bibr">54</a>,<a href="#B55-energies-15-00662" class="html-bibr">55</a>,<a href="#B56-energies-15-00662" class="html-bibr">56</a>,<a href="#B57-energies-15-00662" class="html-bibr">57</a>,<a href="#B58-energies-15-00662" class="html-bibr">58</a>,<a href="#B59-energies-15-00662" class="html-bibr">59</a>,<a href="#B60-energies-15-00662" class="html-bibr">60</a>,<a href="#B61-energies-15-00662" class="html-bibr">61</a>,<a href="#B62-energies-15-00662" class="html-bibr">62</a>,<a href="#B76-energies-15-00662" class="html-bibr">76</a>].</p> Full article ">Figure 4
<p>Photovoltaic installed capacity in years 2014–2019—European Union countries. Source: Authors’ own analysis based on data in [<a href="#B21-energies-15-00662" class="html-bibr">21</a>,<a href="#B22-energies-15-00662" class="html-bibr">22</a>,<a href="#B23-energies-15-00662" class="html-bibr">23</a>,<a href="#B24-energies-15-00662" class="html-bibr">24</a>,<a href="#B25-energies-15-00662" class="html-bibr">25</a>,<a href="#B26-energies-15-00662" class="html-bibr">26</a>,<a href="#B27-energies-15-00662" class="html-bibr">27</a>,<a href="#B79-energies-15-00662" class="html-bibr">79</a>].</p> Full article ">Figure 5
<p>Photovoltaic capacity in European Union countries per inhabitant in 2019 (W/inhabitant). Source: Authors own analysis based on data in [<a href="#B21-energies-15-00662" class="html-bibr">21</a>,<a href="#B22-energies-15-00662" class="html-bibr">22</a>,<a href="#B23-energies-15-00662" class="html-bibr">23</a>,<a href="#B24-energies-15-00662" class="html-bibr">24</a>,<a href="#B25-energies-15-00662" class="html-bibr">25</a>,<a href="#B26-energies-15-00662" class="html-bibr">26</a>,<a href="#B27-energies-15-00662" class="html-bibr">27</a>].</p> Full article ">Figure 6
<p>Relationship between GDP/per capita and W/inhabitant of photovoltaic capacity for the countries analysed. Source: Authors’ own analysis.</p> Full article ">Figure 7
<p>Relationship between national average temperature and W/inhabitant of photovoltaic power. Source: Authors’ own analysis.</p> Full article ">Figure 8
<p>Relationship between long-term orientation of the country and W/inhabitant of photovoltaic capacity. Source: Authors’ own analysis.</p> Full article ">
23 pages, 2274 KiB  
Article
Assessment of the Feasibility of Energy Transformation Processes in European Union Member States
by Michał Bernard Pietrzak, Magdalena Olczyk and Marta Ewa Kuc-Czarnecka
Energies 2022, 15(2), 661; https://doi.org/10.3390/en15020661 - 17 Jan 2022
Cited by 18 | Viewed by 2562
Abstract
The energy transition is now treated in most countries as a necessary condition for their long-term development. The process of energy transformation assumes the simultaneous implementation of the Sustainable Development Goals, which are a major challenge for modern economies and introduce significant restrictions [...] Read more.
The energy transition is now treated in most countries as a necessary condition for their long-term development. The process of energy transformation assumes the simultaneous implementation of the Sustainable Development Goals, which are a major challenge for modern economies and introduce significant restrictions in their functioning. Our study aims to group EU member states according to their ability to achieve energy transition over time. The novelty of our approach is the assessment of energy transformation in the European Union through two aspects. The first one, “smart and efficient energy systems”, assess the current, widely understood energy consumption in economy, and the second one, “macroeconomic heterogeneity”, refers to the economic potential of a country. In our analysis, we included indicators from the 7th, 8th, 10th, 11th, and 12th Sustainable Development Goals. Using taxonomic methods, we created clusters of countries according to the emissivity of their economies and the socio-economic potential for the energy transition. The analysis results revealed that countries vary more due to their emissivity than economic potential. Full article
(This article belongs to the Special Issue Transformation of Energy Markets: Description, Modeling of Functioning Mechanisms and Determining Development Trends)
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<p>Cluster dendrogram for “smart and efficient energy systems”. Source: Authors’ study based on [<a href="#B75-energies-15-00661" class="html-bibr">75</a>].</p> Full article ">Figure 2
<p>Choropleth map for “smart and efficient energy systems”. Source: Authors’ study based on [<a href="#B75-energies-15-00661" class="html-bibr">75</a>].</p> Full article ">Figure 3
<p>Cluster dendrogram for the “macroeconomic heterogeneity” aspect. Source: Authors’ study based on [<a href="#B75-energies-15-00661" class="html-bibr">75</a>].</p> Full article ">Figure 4
<p>Choropleth map for the “macroeconomic heterogeneity”. Source: Authors’ study based on [<a href="#B75-energies-15-00661" class="html-bibr">75</a>].</p> Full article ">Figure 5
<p>Cluster dendrogram for a holistic approach. Source: Authors’ study based on [<a href="#B75-energies-15-00661" class="html-bibr">75</a>].</p> Full article ">Figure 6
<p>Choropleth map for a holistic approach. Source: Authors’ study based on [<a href="#B75-energies-15-00661" class="html-bibr">75</a>].</p> Full article ">
35 pages, 15120 KiB  
Article
Optimising High-Rise Buildings for Self-Sufficiency in Energy Consumption and Food Production Using Artificial Intelligence: Case of Europoint Complex in Rotterdam
by Berk Ekici, Okan F. S. F. Turkcan, Michela Turrin, Ikbal Sevil Sariyildiz and Mehmet Fatih Tasgetiren
Energies 2022, 15(2), 660; https://doi.org/10.3390/en15020660 - 17 Jan 2022
Cited by 18 | Viewed by 3492
Abstract
The increase in global population, which negatively affects energy consumption, CO2 emissions, and arable land, necessitates designing sustainable habitation alternatives. Self-sufficient high-rise buildings, which integrate (electricity) generation and efficient usage of resources with dense habitation, can be a sustainable solution for future [...] Read more.
The increase in global population, which negatively affects energy consumption, CO2 emissions, and arable land, necessitates designing sustainable habitation alternatives. Self-sufficient high-rise buildings, which integrate (electricity) generation and efficient usage of resources with dense habitation, can be a sustainable solution for future urbanisation. This paper focuses on transforming Europoint Towers in Rotterdam into self-sufficient buildings considering energy consumption and food production (lettuce crops) using artificial intelligence. Design parameters consist of the number of farming floors, shape, and the properties of the proposed façade skin that includes shading devices. Nine thousand samples are collected from various floor levels to predict self-sufficiency criteria using artificial neural networks (ANN). Optimisation problems with 117 decision variables are formulated using 45 ANN models that have very high prediction accuracies. 13 optimisation algorithms are used for an in-detail investigation of self-sufficiency at the building scale, and potential sufficiency at the neighbourhood scale. Results indicate that 100% and 43.7% self-sufficiencies could be reached for lettuce crops and electricity, respectively, for three buildings with 1800 residents. At the neighbourhood scale, lettuce production could be sufficient for 27,000 people with a decrease of self-sufficiency in terms of energy use of up to 11.6%. Consequently, this paper discusses the potentials and the improvements for self-sufficient high-rise buildings. Full article
(This article belongs to the Special Issue Research Innovations for Advanced Analysis and Multi-Performance Driven Design in the Built Environment)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Utilisation of MUZO methodology for the self-sufficient Europoint complex.</p> Full article ">Figure 2
<p>Europoint complex in Rotterdam, the Netherlands.</p> Full article ">Figure 3
<p>Proposed building program.</p> Full article ">Figure 4
<p>Proposed façade design and building zones (subdivisions).</p> Full article ">Figure 5
<p>Thermal zones of energy model in residential and farming floors.</p> Full article ">Figure 6
<p>Schedules used in residential energy model.</p> Full article ">Figure 7
<p>BIPV allocation of Europoint complex.</p> Full article ">Figure 8
<p>Simulation result of <span class="html-italic">DF</span> for one design alternative in one floor level.</p> Full article ">Figure 9
<p>Monthly temperature comparisons between DB and HB.</p> Full article ">Figure 10
<p>Weekly temperature comparisons between DB and HB.</p> Full article ">Figure 11
<p>Weekly (W) temperatures of the farming system.</p> Full article ">Figure 12
<p>Distributions of collected samples.</p> Full article ">Figure 13
<p>Grid search results of the best ANN models.</p> Full article ">Figure 14
<p>MAE, MSE, and R<sup>2</sup> results of training and test sets.</p> Full article ">Figure 15
<p>Simulated results versus predicted results.</p> Full article ">Figure 16
<p>Boxplots of the feasible solutions.</p> Full article ">Figure 17
<p>Convergence of the algorithms in time to complete 7500 FES.</p> Full article ">Figure 18
<p>Average air temperatures of the optimised Europoint complex.</p> Full article ">Figure 19
<p>MUZO design versus 7776 typical scenarios.</p> Full article ">Figure 20
<p>Parameters of MUZO design and the best typical scenario.</p> Full article ">Figure 21
<p>Illustration of the optimised design for self-sufficiency at the building scale.</p> Full article ">Figure 22
<p>Search space and optimisation results of jEDE for stepwise run.</p> Full article ">Figure 23
<p>Search space and optimisation results of multi-objective algorithms.</p> Full article ">Figure 24
<p>Self-sufficiency potential of Europoint complex for neighbourhood scale.</p> Full article ">Figure 25
<p>Sufficiency diameter of Europoint complex in Rotterdam, the Netherlands.</p> Full article ">
14 pages, 30212 KiB  
Article
Alternative Fuel Generation from Dangerous Solid Waste in a Protected Environmental Area
by Pedro Mora, Daniel Barettino, Antonio Ponce, Laura Sánchez-Martín and Bernardo Llamas
Energies 2022, 15(2), 659; https://doi.org/10.3390/en15020659 - 17 Jan 2022
Cited by 1 | Viewed by 1529
Abstract
The present investigation project aims to evaluate the extraction of contaminant material from two settling ponds to be used as alternative fuel in two cement plants. The extraction is carried out through mechanical means, and after that extraction, two options are compared: energy [...] Read more.
The present investigation project aims to evaluate the extraction of contaminant material from two settling ponds to be used as alternative fuel in two cement plants. The extraction is carried out through mechanical means, and after that extraction, two options are compared: energy recovery and incineration. Through energy recovery, a potentially contaminated area is decontaminated and its waste is used; its high calorific value makes this option a viable one. The waste extraction is carried out through mechanical means due to the high density and viscosity of the waste. Because of these characteristics, the waste undergoes an on-site security adaptation to stabilize it, reduce declivity risk and make it suitable to be handled and moved. The second treatment is carried out in external installations where the final product is obtained (alternative fuel), which is to be used at industrial kilns. The entire described process shows a difference on the consumed energy of 6060.42 kWh/twaste between the two options under study: waste incineration and energy recovery. In addition, it also reduces CO2 emissions on 2.178 tCO2/twaste. Full article
(This article belongs to the Special Issue Circular Economy and Environmental Protection in the Upstream Petroleum Industry)
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<p>Aerial photo of the area under study.</p> Full article ">Figure 2
<p>Laguna Sureste. Solid hydrocarbon waste.</p> Full article ">Figure 3
<p>Treatment of the waste.</p> Full article ">Figure 4
<p>Graphical representation of the two alternatives.</p> Full article ">
29 pages, 4224 KiB  
Article
The Place of Energy Security in the National Security Framework: An Assessment Approach
by Daniel Mara, Silviu Nate, Andriy Stavytskyy and Ganna Kharlamova
Energies 2022, 15(2), 658; https://doi.org/10.3390/en15020658 - 17 Jan 2022
Cited by 34 | Viewed by 4911
Abstract
The term “energy security” is used almost everywhere in economic and political discussions related to energy supply. However, different authors use different meanings to express the concept of energy security. Quite often, this term is used to give more importance or relevance to [...] Read more.
The term “energy security” is used almost everywhere in economic and political discussions related to energy supply. However, different authors use different meanings to express the concept of energy security. Quite often, this term is used to give more importance or relevance to issues that are often not inherently related to energy security. Attempts to define the essence of the concept of “energy security” have hitherto not been systematic and are characterized by a variety of approaches, and some insufficient justification especially in the aspect of state national security is notable. Our contribution to the discourse development is the consideration of energy security as part of internationally recognized indices that are developed to assess the temperature of world security. A regression modeling approach to test the crucial factors of social-economic development that impact the energy security indicators is presented. The literature analysis and review of the world’s existing national security indices show that the link between energy security and national security is in fact hardly considered. Mostly, energy security is considered in the dichotomy concerning economic security at the international, as well as national levels. The calculative regression modeling revealed that the significant correlation of economic and energy security is just for the U.S.A., the rest of the analyzed countires display the weak or non-significant correlations of the indices of economic/energy/security threats. That pushes the discussion on whether energy security is indeed so impactful a factor for geo-policy and geo-economy, or whether it is mostly the well-rolled media-supported megatrend. However, the present study notes a great shortage of long-term cross-state indices to reflect energy, economic, and national security to allow for valuable modeling. Full article
(This article belongs to the Special Issue Policy and Economic Analysis of Sustainable Energy Transition and Mobility)
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<p>Energy consumption per capita (kWh) in China (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 2
<p>The energy consumption resource distribution in China in 2020 (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 3
<p>The energy consumption resource distribution in Ukraine in 2020 (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 4
<p>Energy consumption per capita (kWh) in Ukraine (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 5
<p>The energy consumption resource distribution in Norway in 2020 (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 6
<p>Energy consumption per capita (kWh) in Norway (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 7
<p>The energy consumption resource distribution in the U.S.A. in 2020 (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 8
<p>Energy consumption per capita (kWh) in the U.S.A. (according to the data source [<a href="#B14-energies-15-00658" class="html-bibr">14</a>]).</p> Full article ">Figure 9
<p>External interventions index (according to the data [<a href="#B18-energies-15-00658" class="html-bibr">18</a>]).</p> Full article ">Figure 10
<p>Index of economic security for Ukraine.</p> Full article ">Figure 11
<p>Comparative dynamics of economic security indices of Ukraine, Germany, France, and Poland during 1991–2020.</p> Full article ">Figure 12
<p>Dynamics of structural components of the economic security of Ukraine.</p> Full article ">Figure 13
<p>Correlation matrix: between factors (Python representation).</p> Full article ">Figure 14
<p>Correlation matrix: impact of factors on the dependent indicator.</p> Full article ">Figure 15
<p>Eviews linear regression assessment output.</p> Full article ">Figure 16
<p>Dynamics of the structural components of the index of economic security in Germany: blue line–social security index, orange–industrial and service security index, grey–financial and macroeconomic security index, yellow–resource index, and black–economic security index.</p> Full article ">Figure 17
<p>Dynamics of the structural components of the index of economic security for the U.S.A.: blue line–social security index, orange–industrial and service security index, grey–financial and macroeconomic security index, yellow–resource index, and black–economic security index.</p> Full article ">Figure 18
<p>Dynamics of the structural components of the index of economic security in China: blue line–social security index, orange–industrial and service security index, grey–financial and macroeconomic security index, yellow–resource index, and black–economic security index.</p> Full article ">Figure A1
<p>Eviews regression result (Ukraine case).</p> Full article ">Figure A2
<p>Forecasting according to the regression model for Ukraine.</p> Full article ">
39 pages, 10884 KiB  
Article
Different Fuzzy Control Configurations Tuned by the Bees Algorithm for LFC of Two-Area Power System
by Mokhtar Shouran, Fatih Anayi, Michael Packianather and Monier Habil
Energies 2022, 15(2), 657; https://doi.org/10.3390/en15020657 - 17 Jan 2022
Cited by 13 | Viewed by 2313
Abstract
This study develops and implements a design of the Fuzzy Proportional Integral Derivative with filtered derivative mode (Fuzzy PIDF) for Load Frequency Control (LFC) of a two-area interconnected power system. To attain the optimal values of the proposed structure’s parameters which guarantee the [...] Read more.
This study develops and implements a design of the Fuzzy Proportional Integral Derivative with filtered derivative mode (Fuzzy PIDF) for Load Frequency Control (LFC) of a two-area interconnected power system. To attain the optimal values of the proposed structure’s parameters which guarantee the best possible performance, the Bees Algorithm (BA) and other optimisation tools are used to accomplish this task. A Step Load Perturbation (SLP) of 0.2 pu is applied in area one to examine the dynamic performance of the system with the proposed controller employed as the LFC system. The supremacy of Fuzzy PIDF is proven by comparing the results with those of previous studies for the same power system. As the designed controller is required to provide reliable performance, this study is further extended to propose three different fuzzy control configurations that offer higher reliability, namely Fuzzy Cascade PI − PD, Fuzzy PI plus Fuzzy PD, and Fuzzy (PI + PD), optimized by the BA for the LFC for the same dual-area power system. Moreover, an extensive examination of the robustness of these structures towards the parametric uncertainties of the investigated power system, considering thirteen cases, is carried out. The simulation results indicate that the contribution of the BA tuned the proposed fuzzy control structures in alleviating the overshoot, undershoot, and the settling time of the frequency in both areas and the tie-line power oscillations. Based on the obtained results, it is revealed that the lowest drop of the frequency in area one is −0.0414 Hz, which is achieved by the proposed Fuzzy PIDF tuned by the BA. It is also divulged that the proposed techniques, as was evidenced by their performance, offer a good transient response, a considerable capability for disturbance rejection, and an insensitivity towards the parametric uncertainty of the controlled system. Full article
(This article belongs to the Special Issue Powering Net Zero Emissions—Selected Papers from 56th International Universities Power Engineering Conference (UPEC 2021))
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<p>Transfer function model of the testbed system.</p> Full article ">Figure 2
<p>Structural diagram of Fuzzy PIDF controller of area 1.</p> Full article ">Figure 3
<p>Membership functions of the two inputs and output.</p> Full article ">Figure 4
<p>The Bees Algorithm flowchart.</p> Full article ">Figure 5
<p>Frequency variation in area one (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">F</mi> <mn>1</mn> </msub> </mrow> </semantics></math> in Hz).</p> Full article ">Figure 6
<p>Frequency variation in area two (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">F</mi> <mn>2</mn> </msub> </mrow> </semantics></math> in Hz).</p> Full article ">Figure 7
<p>Tie-line power variation (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">P</mi> <mrow> <mi>tie</mi> </mrow> </msub> </mrow> </semantics></math> in pu).</p> Full article ">Figure 8
<p>Percentage of improvement with different techniques.</p> Full article ">Figure 9
<p>Frequency deviation in area one (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">F</mi> <mn>1</mn> </msub> </mrow> </semantics></math> in Hz) under parametric uncertainties of the testbed system.</p> Full article ">Figure 10
<p>Frequency deviation in area two (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">F</mi> <mn>2</mn> </msub> </mrow> </semantics></math> in Hz) under parametric uncertainties of the testbed system.</p> Full article ">Figure 11
<p>Tie-line power deviation (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">P</mi> <mrow> <mi>tie</mi> </mrow> </msub> </mrow> </semantics></math> in pu) under parametric uncertainties of the testbed system.</p> Full article ">Figure 12
<p>Random load profile.</p> Full article ">Figure 13
<p>Frequency deviation in area one: (<b>A</b>) based on BA tuning and (<b>B</b>) based on TLBO and PSO tuning.</p> Full article ">Figure 14
<p>Frequency deviation in area two: (<b>A</b>) based on BA tuning and (<b>B</b>) based on TLBO and PSO tuning.</p> Full article ">Figure 15
<p>Tie-line power deviation (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">P</mi> <mrow> <mi>tie</mi> </mrow> </msub> </mrow> </semantics></math> in pu): (<b>A</b>) based on BA tuning and (<b>B</b>) based on TLBO and PSO tuning.</p> Full article ">Figure 16
<p>Block diagram of Fuzzy Cascade PI − PD controller configuration equipped in area one.</p> Full article ">Figure 17
<p>Block diagram of Fuzzy PI plus Fuzzy PD controller configuration equipped in area one.</p> Full article ">Figure 18
<p>Block diagram of Fuzzy (PI + PD) controller configuration equipped in area one.</p> Full article ">Figure 19
<p>Frequency deviation in area one (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">F</mi> <mn>1</mn> </msub> </mrow> </semantics></math> in Hz).</p> Full article ">Figure 20
<p>Frequency deviation in area two (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">F</mi> <mn>2</mn> </msub> </mrow> </semantics></math> in Hz).</p> Full article ">Figure 21
<p>Tie-line power deviation (<math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="normal">P</mi> <mrow> <mi>tie</mi> </mrow> </msub> </mrow> </semantics></math> in pu).</p> Full article ">Figure 22
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 1. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 23
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 2. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 24
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 3. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 25
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 4. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 26
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 5. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 27
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 6. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 28
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 7. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 29
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 8. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 30
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 9. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 31
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 10. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 32
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 11. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 33
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 12. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">Figure 34
<p>Dynamic response of the testbed power system based on different fuzzy controllers under parametric uncertainty conditions, case 13. (<b>A</b>) Frequency variation in area 1; (<b>B</b>) frequency variation in area 2; (<b>C</b>) tie-line power variation.</p> Full article ">
35 pages, 5213 KiB  
Article
Prediction of Oil Recovery Factor in Stratified Reservoirs after Immiscible Water-Alternating Gas Injection Based on PSO-, GSA-, GWO-, and GA-LSSVM
by Pål Østebø Andersen, Jan Inge Nygård and Aizhan Kengessova
Energies 2022, 15(2), 656; https://doi.org/10.3390/en15020656 - 17 Jan 2022
Cited by 7 | Viewed by 1929
Abstract
In this study, we solve the challenge of predicting oil recovery factor (RF) in layered heterogeneous reservoirs after 1.5 pore volumes of water-, gas- or water-alternating-gas (WAG) injection. A dataset of ~2500 reservoir simulations is analyzed based on a Black Oil [...] Read more.
In this study, we solve the challenge of predicting oil recovery factor (RF) in layered heterogeneous reservoirs after 1.5 pore volumes of water-, gas- or water-alternating-gas (WAG) injection. A dataset of ~2500 reservoir simulations is analyzed based on a Black Oil 2D Model with different combinations of reservoir heterogeneity, WAG hysteresis, gravity influence, mobility ratios and WAG ratios. In the first model MOD1, RF is correlated with one input (an effective WAG mobility ratio M*). Good correlation (Pearson coefficient −0.94), but with scatter, motivated a second model MOD2 using eight input parameters: water–oil and gas–oil mobility ratios, water–oil and gas–oil gravity numbers, a reservoir heterogeneity factor, two hysteresis parameters and water fraction. The two mobility ratios exhibited the strongest correlation with RF (Pearson coefficient −0.57 for gas-oil and −0.48 for water-oil). LSSVM was applied in MOD2 and trained using different optimizers: PSO, GA, GWO and GSA. A physics-based adaptation of the dataset was proposed to properly handle the single-phase injection. A total of 70% of the data was used for training, 15% for validation and 15% for testing. GWO and PSO optimized the model equally well (R2 = 0.9965 on the validation set), slightly better than GA and GSA (R2 = 0.9963). The performance metrics for MOD1 in the total dataset were: RMSE = 0.050 and R2 = 0.889; MOD2: RMSE = 0.0080 and R2 = 0.998. WAG outperformed single-phase injection, in some cases with 0.3 units higher RF. The benefits of WAG increased with stronger hysteresis. The LSSVM model could be trained to be less dependent on hysteresis and the non-injected phase during single-phase injection. Full article
(This article belongs to the Special Issue Management of High Water Cut and Mature Petroleum Reservoirs)
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<p>The geometrical configuration of the model (modified from [<a href="#B47-energies-15-00656" class="html-bibr">47</a>]). is the distance from the injector, while is the distance from the top of the reservoir.</p> Full article ">Figure 2
<p>Workflow demonstrating the development, assessment and application of the models.</p> Full article ">Figure 3
<p>Datapoints plotted against corresponding values of <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>0</mn> </msub> </mrow> </semantics></math> for MOD1, defined using a third-order polynomial (blue line) of <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>0</mn> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Comparison of estimated <math display="inline"><semantics> <mrow> <mi>RF</mi> </mrow> </semantics></math> with MOD1 and actual datapoints (<b>a</b>) and a histogram of the residuals (<b>b</b>).</p> Full article ">Figure 5
<p>Illustration of optimizer performance in terms of the best solution’s <span class="html-italic">R</span><sup>2</sup> (<b>a</b>), RMSE (<b>b</b>) and search parameter values <math display="inline"><semantics> <mrow> <mi>l</mi> <mi>o</mi> <mi>g</mi> <mrow> <mo>(</mo> <mi>γ</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (<b>c</b>) and <math display="inline"><semantics> <mrow> <mi>l</mi> <mi>o</mi> <mi>g</mi> <mrow> <mo>(</mo> <mi>σ</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (<b>d</b>), at a given iteration. In total, 20 solutions were initiated and run for 30 iterations in each case. Two identical initializations (marked 1 and 2) were run for each algorithm.</p> Full article ">Figure 6
<p>Comparison of estimated <math display="inline"><semantics> <mrow> <mi>RF</mi> </mrow> </semantics></math> and actual datapoints on (<b>a</b>) the training set, (<b>b</b>) validation set and (<b>c</b>) test set. Estimated points are based on MOD2 (optimized LSSVM). The orange line represents perfect match.</p> Full article ">Figure 7
<p>Histogram of residual errors (estimated <math display="inline"><semantics> <mrow> <mi>RF</mi> </mrow> </semantics></math> minus actual <math display="inline"><semantics> <mrow> <mi>RF</mi> </mrow> </semantics></math> ) for the total dataset based on MOD2 (optimized LSSVM model).</p> Full article ">Figure 8
<p>Histogram of partial derivatives for the total dataset based on MOD2 (the optimized LSSVM model). Each partial derivative is evaluated numerically with a small or large difference <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mi>x</mi> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>Contour plots of recovery factor RF plotted against <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>r</mi> <mi>w</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>5</mn> </msub> <mo>=</mo> <mi>l</mi> <mi>o</mi> <mi>g</mi> <mrow> <mo>(</mo> <mrow> <msubsup> <mi>M</mi> <mrow> <mi>g</mi> <mi>o</mi> </mrow> <mo>*</mo> </msubsup> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>. The latter represents variation in oil viscosity, which affects all of <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>5</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>6</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>7</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>8</mn> </msub> </mrow> </semantics></math>. The four cases are for low heterogeneity and hysteresis (<b>a</b>), high heterogeneity and low hysteresis (<b>b</b>), low heterogeneity and high hysteresis (<b>c</b>) and high heterogeneity and hysteresis (<b>d</b>). See all input values in <a href="#energies-15-00656-t005" class="html-table">Table 5</a>.</p> Full article ">Figure 10
<p>Contour plots of recovery factor RF plotted against <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>=</mo> <mi>l</mi> <mi>o</mi> <mi>g</mi> <mrow> <mo>(</mo> <mrow> <msub> <mi>F</mi> <mi>H</mi> </msub> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>5</mn> </msub> <mo>=</mo> <mi>l</mi> <mi>o</mi> <mi>g</mi> <mrow> <mo>(</mo> <mrow> <msubsup> <mi>M</mi> <mrow> <mi>g</mi> <mi>o</mi> </mrow> <mo>*</mo> </msubsup> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>. The latter represents variation in oil viscosity, which affects all of <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>5</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>6</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>7</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>8</mn> </msub> </mrow> </semantics></math>. The cases are for WAG injection with <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>w</mi> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math> and either low (<b>a</b>) or high (<b>b</b>) hysteresis. See all input values in <a href="#energies-15-00656-t005" class="html-table">Table 5</a>.</p> Full article ">Figure 11
<p>Contour plot of recovery factor RF plotted against <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>r</mi> <mi>w</mi> </msub> </mrow> </semantics></math> and log gravity number with equal values of <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>7</mn> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>8</mn> </msub> </mrow> </semantics></math>. Low-heterogeneity (<b>a</b>) and high-heterogeneity (<b>b</b>) cases are shown (see all input values in <a href="#energies-15-00656-t006" class="html-table">Table 6</a>).</p> Full article ">Figure 12
<p>Contour plot of recovery factor RF plotted against <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>r</mi> <mi>w</mi> </msub> </mrow> </semantics></math> and log gravity number with equal values of <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>7</mn> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>8</mn> </msub> </mrow> </semantics></math>. Favorable (<b>a</b>) and unfavorable (<b>b</b>) mobility ratio cases are shown (see all input values in <a href="#energies-15-00656-t006" class="html-table">Table 6</a>).</p> Full article ">Figure 13
<p>Contour plot of recovery factor RF plotted against <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>r</mi> <mi>w</mi> </msub> </mrow> </semantics></math> and log gravity number with equal values of <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>7</mn> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>8</mn> </msub> </mrow> </semantics></math>. Low- (<b>a</b>) and high- (<b>b</b>) hysteresis cases are presented (see all input values in <a href="#energies-15-00656-t006" class="html-table">Table 6</a>).</p> Full article ">Figure 14
<p>Contour plots of recovery factor RF as function of varying water fraction (horizontal axis) and the indicated parameter (<math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>3</mn> </msub> </mrow> </semantics></math> in (<b>a</b>), <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>4</mn> </msub> </mrow> </semantics></math> in (<b>b</b>), <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>5</mn> </msub> </mrow> </semantics></math> in (<b>c</b>) and <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>6</mn> </msub> </mrow> </semantics></math> in (<b>d</b>)) on the vertical axis while holding other parameters fixed. <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>w</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> indicates gas injection and <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>w</mi> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> water injection.</p> Full article ">Figure 15
<p>Illustration of the 3D model, where permeability and well placements are indicated.</p> Full article ">Figure 16
<p>RF after 1.5 PV calculated for different injected WAG fractions (<span class="html-italic">r<sub>w</sub></span>), low or high oil viscosity and low or high degree of hysteresis, calculated based on a 3D Eclipse model (<b>a</b>), MOD1 (<b>b</b>) or MOD2 (<b>c</b>).</p> Full article ">
12 pages, 3221 KiB  
Article
Effects of Cofiring Coal and Biomass Fuel on the Pulverized Coal Injection Combustion Zone in Blast Furnaces
by Gyeong-Min Kim, Jae Hyung Choi, Chung-Hwan Jeon and Dong-Ha Lim
Energies 2022, 15(2), 655; https://doi.org/10.3390/en15020655 - 17 Jan 2022
Cited by 5 | Viewed by 2251
Abstract
CO2 emissions are a major contributor to global warming. Biomass combustion is one approach to tackling this issue. Biomass is used with coal combustion in thermal power plants or with blast furnaces (BFs) because it is a carbon-neutral fuel; therefore, biomass provides [...] Read more.
CO2 emissions are a major contributor to global warming. Biomass combustion is one approach to tackling this issue. Biomass is used with coal combustion in thermal power plants or with blast furnaces (BFs) because it is a carbon-neutral fuel; therefore, biomass provides the advantage of reduced CO2 emissions. To examine the effect of co-firing on pulverized coal injection (PCI) in BFs, two coals of different ranks were blended with the biomass in different proportions, and then their combustion behaviors were examined using a laminar flow reactor (LFR). The PCI combustion primarily functions as a source of heat and CO to supply the upper part of the BF. To create a similar PCI combustion environment, the LFR burner forms a diffusion flat flame with an oxygen concentration of 26% with a flame temperature of ~2000–2250 K at a heating rate of 105 K/s. The combustion characteristics, such as the flame structure, burning coal particle temperature, unburned carbon (UBC), and CO and CO2 emissions were measured to evaluate their effect on PCI combustion. With the increase in the biomass blending ratio, the brightness of the volatile cloud significantly increased, and the particle temperature tended to decrease. The fragmentation phenomenon, which was observed for certain coal samples, decreased with the increase in the biomass blending ratio. In particular, with an increase in the biomass blending ratio, the optimum combustion point occurred, caused by the fragmentation of coal and volatile gas combustion of biomass. Full article
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<p>Schematic of an LFR system.</p> Full article ">Figure 2
<p>Schematic of the cross-sectional area of a Henken burner.</p> Full article ">Figure 3
<p>Schematic of the burning particle temperature-measuring system.</p> Full article ">Figure 4
<p>Gas temperature profile at the LFR center line.</p> Full article ">Figure 5
<p>Flame structure of the burning coal particles (O<sub>2</sub> = 26%).</p> Full article ">Figure 6
<p>Particle–temperature distribution along the height above the reactor: (<b>a</b>) Coal A + biomass (0%, 5%, 10%, 15%) and (<b>b</b>) Coal B + biomass (0%, 5%, 10%, 15%).</p> Full article ">Figure 7
<p>CO/CO<sub>2</sub> emission gas concentration distribution along the height above the reactor: (<b>a</b>) Coal A + biomass (0%, 5%, 10%, 15%) and (<b>b</b>) Coal B + biomass (0%, 5%, 10%, 15%).</p> Full article ">Figure 8
<p>Unburned carbon ratio and the ratio of coal to biomass in unburned carbon (<b>a</b>) Coal A + biomass (0%, 5%, 10%, 15%) and (<b>b</b>) Coal B + biomass (0%, 5%, 10%, 15%) (The proportions of the coal–biomass shown in the plot were rescaled to show the tendency).</p> Full article ">
29 pages, 46865 KiB  
Article
Study on Behavioral Decision Making by Power Generation Companies Regarding Energy Transitions under Uncertainty
by Ryosuke Gotoh, Tetsuo Tezuka and Benjamin C. McLellan
Energies 2022, 15(2), 654; https://doi.org/10.3390/en15020654 - 17 Jan 2022
Cited by 2 | Viewed by 2072
Abstract
With respect to decision making by companies, normative approaches such as the net present value (NPV) method are widely applied, even though it is known that investors may make non-normative decisions. This study aimed to obtain new information on the decision-making behavior of [...] Read more.
With respect to decision making by companies, normative approaches such as the net present value (NPV) method are widely applied, even though it is known that investors may make non-normative decisions. This study aimed to obtain new information on the decision-making behavior of renewable energy (RE) companies under uncertainty in the energy market, which is not provided by the conventional normative approach. In this study, we designed a novel framework that expressed both normative and non-normative perspectives of decision making, and developed a behavioral decision-making model of a power generation company investing in large-scale RE (RE company). We also examined the decisions of the RE company under uncertainty in the energy market using the developed model, considering the Kansai region in Japan as an example study area. As a result, compared to the conventional NPV method, we obtained the following information: (i) heavy investments in either photovoltaics (PV) or wind resulted in decreased variable renewable energy (VRE) capacity, even though financial support was sufficient; (ii) balanced investments in both PV and wind yielded a larger VRE capacity in cases where financial support was sufficient; and (iii) co-worker’s suggestions that lowered the decision-makers’ reference point (RFP) encouraged VRE investments despite insufficient financial support. Full article
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<p>Framework of decisions of RE companies based on normative and non-normative perspectives.</p> Full article ">Figure 2
<p>Overview of the developed model based on the designed framework: (<b>a</b>) companies in the energy market and (<b>b</b>) application of the framework to the decision-making process Company 2.</p> Full article ">Figure 3
<p>Calculation steps of the developed behavioral decision model of Company 2.</p> Full article ">Figure 4
<p>Calculation process of the VRE investment value in STEP IV: (1)–(6) correspond to the numbers in the description of STEP VI. The black dots in the graphs are examples.</p> Full article ">Figure 5
<p>National power grid in Japan and the Kansai region (Based on [<a href="#B43-energies-15-00654" class="html-bibr">43</a>]).</p> Full article ">Figure 6
<p>National power grid in the Kansai region of Japan.</p> Full article ">Figure 7
<p>Concept of selected reference points for the decision making of the top management.</p> Full article ">Figure 8
<p>Results of different FIP prices (Low, Middle, and High FIP): (<b>a</b>) Expected NPV with standard deviation, (<b>b</b>) Value in the case of high RFP, (<b>c</b>) Value in case of low RFP and (<b>d</b>) Spot price. The horizontal dashed lines show the zero axis in the Value graphs.</p> Full article ">Figure 9
<p>Results of different strategies of Company 1 with low FIP: (<b>a</b>) Expected NPV with standard deviation, (<b>b</b>) Value in case of high RFP, (<b>c</b>) Value in case of low RFP, (<b>d</b>) Spot price, and (<b>e</b>) CO<sub>2</sub> emissions.</p> Full article ">Figure 10
<p>Results of the mixture of VRE: (<b>a</b>) Expected NPV with standard deviation, (<b>b</b>) Value in case of high RFP, (<b>c</b>) Value in case of low RFP, (<b>d</b>) Standard deviation of NPV, and (<b>e</b>) CVaR of NPV.</p> Full article ">Figure 11
<p>Results of option to expand in case of low FIP: (<b>a</b>) Expected NPV with standard deviation, (<b>b</b>) Value in case of high RFP and (<b>c</b>) Value in case of low RFP.</p> Full article ">Figure 12
<p>Results of option to expand in case of high FIP: (<b>a</b>) Expected NPV with standard deviation, (<b>b</b>) Value in case of high RFP and (<b>c</b>) Value in case of low RFP.</p> Full article ">Figure A1
<p>The Value Function (based on [<a href="#B30-energies-15-00654" class="html-bibr">30</a>]).</p> Full article ">Figure A2
<p>The Weighting Function (based on [<a href="#B30-energies-15-00654" class="html-bibr">30</a>]).</p> Full article ">
12 pages, 938 KiB  
Article
Experimental Lognormal Modeling of Harmonics Power of Switched-Mode Power Supplies
by Dima Bykhovsky
Energies 2022, 15(2), 653; https://doi.org/10.3390/en15020653 - 17 Jan 2022
Cited by 4 | Viewed by 1560
Abstract
Switched-mode power supplies (SMPSs) are an important component in many electrical systems. As a highly non-linear device, an unavoidable side-effect of SMPS operation is its high harmonics power. One of the ways to model the harmonic power consumption profile is in terms of [...] Read more.
Switched-mode power supplies (SMPSs) are an important component in many electrical systems. As a highly non-linear device, an unavoidable side-effect of SMPS operation is its high harmonics power. One of the ways to model the harmonic power consumption profile is in terms of a random process. This paper addresses random process modeling with a corresponding probability density function (PDF), auto-covariance function (ACF) and spectral coherence. The consumed harmonics power was evaluated under different load conditions and is based on experimental results of current consumption from SMPSs. The analysis shows that harmonics power may be modeled by a lognormal distribution that is time-domain uncorrelated, and that has spectral-domain correlation modeled by a Gaussian radial basis function. Extensive discussion on the modeling results is also provided. Moreover, random simulation approach based on the modeling results was proposed. Full article
(This article belongs to the Special Issue New Challenges in Harmonics and Power Quality Research)
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<p>Illustration of a random SMPS current for a constant load.</p> Full article ">Figure 2
<p>The analysis of a harmonics signal is based on the spectrogram concept, with power <math display="inline"><semantics> <msub> <mi>p</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>l</mi> </mrow> </msub> </semantics></math> of <span class="html-italic">l</span>-th frame and <span class="html-italic">m</span>-th harmonic: (<b>a</b>) harmonics value for each time-frame; (<b>b</b>) statistics of <span class="html-italic">m</span>-th harmonic for all frames; (<b>c</b>) inter-harmonics relation; (<b>d</b>) intra-harmonics relation.</p> Full article ">Figure 3
<p>Schematic presentation of the experimental setup.</p> Full article ">Figure 4
<p>An example of the fluctuations of harmonics power (Equation (<a href="#FD4-energies-15-00653" class="html-disp-formula">4</a>)) at 800 mA load modeled by a lognormal distribution; the distribution is in dB units fitted with the Gaussian PDF for (<b>a</b>) 750 Hz harmonic and (<b>b</b>) 850Hz harmonic.</p> Full article ">Figure 5
<p>Histogram fits of lognormal distribution for different harmonics and different DC load levels.</p> Full article ">Figure 6
<p>Lognormal distribution parameters as a function of frequency for different load levels: (<b>a</b>) <math display="inline"><semantics> <msub> <mi>μ</mi> <mrow> <mi>d</mi> <mi>B</mi> </mrow> </msub> </semantics></math> and (<b>b</b>) <math display="inline"><semantics> <msub> <mi>σ</mi> <mrow> <mi>d</mi> <mi>B</mi> </mrow> </msub> </semantics></math>.</p> Full article ">Figure 7
<p>Box-plot of the levels of the different harmonics power as a function of DC load current.</p> Full article ">Figure 8
<p>ACF of harmonics power for different frequencies.</p> Full article ">Figure 9
<p>Correlation of harmonics coefficients. (<b>a</b>) Covariance matrix visualization. (<b>b</b>) Selected harmonics with Gaussian radial function fit.</p> Full article ">Figure 10
<p>An example of the reconstructed signal <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">y</mi> <mo>^</mo> </mover> </semantics></math> compared to the original signal.</p> Full article ">Figure 11
<p>Even harmonics at high load sometimes cannot be lognormal modeled. An example of 900 mA load: (<b>a</b>) 100 Hz harmonic; (<b>b</b>)150 Hz harmonic.</p> Full article ">
23 pages, 2107 KiB  
Article
Standing Wave Pattern and Distribution of Currents in Resonator Arrays for Wireless Power Transfer
by Mattia Simonazzi, Ugo Reggiani and Leonardo Sandrolini
Energies 2022, 15(2), 652; https://doi.org/10.3390/en15020652 - 17 Jan 2022
Cited by 9 | Viewed by 1978
Abstract
The possibility of increasing the transmission efficiency in mid-range wireless power transfer (WPT) applications can be achieved by inserting resonant relay coils between the transmitting and receiving sides of the device, forming an array of magnetically coupled resonant circuits, over which a receiver [...] Read more.
The possibility of increasing the transmission efficiency in mid-range wireless power transfer (WPT) applications can be achieved by inserting resonant relay coils between the transmitting and receiving sides of the device, forming an array of magnetically coupled resonant circuits, over which a receiver can be placed. This is a very cheap solution for improving the performance of the WPT apparatus, even if the complexity of the system increases, requiring a complete and detailed investigation for a smart design and control of the apparatus. The presented study investigates the current distribution in the coils of the array, which revealed strong peaks in magnitude depending on the load and receiver position. The analysis is carried out with the transmission line (TL) theory and it is performed for different positions of the receiver, as well as for different load conditions. Furthermore, a real application is considered and discussed, which includes the presence of a power converter as power supply and a battery charging system as load. Each resonant circuit resonates at 150 kHz and the whole apparatus is capable to transmit power up to 1 kW with an efficiency around 70%. The theoretical results have been validated with experimental measurements. Full article
(This article belongs to the Special Issue Intelligent Wireless Power Transfer System and Its Application 2021)
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<p>Array of R-L-C resonators as inductive coupling device of a battery charger.</p> Full article ">Figure 2
<p>Equivalent circuits of a resonator array (<b>a</b>) circuit fed by a half-bridge inverter and connected to a load and (<b>b</b>) approximate circuit for the first harmonic.</p> Full article ">Figure 3
<p>Equivalent representation of a resonator array by a cascade connection of two-port networks.</p> Full article ">Figure 4
<p>Current standing wave patterns for different termination loads.</p> Full article ">Figure 5
<p>Standing wave ratio for arrays of different length and different termination conditions.</p> Full article ">Figure 6
<p>Resonator array with a receiver.</p> Full article ">Figure 7
<p>Equivalent circuit of a resonator array with a receiver.</p> Full article ">Figure 8
<p>Mutual inductance between the receiver and three consecutive resonators of the array, as a function of the receiver position at a receiver height of 10 mm.</p> Full article ">Figure 9
<p>Section of the equivalent TL of a resonator array with a receiver coupled with the <span class="html-italic">i</span>th resonator.</p> Full article ">Figure 10
<p>Section of the equivalent TL of a resonator array with a receiver coupled with the <span class="html-italic">i</span>th and <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </semantics></math>th resonators.</p> Full article ">Figure 11
<p>Current magnitude of each resonator as a function of the receiver position, for a matched array and different load resistances.</p> Full article ">Figure 12
<p>Standing wave patterns for different positions of the perfectly aligned receiver, a matched array and different load resistances.</p> Full article ">Figure 13
<p>Transmission efficiency in the cases of S.C., O.C. and matched terminations for <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mi>l</mi> </msub> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">Figure 14
<p>Magnitude of the currents of the array resonators as a function of the receiver position, for different terminations and a receiver load <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">Figure 15
<p>Standing wave patterns for different positions of the receiver, different terminations and a receiver load <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">Figure 16
<p>Magnitude of the currents of the array resonators as a function of the receiver position, for different terminations and a receiver load <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">Figure 17
<p>Standing wave patterns for different positions of the receiver, different terminations and a receiver load <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">Figure 18
<p>Magnitude of the currents of the array resonators as a function of the receiver position, for different terminations and a receiver load <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">Figure 19
<p>Standing wave patterns for different positions of the receiver, different terminations and a receiver load <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">Figure 20
<p>Experimental setup.</p> Full article ">Figure 21
<p>Comparison between the numerical and experimental values of the resonator current magnitude for different receiver positions in the case of <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mi>T</mi> </msub> <mo>=</mo> <mn>1.5</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>Z</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math><math display="inline"><semantics> <mo>Ω</mo> </semantics></math>.</p> Full article ">
8 pages, 1264 KiB  
Article
The Comparison of Microwave Reflectance of Graphite and Reduced Graphene Oxide Used for Electronic Devices Protection
by Roman Kubacki, Ludwika Lipińska, Rafał Przesmycki and Dariusz Laskowski
Energies 2022, 15(2), 651; https://doi.org/10.3390/en15020651 - 17 Jan 2022
Cited by 2 | Viewed by 2133
Abstract
This work presents the investigation of graphite and reduced graphene oxide (RGO) reflectance as an important parameter for electronic devices’ protection. These materials should protect electronic circuits against external as well as internal reflected radiation. The investigation was focused on comparing the reflectance [...] Read more.
This work presents the investigation of graphite and reduced graphene oxide (RGO) reflectance as an important parameter for electronic devices’ protection. These materials should protect electronic circuits against external as well as internal reflected radiation. The investigation was focused on comparing the reflectance of both materials on the metal layers. The measurements of constant electromagnetic parameters, such as permittivity and permeability, were carried out on pure materials without any additives, such as polystyrene foam, resin, wax, etc. The measurements were implemented in a coaxial line within the microwave frequency range from 100 MHz to 10 GHz. The measurements show a high value of reflected power, over 90% for graphite while RGO reflects only 80% of incident power. In addition, due to the half-wavelength effect in reduced graphene oxide, the reflection coefficient is reduced to 70%. Full article
(This article belongs to the Special Issue Engineering and Medical Aspects of the Use of Electromagnetic Field Energy 2021)
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<p>Schematic presentation of incident (E), transmitted (E<sub>T</sub>) and reflected field (E<sub>R</sub>): (<b>a</b>) electronic circuit inside metallic or metallic-like enclosure, (<b>b</b>) enclosure equipped with an absorber.</p> Full article ">Figure 2
<p>Configuration of material sample in the coaxial holder.</p> Full article ">Figure 3
<p>(<b>a</b>,<b>b</b>) permittivity of graphite (blue, dashed lines) and reduced graphene oxide (red, solid lines); (<b>c</b>,<b>d</b>) permeability of graphite (blue, dashed lines) and reduced graphene oxide (red, solid lines).</p> Full article ">Figure 4
<p>Schematic presentation of reflected rays from material backed with metal.</p> Full article ">Figure 5
<p>Reflection coefficients of power density of the absorber backed with the metal layer with thickness: (<b>a</b>) 2 mm, (<b>b</b>) 5 mm; graphite—blue, dotted line; RGO—red, solid.</p> Full article ">
20 pages, 2698 KiB  
Article
Designing the Business Ecosystem of a Decentralised Energy Datahub
by Sinan Küfeoğlu, Eray Açıkgöz, Yunus Emre Taşcı, Taha Yasin Arslan, Jan Priesmann and Aaron Praktiknjo
Energies 2022, 15(2), 650; https://doi.org/10.3390/en15020650 - 17 Jan 2022
Cited by 5 | Viewed by 3020
Abstract
Datahubs step forth as convenient test beds for innovative solutions to create value from the energy data. There are numerous pilots and early trials for establishing energy Datahubs, especially in northern Europe. These are all centralised models, and the centralisation of data control [...] Read more.
Datahubs step forth as convenient test beds for innovative solutions to create value from the energy data. There are numerous pilots and early trials for establishing energy Datahubs, especially in northern Europe. These are all centralised models, and the centralisation of data control and value creation can be regarded as contradictory to the decentralisation trend in the energy sector. This paper attempts to design the first decentralised energy Datahub ecosystem’s business ecosystem, with the name DenHub, using Blockchain technology. This model enables easy access to transparent and flexible energy data and new business models that will emerge upon its use. All data produced, distributed, used, and curated will help researchers and entrepreneurs study this field and propose new business models to make the energy ecosystem more efficient, clean, and inclusive. The paper also presents the differences between centralised and decentralised methods by underlining the advantages and disadvantages of both approaches. Full article
(This article belongs to the Special Issue State-of-the-Art Energy Related Technologies and New Business Models in UK)
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<p>Blockchain-based Energy Datahub (DenHub) Ecosystem Participants.</p> Full article ">Figure 2
<p>Centralised Energy Datahub Ecosystem Participants [<a href="#B3-energies-15-00650" class="html-bibr">3</a>].</p> Full article ">Figure 3
<p>Data Flow Chart on Smart Metering Infrastructure.</p> Full article ">Figure 4
<p>Incentive Structure of the Blockchain.</p> Full article ">Figure 5
<p>Blockchain Types.</p> Full article ">Figure 6
<p>The DenHub Hybrid Blockchain Model.</p> Full article ">
18 pages, 3552 KiB  
Review
Performance-Based Analysis in Evaluation of Safety in Car Parks under Electric Vehicle Fire Conditions
by Dorota Brzezinska and Paul Bryant
Energies 2022, 15(2), 649; https://doi.org/10.3390/en15020649 - 17 Jan 2022
Cited by 28 | Viewed by 8005
Abstract
Even though electric vehicles (EV) were invented over a century ago, their popularity has grown significantly within the last 10 years due to the development of Li-ion battery technology. This evolution created an increase in the fire risk and hazards associated with this [...] Read more.
Even though electric vehicles (EV) were invented over a century ago, their popularity has grown significantly within the last 10 years due to the development of Li-ion battery technology. This evolution created an increase in the fire risk and hazards associated with this type of high-energy battery. This review focuses on lessons learned from electric vehicle fires and fire risk mitigation measures for passenger road vehicles partially or fully powered by Li-ion batteries. The paper presents EV fire risks, as well as historical car fires, published large-scale fire tests, and some proposed fire protection strategies in the aspect of electromobility safety for the future. Technical solutions for EV fire hazard mitigation are discussed, and methods of performance-based analysis and simulations for fire safety in car park evaluation are demonstrated. The Fire Dynamic Simulator (FDS) was used for the CFD simulations for the prediction of smoke dispersion and temperature distribution during an EV fire. The presented case study demonstrates how fire simulations could predict conditions for the safe evacuation of people and Fire Brigade intervention conditions in the case of an EV fire in a car park. Full article
(This article belongs to the Special Issue Performance Analysis and Simulation of Electric Vehicles)
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<p>Global electric car sales and market share from 2013 to 2018 (BEVs = battery electric vehicles; PHEVs = plug-in hybrid electric vehicles) [<a href="#B23-energies-15-00649" class="html-bibr">23</a>].</p> Full article ">Figure 2
<p>Global future trends of EV popularization for road EVs [<a href="#B23-energies-15-00649" class="html-bibr">23</a>].</p> Full article ">Figure 3
<p>Realized analysis steps.</p> Full article ">Figure 4
<p>HRR curve of the fire.</p> Full article ">Figure 5
<p>Scheme of the car park.</p> Full article ">Figure 6
<p>Detection activation—starting fire alarm.</p> Full article ">Figure 7
<p>Graphical presentation of the CFD simulation results.</p> Full article ">
23 pages, 18069 KiB  
Article
A Thermohydraulic Performance of Internal Spiral Finned Tube Based on the Inner Tube Secondary Flow
by Yicong Li, Zuoqin Qian and Qiang Wang
Energies 2022, 15(2), 648; https://doi.org/10.3390/en15020648 - 17 Jan 2022
Cited by 2 | Viewed by 1698
Abstract
In this article, the BSL k-ω model was chosen as the turbulence model to simulate the heat transfer and flow characteristics of the proposed tubes inserted with internal spiral fins when the Re was set as 3000 to 17,000. The numerical results agreed [...] Read more.
In this article, the BSL k-ω model was chosen as the turbulence model to simulate the heat transfer and flow characteristics of the proposed tubes inserted with internal spiral fins when the Re was set as 3000 to 17,000. The numerical results agreed well with the empirical formula. The average deviations of Nu and f between the simulation results and empirical formula results were 5.11% and 8.45%, respectively. By means of numerical simulation, the impact of three configurational parameters on the thermal performance was studied, namely the pitch P, the height H, and the number N of the internal spiral fins. The results showed that the Nu and f of the internal spiral finned tube were 1.77–3.74 and 3.04–10.62 times higher than those of smooth tube, respectively. PEC was also taken into account, ranging from 1.038 to 1.652. When the Re was set as 3000, the PEC achieved the peak value of 1.652 under the height H of the fins at 5 mm, the number N was 8, and the pitch P was 75 mm. However, with the increase of Re, the effect of pressure drop on the comprehensive performance in the tube was stronger than that of thermal enhancement. However, the PEC gradually decreased as the Re increased from 3000 to 17,000. In addition, the velocity and temperature fields were obtained to investigate the mechanisms of heat transfer enhancement. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Detailed view of the internal spiral finned tube.</p> Full article ">Figure 2
<p>Comparisons between numerical data and correlation data: (<b>a</b>) comparisons of <span class="html-italic">Nu</span>; (<b>b</b>) comparisons of <span class="html-italic">f</span>.</p> Full article ">Figure 2 Cont.
<p>Comparisons between numerical data and correlation data: (<b>a</b>) comparisons of <span class="html-italic">Nu</span>; (<b>b</b>) comparisons of <span class="html-italic">f</span>.</p> Full article ">Figure 3
<p>Boundary conditions.</p> Full article ">Figure 4
<p>Grids generated for computation domain.</p> Full article ">Figure 5
<p>Verification between numerical result and correlation data.</p> Full article ">Figure 6
<p>The velocity, temperature and streamlines distributions of five intercepted sections.</p> Full article ">Figure 7
<p>The velocity distribution of the ordinary circular tube.</p> Full article ">Figure 8
<p>The temperature distribution of the ordinary circular tube.</p> Full article ">Figure 9
<p>The vorticity distributions of the internal spiral finned tube at Z = 50 mm.</p> Full article ">Figure 10
<p>The <span class="html-italic">Nu</span> of the internal spiral finned tube and plain tube under different <span class="html-italic">H</span>.</p> Full article ">Figure 11
<p>The temperature and velocity distributions of the internal spiral finned tube under different <span class="html-italic">H</span>.</p> Full article ">Figure 12
<p>The <span class="html-italic">f</span> of the internal spiral finned tube and plain tube under different <span class="html-italic">H</span>.</p> Full article ">Figure 13
<p>Comparison of heat transfer and flow resistance between plain tube and internal spiral finned tube in different <span class="html-italic">P</span>. (<b>a</b>) <span class="html-italic">Nu</span>, (<b>b</b>) <span class="html-italic">f</span>.</p> Full article ">Figure 13 Cont.
<p>Comparison of heat transfer and flow resistance between plain tube and internal spiral finned tube in different <span class="html-italic">P</span>. (<b>a</b>) <span class="html-italic">Nu</span>, (<b>b</b>) <span class="html-italic">f</span>.</p> Full article ">Figure 14
<p>The temperature and velocity distributions of the internal spiral finned tube under different <span class="html-italic">P</span>.</p> Full article ">Figure 15
<p>Comparison of heat transfer and flow resistance between plain tube and internal spiral finned tube in different <span class="html-italic">N</span>. (<b>a</b>) <span class="html-italic">Nu</span>, (<b>b</b>) <span class="html-italic">f</span>.</p> Full article ">Figure 15 Cont.
<p>Comparison of heat transfer and flow resistance between plain tube and internal spiral finned tube in different <span class="html-italic">N</span>. (<b>a</b>) <span class="html-italic">Nu</span>, (<b>b</b>) <span class="html-italic">f</span>.</p> Full article ">Figure 16
<p>The temperature and velocity distributions of the internal spiral finned tube under different <span class="html-italic">N</span>.</p> Full article ">Figure 17
<p>Effect of different factors on heat transfer and flow performance: (<b>a</b>) the angle <span class="html-italic">α</span>, (<b>b</b>) the height <span class="html-italic">H</span>, (<b>c</b>) the number <span class="html-italic">N</span>.</p> Full article ">Figure 17 Cont.
<p>Effect of different factors on heat transfer and flow performance: (<b>a</b>) the angle <span class="html-italic">α</span>, (<b>b</b>) the height <span class="html-italic">H</span>, (<b>c</b>) the number <span class="html-italic">N</span>.</p> Full article ">Figure 18
<p>Comparisons with previous work.</p> Full article ">
33 pages, 2320 KiB  
Review
Review of Carnot Battery Technology Commercial Development
by Vaclav Novotny, Vit Basta, Petr Smola and Jan Spale
Energies 2022, 15(2), 647; https://doi.org/10.3390/en15020647 - 17 Jan 2022
Cited by 47 | Viewed by 8588
Abstract
Carnot batteries are a quickly developing group of technologies for medium and long duration electricity storage. It covers a large range of concepts which share processes of a conversion of power to heat, thermal energy storage (i.e., storing thermal exergy) and in times [...] Read more.
Carnot batteries are a quickly developing group of technologies for medium and long duration electricity storage. It covers a large range of concepts which share processes of a conversion of power to heat, thermal energy storage (i.e., storing thermal exergy) and in times of need conversion of the heat back to (electric) power. Even though these systems were already proposed in the 19th century, it is only in the recent years that this field experiences a rapid development, which is associated mostly with the increasing penetration of intermittent cheap renewables in power grids and the requirement of electricity storage in unprecedented capacities. Compared to the more established storage options, such as pumped hydro and electrochemical batteries, the efficiency is generally much lower, but the low cost of thermal energy storage in large scale and long lifespans comparable with thermal power plants make this technology especially feasible for storing surpluses of cheap renewable electricity over typically dozens of hours and up to days. Within the increasingly extensive scientific research of the Carnot Battery technologies, commercial development plays the major role in technology implementation. This review addresses the gap between academia and industry in the mapping of the technologies under commercial development and puts them in the perspective of related scientific works. Technologies ranging from kW to hundreds of MW scale are at various levels of development. Some are still in the stage of concepts, whilst others are in the experimental and pilot operations, up to a few commercial installations. As a comprehensive technology review, this paper addresses the needs of both academics and industry practitioners. Full article
(This article belongs to the Topic Energy Storage and Conversion Systems)
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Graphical abstract
Full article ">Figure 1
<p>Overview of global installed grid scale electricity storage systems power rating in 2020.</p> Full article ">Figure 2
<p>General principle of Carnot battery systems.</p> Full article ">Figure 3
<p>CB concepts regarding thermal integration of heat sources and conversion systems. (<b>a</b>) direct heat to power conversion, (<b>b</b>) reversible thermodynamic cycle, (<b>c</b>) with heat source integration and hot storage or (<b>d</b>) cold storage.</p> Full article ">Figure 4
<p>Bibliographic study on a yearly number of scientific works with main CB keywords.</p> Full article ">Figure 5
<p>Storage power output and capacity (<b>a</b>) and discharge duration (<b>b</b>) for the commercially developed CB systems.</p> Full article ">Figure 6
<p>Overview of round trip efficiency in the commercially CB systems (mostly declared as experimental values are limited). In notation (d) stands for demo, (p) pilot, (c) commercial units (built or under construction), * for systems with additional fuel firing.</p> Full article ">Figure 7
<p>Timeline of experimental commercial CB development. In notation (d) stands for demo or laboratory prototype, (p) pilot, (c) commercial units.</p> Full article ">
28 pages, 13437 KiB  
Article
Towards a Powerful Hardware-in-the-Loop System for Virtual Calibration of an Off-Road Diesel Engine
by Antonio Riccio, Filippo Monzani and Maurizio Landi
Energies 2022, 15(2), 646; https://doi.org/10.3390/en15020646 - 17 Jan 2022
Cited by 10 | Viewed by 2938
Abstract
A common challenge among internal combustion engine (ICE) manufacturers is shortening the development time while facing requirements and specifications that are becoming more complex and border in scope. Virtual simulation and calibration are effective instruments in the face of these demands. This article [...] Read more.
A common challenge among internal combustion engine (ICE) manufacturers is shortening the development time while facing requirements and specifications that are becoming more complex and border in scope. Virtual simulation and calibration are effective instruments in the face of these demands. This article presents the development of zero-dimensional (0D)—real-time engine and exhaust after-treatment system (EAS) models and their deployment on a Virtual test bench (VTB). The models are created using a series of measurements acquired in a real test bench, carefully performed in view of ensuring the highest reliability of the models themselves. A zero-dimensional approach was chosen to guarantee that models could be run in real-time and interfaced to the real engine Electronic Control Unit (ECU). Being physically based models, they react to changes in the ECU calibration parameters. Once the models are validated, they are then integrated into a Simulink® based architecture with all the Inputs/Outputs connections to the ECU. This Simulink® model is then deployed on a Hardware in the Loop (HiL) machine for ECU testing and calibration. The results for engine and EAS performance and emissions align with both steady-state and transient measurements. Finally, two different applications of the HiL system are presented to explain the opportunities and advantages of this tool integrated within the standard engine development. Examples cited refer to altitude calibration activities and soot loading investigation on vehicle duty cycles. The cases described in this work are part of the actual development of one of the latest engines developed by Kohler Engines: the KDI 1903 TCR Stage V. The application of this methodology reveals a great potential for engine development and may become an essential tool for calibration engineers. Full article
(This article belongs to the Special Issue Advanced Calibration Methodologies for a New Generation of Engines and Powertrains)
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<p>Virtualization process to reduce ICE development cost and timing and to go faster to Start of Production (SOP) stage.</p> Full article ">Figure 2
<p>Hardware in the Loop Simulator.</p> Full article ">Figure 3
<p>Kohler KDI 1903 engine: experimental setup layout and engine schematic.</p> Full article ">Figure 4
<p>Engine Model sketch in AVL CRUISE™ M environment.</p> Full article ">Figure 5
<p>Parametrization of the flow coefficient of the intake throttle valve.</p> Full article ">Figure 6
<p>Coolant temperature: model description.</p> Full article ">Figure 7
<p>External emission models for CO, THC and Soot.</p> Full article ">Figure 8
<p>HC Model Structure graphic.</p> Full article ">Figure 9
<p>Exhaust after-treatment system of KDI 1903 TCR engine.</p> Full article ">Figure 10
<p>(<b>a</b>) Simulated (red) vs. experimental (black) NO<sub>x</sub> emission downstream DOC. (<b>b</b>) Simulated (red) vs. experimental (black) HC emission downstream DOC.</p> Full article ">Figure 11
<p>(<b>a</b>) Top: Simulated (red) vs. experimental (black) NO<sub>x</sub> emission downstream DOC. Bottom: Simulated (red) vs. experimental (black) NO emission downstream DOC. (<b>b</b>) Top: Simulated (red) vs experimental (black) HC emission downstream DOC. Bottom: Simulated (red) vs experimental (black) CO emission downstream DOC.</p> Full article ">Figure 12
<p>DPF model overview.</p> Full article ">Figure 13
<p>DPF—NO<sub>2</sub> recycling.</p> Full article ">Figure 14
<p>DPF Combustion rate simulated tests.</p> Full article ">Figure 15
<p>Measured (<span class="html-italic">x</span>-axis) vs. Simulated (<span class="html-italic">y</span>-axis) NO<sub>x</sub> emissions at Engine Out (normalized).</p> Full article ">Figure 16
<p>Measured (<span class="html-italic">x</span>-axis) vs. Simulated (<span class="html-italic">y</span>-axis) Soot emission at Engine Out (normalized).</p> Full article ">Figure 17
<p>Top: Simulated (red) vs. experimental (black) NO<sub>x</sub> Engine Out (normalized). Bottom: Difference between simulated and measured NO<sub>x</sub> Engine out signals (normalized).</p> Full article ">Figure 18
<p>(<b>a</b>) Statistical analysis of NOx Engine Out simulated at VTB to determine the model accuracy over the NRTC; (<b>b</b>) Simulated (red) vs experimental (black) of cumulated NOx engine Out emission normalized with respect reference value.</p> Full article ">Figure 19
<p>Simulated (red) vs. Measured (black) cumulated soot over NRTC Cycle (normalized).</p> Full article ">Figure 20
<p>(<b>a</b>) Turbo speed w/o Altitude Calibration normalized with respect to the maximum value reached in the test; (<b>b</b>) Turbo speed w/ Altitude Calibration normalized with respect to the maximum value reached in the test w/o altitude calibration.</p> Full article ">Figure 21
<p>(<b>a</b>) Turbine inlet temperature w/o Altitude Calibration normalized with respect to the maximum value reached in the test; (<b>b</b>) Turbine inlet temperature w/ Altitude Calibration normalized with respect to the maximum value reached in the test w/o altitude calibration.</p> Full article ">Figure 22
<p>(<b>a</b>) Simulated (red) vs measured (black) Intake throttle valve (top) and EGR valve (bottom) positions (normalized with respect to the maximum value reached in the test); (<b>b</b>) Simulated (red) vs measured (black) fuel injection (normalized with respect to the maximum value reached in the test).</p> Full article ">Figure 23
<p>(<b>a</b>) Simulated (red) vs. measured (black) turbocharger speed (normalized with respect to the maximum value reached in the test); (<b>b</b>) Simulated (red) vs. measured (black) NOx engine out emission (normalized with respect to the maximum value reached in the test).</p> Full article ">Figure 24
<p>(<b>a</b>) Simulated (red) vs. measured (black) intake manifold pressure (normalized with respect to maximum value reached in the test); (<b>b</b>) Simulated (red) vs. measured (black) intake manifold temperature (normalized with respect to maximum value reached in the test).</p> Full article ">Figure 25
<p>(<b>a</b>) Simulated (red) vs measured (black) DOC inlet temperature (normalized with respect to the maximum value reached in the test); (<b>b</b>) Simulated (red) vs measured (black) DPF inlet temperature (normalized with respect to the maximum value reached in the test).</p> Full article ">Figure 26
<p>Top: engine speed (normalized with respect to the maximum value reached in the test) of vehicle duty cycle; Bottom: injected quantity of vehicle duty cycle (normalized with respect to the maximum value reached in the test).</p> Full article ">Figure 27
<p>Exhaust Temperature over the Vehicle Duty Cycle (normalized with respect to the maximum value reached in the test).</p> Full article ">Figure 28
<p>Soot Loading comparison between HiL simulation and real engine test bed (normalized with respect to the maximum value reached in the test).</p> Full article ">
20 pages, 2048 KiB  
Article
Linking the National Energy and Climate Plan with Municipal Spatial Planning and Supporting Sustainable Investment in Renewable Energy Sources in Austria
by Susanne Geissler, Abraham Arevalo-Arizaga, David Radlbauer and Peter Wallisch
Energies 2022, 15(2), 645; https://doi.org/10.3390/en15020645 - 17 Jan 2022
Cited by 15 | Viewed by 2842
Abstract
The Austrian National Energy and Climate Plan (NECP) refers to spatial planning as an important instrument to achieve 2030 targets because the technical potential of renewable energy sources (RES) are closely related to the types of land use. In Austria, land use is [...] Read more.
The Austrian National Energy and Climate Plan (NECP) refers to spatial planning as an important instrument to achieve 2030 targets because the technical potential of renewable energy sources (RES) are closely related to the types of land use. In Austria, land use is regulated by the spatial planning laws of the nine provinces, whereby the municipalities play an important role. It was the objective of the transFORMAT project to understand the scope for action of the municipalities with regard to promoting renewable energy use, and to understand the practical implications for renewable energy projects. To this end, the consolidated versions of spatial planning laws were analyzed and supported by a software tool (transFORMAT-Analyzer) that was developed to facilitate this process and the resulting follow-up activities. Responsible administrative departments were approached for supplementary information when deemed necessary. As a conclusion, the legal instrument (municipal ordinance), called a municipal development plan or concept, represents a long-term plan for the development of the municipality with the obligation or the option for revision under specific conditions. In theory, these revision intervals could be used to better align municipal plans with the NECP. In practice, however, significant barriers exist and opportunities for improvement have been identified, leading to recommendations on how investments in renewable energy systems can be planned more realistically and, thus, more sustainably. Full article
(This article belongs to the Special Issue The Role of Spatial Policy Tools in Renewable Energy Investment)
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<p>Overview of the Austrian legislative framework for spatial planning and the relation with the NECP and the Governance regulation.</p> Full article ">Figure 2
<p>Screenshot of transFORMAT tool, English version. (<a href="https://transformat.sera.global/home" target="_blank">https://transformat.sera.global/home</a>; accessed on 6 July 2021).</p> Full article ">Figure 3
<p>Overview of main components of transFORMAT-A and the relationship between them. (<b>a</b>) One-time retrieval of the transFORMAT-A application without content. (<b>b</b>) Dynamic content updating process. (<b>c</b>) Content change requests.</p> Full article ">
13 pages, 3205 KiB  
Article
Optimization of Operating Conditions of a Solid Oxide Fuel Cell System with Anode Off-Gas Recirculation Using the Model-Based Sensitivity Analysis
by Eun-Jung Choi, Sangseok Yu and Sang-Min Lee
Energies 2022, 15(2), 644; https://doi.org/10.3390/en15020644 - 17 Jan 2022
Cited by 5 | Viewed by 1936
Abstract
Designing a configuration of an efficient solid oxide fuel cell (SOFC) system and operating it under appropriate conditions are important for achieving a highly efficient SOFC system. In our previous research, the system layout of a SOFC system with anode off-gas recirculation was [...] Read more.
Designing a configuration of an efficient solid oxide fuel cell (SOFC) system and operating it under appropriate conditions are important for achieving a highly efficient SOFC system. In our previous research, the system layout of a SOFC system with anode off-gas recirculation was suggested, and the system performance was examined using a numerical model. In the present study, the system operating conditions were optimized based on the system configuration and numerical model developed in the previous paper. First, a parametric sensitivity analysis of the system performance was investigated to demonstrate the main operating parameters. Consequently, the fuel flow rate and recirculation ratio were selected. Then, the available operating conditions, which keep the system below the operating limits and satisfy the desired system performance (Ufuel > 0.7 and ηelec > 45%) were discovered. Finally, optimized operating conditions were suggested for three operating modes: optimized electrical efficiency, peak power, and heat generation. Depending on the situation, the demand for electricity and heat can be different, so different proper operating points are suggested for each mode. Additionally, using the developed model and the conducted process of this study, various optimized operating conditions can be derived for diverse cases. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling)
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<p>Schematic diagram of a solid oxide fuel cell (SOFC) system with anode off-gas recirculation (AOGR) (AOGR #2 system in ref. [<a href="#B7-energies-15-00644" class="html-bibr">7</a>]).</p> Full article ">Figure 2
<p>Sensitivity of (<b>a</b>) CH<sub>4</sub> flow rate, (<b>b</b>) air flow rate, and (<b>c</b>) recirculation ratio on performance characteristics.</p> Full article ">Figure 2 Cont.
<p>Sensitivity of (<b>a</b>) CH<sub>4</sub> flow rate, (<b>b</b>) air flow rate, and (<b>c</b>) recirculation ratio on performance characteristics.</p> Full article ">Figure 3
<p>Changes of (<b>a</b>) fuel utilization factor (<math display="inline"><semantics> <mrow> <msub> <mi>U</mi> <mrow> <mi>f</mi> <mi>u</mi> <mi>e</mi> <mi>l</mi> </mrow> </msub> </mrow> </semantics></math>) and (<b>b</b>) electrical efficiency (<math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mrow> <mi>e</mi> <mi>l</mi> <mi>e</mi> <mi>c</mi> </mrow> </msub> <mo stretchy="false">)</mo> </mrow> </semantics></math> with various fuel flow rates and recirculation ratios at current density of 0.3 A/cm<sup>2</sup>.</p> Full article ">Figure 4
<p>Desired operating conditions of the SOFC system with various fuel flow rates and recirculation ratios at operating current densities of (<b>a</b>) 0.3 A/cm<sup>2</sup> and (<b>b</b>) 0.5 A/cm<sup>2</sup>.</p> Full article ">Figure 5
<p>Change of electrical efficiency with various fuel flow rates and recirculation ratios at operating current densities of (<b>a</b>) 0.3 A/cm<sup>2</sup> and (<b>b</b>) 0.5 A/cm<sup>2</sup>.</p> Full article ">Figure 6
<p>Change in net power with various fuel flow rates and recirculation ratios at operating current densities of (<b>a</b>) 0.3 A/cm<sup>2</sup> and (<b>b</b>) 0.5 A/cm<sup>2</sup>.</p> Full article ">Figure 7
<p>Change in thermal efficiency with various fuel flow rates and recirculation ratios at operating current densities of (<b>a</b>) 0.3 A/cm<sup>2</sup> and (<b>b</b>) 0.5 A/cm<sup>2</sup>.</p> Full article ">
17 pages, 2724 KiB  
Article
Energy Efficiency of Transport Tasks Performed by the Air SAR System in the Baltic Sea: Case Study
by Jerzy Fiuk, Norbert Chamier-Gliszczynski, Marianna Jacyna and Mariusz Izdebski
Energies 2022, 15(2), 643; https://doi.org/10.3390/en15020643 - 17 Jan 2022
Cited by 3 | Viewed by 1660
Abstract
The issues discussed in this article concern the energy efficiency of transport tasks carried out by the air SAR system in the Baltic Sea. Search and rescue (SAR) are rescue operations consisting of finding people in danger, providing them with help, and delivering [...] Read more.
The issues discussed in this article concern the energy efficiency of transport tasks carried out by the air SAR system in the Baltic Sea. Search and rescue (SAR) are rescue operations consisting of finding people in danger, providing them with help, and delivering them to a safe place. The transport task is an element of the rescue operations carried out in the open water area. It is carried out by a given type of helicopter from a strictly defined rescue base. The aim of the article is to develop a method of selecting the base and means of transport for the transport task carried out by the air SAR system, based on the assessment of energy efficiency of a given transport task. The article proposes a selection model; parameterization of the model was carried out, indicators of energy efficiency evaluation were determined, and limitations were indicated. In practical terms, the authors’ model of selection is presented on the example of transport tasks carried out by the air SAR system in the Polish zone of responsibility in the Baltic Sea. Full article
(This article belongs to the Special Issue Energy Intensity of Transport and Environmentally Friendly Mobility)
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<p>Algorithm for the implementation of the transport task.</p> Full article ">Figure 2
<p>The Polish zone of maritime search and rescue responsibility in the Baltic Sea.</p> Full article ">Figure 3
<p>Types of helicopters equipped with the aviation SAR system: (<b>a</b>) Mi-14 PS, (<b>b</b>) W-3RM Anakonda.</p> Full article ">Figure 4
<p>Dependence of the operation time in the search area depending on the search speed <span class="html-italic">vpo</span> achieved by the helicopter; optimal search speed is <span class="html-italic">vpo</span> = 130 km/h, constant cruising speed of the helicopter <span class="html-italic">vp</span> = 220 km/h and the set of search radius <span class="html-italic">rp</span> = (100, 150, 200, 250 km).</p> Full article ">Figure 5
<p>Range of operation of active SAR bases in Polish System (EPDA and EPOK) with provisionary base in Dziwnów.</p> Full article ">Figure 6
<p>Rescue mission distance from base for missions which started from both EPDA and EPOK bases in years 1995–2001; Mi-14 PS and W3-RM helicopters were used.</p> Full article ">Figure 7
<p>Range from base for simulated missions which started from Dziwnów base in years 1995–2001; W3-RM and Mi-13PS helicopters were used.</p> Full article ">Figure 8
<p>Range from base for simulated missions closer than 150 km which started from Dziwnów base in years 1995–2001; W3-RM and Mi-13PS helicopters were used.</p> Full article ">Figure 9
<p>Distance distribution for missions that started from EPOK and EPDA bases in 1995–2001; W3-RM and Mi-13PS helicopters were used.</p> Full article ">Figure 10
<p>Distance distribution for simulated missions that started from Dziwnów base in 1995–2001; W3-RM and Mi-13PS helicopters were used.</p> Full article ">
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