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Energies, Volume 14, Issue 4 (February-2 2021) – 425 articles

Cover Story (view full-size image): As the most abundant element in the world, hydrogen is a promising energy carrier and has received continuously growing attention. This review paper summarizes the latest findings on solid-state storage solutions of different non-equilibrium systems that have been synthesized by mechanical routes based on severe plastic deformation. View this paper.
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21 pages, 10215 KiB  
Article
A Novel Co-Phase Power Supply System for Electrified Railway Based on V Type Connection Traction Transformer
by Shaofeng Xie, Yiming Zhang and Hui Wang
Energies 2021, 14(4), 1214; https://doi.org/10.3390/en14041214 - 23 Feb 2021
Cited by 11 | Viewed by 3909
Abstract
Power quality and neutral section are two technical problems that hinder the development of electrified railway to high-speed and heavy railway. The co-phase power supply technology is one of the best ways to solve these two technical problems. At present, a V type [...] Read more.
Power quality and neutral section are two technical problems that hinder the development of electrified railway to high-speed and heavy railway. The co-phase power supply technology is one of the best ways to solve these two technical problems. At present, a V type connection traction transformer is widely used in a power frequency single-phase AC traction power supply system, especially in high-speed railway. In this paper, a new type of co-phase power supply system for electrified railway based on V type connection traction transformer is proposed. One single-phase winding in the V type connection traction transformer is used as main power supply channel, and three ports are used as compensation ports. Neutral section is no longer set with traction substation, and the train is continuously powered through. The independent single-phase Static Var Generators (SVGs) are used to compensate the three-phase imbalance caused by single-phase traction load. When necessary, the power factor can be improved at the same time. The principle, structure, control strategy, and capacity configuration of the technical scheme are analyzed in this paper, and the effectiveness of the scheme is verified by using the measured data of electrified railway. The advantage of this scheme lies in the universal applicability of the V type connection traction transformer, and the flexibility of the SVG device. Full article
(This article belongs to the Special Issue Power Quality in Electrified Transportation Systems)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Structure diagram of China’s existing traction power supply system.</p> Full article ">Figure 2
<p>Structure diagram of traction substation with co-phase power supply. (<b>a</b>) Traction substation under direct power supply mode; (<b>b</b>) traction substation under Auto Transformer (AT) power supply mode.</p> Full article ">Figure 3
<p>Phasor diagram of comprehensive compensation principle. (<b>a</b>) Phasor diagram of Positive sequence; (<b>b</b>) phasor diagram of Negative sequence.</p> Full article ">Figure 4
<p>Simplified electrical schematic diagram of Traction Compensation Transformer (TCT).</p> Full article ">Figure 5
<p>Block diagram of expected value detection of compensation currents.</p> Full article ">Figure 6
<p>Control block diagram of Comprehensive Compensation Equipment (CCE).</p> Full article ">Figure 7
<p>Schematic diagram of the process of determining the values of <math display="inline"> <semantics> <mrow> <msub> <mi>K</mi> <mi>C</mi> </msub> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <msub> <mi>K</mi> <mi>N</mi> </msub> </mrow> </semantics> </math>.</p> Full article ">Figure 8
<p>Diagram of 24-h load curve of the traction substation.</p> Full article ">Figure 9
<p>Diagram of 24-h three-phase voltage unbalance degree curve of the traction substation.</p> Full article ">Figure 10
<p>Diagram of 24-h <math display="inline"> <semantics> <mrow> <msub> <mi>K</mi> <mi>C</mi> </msub> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <msub> <mi>K</mi> <mi>N</mi> </msub> </mrow> </semantics> </math> calculation results curve of the traction substation. (<b>a</b>) Diagram of calculation results for reactive power compensation degree <math display="inline"> <semantics> <mrow> <msub> <mi>K</mi> <mi>C</mi> </msub> </mrow> </semantics> </math> during a day; (<b>b</b>) diagram of calculation results for negative sequence compensation degree <math display="inline"> <semantics> <mrow> <msub> <mi>K</mi> <mi>N</mi> </msub> </mrow> </semantics> </math> during a day.</p> Full article ">Figure 11
<p>Diagram of device output curve of the CCE during a day. (<b>a</b>) Diagram of device output curve of the Static Var Generator (SVG)1 during a day; (<b>b</b>) diagram of device output curve of the SVG2 during a day; (<b>c</b>) diagram of device output curve of the SVG3 during a day; (<b>d</b>) diagram of total device output curve of the CCE during a day.</p> Full article ">Figure 12
<p>Diagram of 24-h three-phase voltage unbalance degree curve of the traction substation (before and after compensation).</p> Full article ">Figure 13
<p>Diagram of 24-h power factor curve of the traction substation (before and after compensation).</p> Full article ">Figure 14
<p>Diagram of statistical result of the data in <a href="#energies-14-01214-f012" class="html-fig">Figure 12</a> and <a href="#energies-14-01214-f013" class="html-fig">Figure 13</a>. (<b>a</b>) Diagram of statistical result of three-phase voltage unbalance degree during a day before and after compensation; (<b>b</b>) diagram of statistical result of power factor during a day before and after compensation.</p> Full article ">Figure 15
<p>Diagram of comprehensive compensation control strategy simulation.</p> Full article ">Figure 16
<p>Simulation results at Point of Common Coupling (PCC) before and after comprehensive compensation.</p> Full article ">Figure 17
<p>Simulation results at PCC before and after negative sequence power compensation.</p> Full article ">Figure 18
<p>Simulation results at PCC before and after reactive power compensation.</p> Full article ">
20 pages, 8561 KiB  
Article
Neural Network Approach for Global Solar Irradiance Prediction at Extremely Short-Time-Intervals Using Particle Swarm Optimization Algorithm
by Ahmed Aljanad, Nadia M. L. Tan, Vassilios G. Agelidis and Hussain Shareef
Energies 2021, 14(4), 1213; https://doi.org/10.3390/en14041213 - 23 Feb 2021
Cited by 42 | Viewed by 4347
Abstract
Hourly global solar irradiance (GSR) data are required for sizing, planning, and modeling of solar photovoltaic farms. However, operating and controlling such farms exposed to varying environmental conditions, such as fast passing clouds, necessitates GSR data to be available for very short time [...] Read more.
Hourly global solar irradiance (GSR) data are required for sizing, planning, and modeling of solar photovoltaic farms. However, operating and controlling such farms exposed to varying environmental conditions, such as fast passing clouds, necessitates GSR data to be available for very short time intervals. Classical backpropagation neural networks do not perform satisfactorily when predicting parameters within short intervals. This paper proposes a hybrid backpropagation neural networks based on particle swarm optimization. The particle swarm algorithm is used as an optimization algorithm within the backpropagation neural networks to optimize the number of hidden layers and neurons used and its learning rate. The proposed model can be used as a reliable model in predicting changes in the solar irradiance during short time interval in tropical regions such as Malaysia and other regions. Actual global solar irradiance data of 5-s and 1-min intervals, recorded by weather stations, are applied to train and test the proposed algorithm. Moreover, to ensure the adaptability and robustness of the proposed technique, two different cases are evaluated using 1-day and 3-days profiles, for two different time intervals of 1-min and 5-s each. A set of statistical error indices have been introduced to evaluate the performance of the proposed algorithm. From the results obtained, the 3-days profile’s performance evaluation of the BPNN-PSO are 1.7078 of RMSE, 0.7537 of MAE, 0.0292 of MSE, and 31.4348 of MAPE (%), at 5-s time interval, where the obtained results of 1-min interval are 0.6566 of RMSE, 0.2754 of MAE, 0.0043 of MSE, and 1.4732 of MAPE (%). The results revealed that proposed model outperformed the standalone backpropagation neural networks method in predicting global solar irradiance values for extremely short-time intervals. In addition to that, the proposed model exhibited high level of predictability compared to other existing models. Full article
(This article belongs to the Special Issue Solar Radiation Forecasting and Photovoltaic Systems Performance Modeling)
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Figure 1

Figure 1
<p>Backpropagation neural networks (BPNN) structure with seven inputs, one output, and multi hidden nodes.</p> Full article ">Figure 2
<p>The structure of the proposed backpropagation neural network based on Particle Swarm Optimization Algorithm (PSO) algorithm.</p> Full article ">Figure 3
<p>Flowchart of the proposed hybrid backpropagation neural network based on particle swarm optimization algorithm (BPNN-PSO) model.</p> Full article ">Figure 4
<p>The convergence performance curves of solar irradiance prediction for 3-days, with 1-min and 5-s time interval.</p> Full article ">Figure 5
<p>The convergence performance curves of solar irradiance prediction for 1-Day, with 1-min and 5-s time interval.</p> Full article ">Figure 6
<p>The photovoltaics solar prediction results using 3-days profile with 5-s time interval. (<b>a</b>) Solar irradiance prediction. (<b>b</b>) Solar irradiance prediction error.</p> Full article ">Figure 7
<p>The photovoltaics prediction results using 3-days profile with 1-min time interval. (<b>a</b>) Solar irradiance prediction. (<b>b</b>) Solar irradiance prediction error.</p> Full article ">Figure 8
<p>The prediction results using 1-day profile with 5-s time interval. (<b>a</b>) Photovoltaics (PV) solar irradiance prediction. (<b>b</b>) Photovoltaics (PV) solar irradiance prediction error.</p> Full article ">Figure 9
<p>The prediction results using 1-day profile with 1-min time interval. (<b>a</b>) Photovoltaics (PV) solar irradiance prediction. (<b>b</b>) Photovoltaics (PV) solar irradiance prediction error.</p> Full article ">Figure 10
<p>Regression performance of 3-days profile (<b>a</b>) BPNN-PSO, with 5-s time interval. (<b>b</b>) BPNN-PSO, with 1-min time interval.</p> Full article ">Figure 11
<p>Regression performance of 1-day profile. (<b>a</b>) BPNN-PSO with 5-s time interval. (<b>b</b>) BPNN-PSO with 1-min time interval.</p> Full article ">
14 pages, 4626 KiB  
Article
Effect of the Reactant Transportation on Performance of a Planar Solid Oxide Fuel Cell
by Yongqing Wang, Xingchen Li, Zhenning Guo, Ke Wang and Yan Cao
Energies 2021, 14(4), 1212; https://doi.org/10.3390/en14041212 - 23 Feb 2021
Cited by 3 | Viewed by 2330
Abstract
The process of reactant transportation greatly affects the performance of solid oxide fuel cells (SOFCs). Therefore, a three-dimension numerical SOFC model was built to evaluate mainly the effect of the reactant transportation coupling of heat and mass transfer and electrochemical reactions, and the [...] Read more.
The process of reactant transportation greatly affects the performance of solid oxide fuel cells (SOFCs). Therefore, a three-dimension numerical SOFC model was built to evaluate mainly the effect of the reactant transportation coupling of heat and mass transfer and electrochemical reactions, and the reliability of numerical calculations was validated. Numerical studies revealed the correlation of both increase of reactant concentration gradients and improved mass transfer capability of multi reactants in gas diffusion electrode with the enhancement of the SOFC performance, in the condition of enough supplies of the fuel and the oxidant. Further studies identified the oxygen ions conductivity in electrolytes played a critical role in energy output and thus the performance of SOFCs. For example, the current density would increase by 65% if the ionic conductivity of electrolytes doubled. This study gives insight into the significance of operational conditions, electrolytes, and structures on the ionic oxygen conductivity and further on the optimization of the SOFCs. Overall, the numerical modeling leads a clear path toward the optimization of SOFCs. Full article
(This article belongs to the Section A5: Hydrogen Energy)
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Figure 1
<p>Numerical solid oxide fuel cell (SOFC) model.</p> Full article ">Figure 2
<p>Comparison of the numerical results with those in [<a href="#B25-energies-14-01212" class="html-bibr">25</a>,<a href="#B27-energies-14-01212" class="html-bibr">27</a>]: (<b>a</b>) cell voltage versus current density and (<b>b</b>) power density versus current density.</p> Full article ">Figure 3
<p>Numerical model without the interconnect.</p> Full article ">Figure 4
<p>Comparison of main SOFC performance parameters.</p> Full article ">Figure 5
<p>Distribution of mole fractions of oxygen and hydrogen along the cathode channel: (<b>a</b>) model concerning interconnects and (<b>b</b>) model not concerning interconnects.</p> Full article ">Figure 5 Cont.
<p>Distribution of mole fractions of oxygen and hydrogen along the cathode channel: (<b>a</b>) model concerning interconnects and (<b>b</b>) model not concerning interconnects.</p> Full article ">Figure 6
<p>Comparison among the different inlet gas conditions.</p> Full article ">Figure 7
<p>Distribution of hydrogen mole fraction along the anode channel.</p> Full article ">Figure 8
<p>Distribution of oxygen mole fraction on the middle cross section: (<b>a</b>) mole fraction contours of oxygen and (<b>b</b>) mole fraction of oxygen in electrode.</p> Full article ">Figure 9
<p>Comparison between two cases with different ionic conductivities: (<b>a</b>) cell voltage and the power density and (<b>b</b>) current density distribution.</p> Full article ">
17 pages, 3773 KiB  
Article
An Analysis of Repeating Thermal Bridges from Timber Frame Fraction in Closed Panel Timber Frame Walls: A Case Study from Wales, UK
by Francesco Zaccaro, John Richard Littlewood and Carolyn Hayles
Energies 2021, 14(4), 1211; https://doi.org/10.3390/en14041211 - 23 Feb 2021
Cited by 3 | Viewed by 3700
Abstract
Calculating Repeating Thermal Bridges (RTBs) for Timber Frame (TF) closed panels that could occur in Offsite Manufactured (OSM) Modern Methods of Construction (MMC), such as exterior walls for nearly-to-zero operational energy dwellings to be constructed in Wales, United Kingdom (UK) is discussed in [...] Read more.
Calculating Repeating Thermal Bridges (RTBs) for Timber Frame (TF) closed panels that could occur in Offsite Manufactured (OSM) Modern Methods of Construction (MMC), such as exterior walls for nearly-to-zero operational energy dwellings to be constructed in Wales, United Kingdom (UK) is discussed in this paper. Detailed calculations for linear RTBs due to the TF components are often neglected when evaluating thermal transmittance (known as U-values hereafter). The use of standard TF fractions does not allow the designer to perceive their detrimental impact on RTBs and consequent U-values for exterior walls. With the increase of the thermal performance of exterior walls and as such lower U-values due to ever-tightening Building Regulations, specifically related to the energy use and carbon emissions from the space heating of dwellings, then the impacts of RTBs requires more investigation. By not calculating the potential of linear RTB at the design stage could lead to a performance gap where assumed U-values for exterior walls differ from manufacture to onsite. A TF detail from the Welsh manufacture has been chosen as a case study, to develop and apply a methodology using manufacturing drawings to evaluate TF fraction and their effect on the thermal performance. Full article
(This article belongs to the Special Issue Environmental and Sustainable Built Environments)
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Figure 1
<p>Examples of TB: (<b>a</b>) linear (two walls) (<b>b</b>) point (roof-walls) (<b>c</b>) repeating (wall joists) (<b>d</b>) non-repeating (multiple linear TB on the building). Reprinted with permission from ref. [<a href="#B27-energies-14-01211" class="html-bibr">27</a>], Springer, Singapore, 2021.</p> Full article ">Figure 2
<p>Effect of TFF on U-value for different flanking insulation values and reflective membranes.</p> Full article ">Figure 3
<p>Effect of TFF on U-value for different flanking insulation values and reflective membranes.</p> Full article ">Figure 4
<p>Comparison of two solutions with the same total thickness: the first (red lines) 220 mm core and 50 mm flanking insulation; the second (yellow lines) 140 mm core and 130 mm flanking insulation.</p> Full article ">Figure 5
<p>TFF calculation rules for closed panels: panel without apertures (<b>a</b>) and with aperture (<b>b</b>). Panel junction rules: two consecutive panels (<b>c</b>), corner panels (<b>d</b>), partition-external wall junction (<b>e</b>), party wall- external wall junction (<b>f</b>).</p> Full article ">Figure 6
<p>Variation of U-value offsite/onsite for the construction detail of <a href="#energies-14-01211-f002" class="html-fig">Figure 2</a> with 140 mm core insulation, 0 mm (<b>a</b>) and 50 mm (<b>b</b>) flanking insulation.</p> Full article ">Figure 7
<p>Variation of U-value offsite/onsite for the construction detail of <a href="#energies-14-01211-f002" class="html-fig">Figure 2</a>. with 197 mm core insulation, 0 mm (<b>a</b>) and 50 mm (<b>b</b>) flanking insulation.</p> Full article ">
15 pages, 4939 KiB  
Article
Field Performance of South-Facing and East-West Facing Bifacial Modules in the Arctic
by Christopher Pike, Erin Whitney, Michelle Wilber and Joshua S. Stein
Energies 2021, 14(4), 1210; https://doi.org/10.3390/en14041210 - 23 Feb 2021
Cited by 23 | Viewed by 7966
Abstract
This paper presents the first systematic comparison between south-facing monofacial and bifacial photovoltaic (PV) modules, as well as between south-facing bifacial and vertical east-west facing bifacial PV modules in Alaska. The state’s solar industry, driven by the high price of energy and dropping [...] Read more.
This paper presents the first systematic comparison between south-facing monofacial and bifacial photovoltaic (PV) modules, as well as between south-facing bifacial and vertical east-west facing bifacial PV modules in Alaska. The state’s solar industry, driven by the high price of energy and dropping equipment costs, is quickly growing. The challenges posed by extreme sun angles in Alaska’s northern regions also present opportunities for unique system designs. Annual bifacial gains of 21% were observed between side by side south-facing monofacial and bifacial modules. Vertical east-west bifacial modules had virtually the same annual production as south-facing latitude tilt bifacial modules, but with different energy production profiles. Full article
(This article belongs to the Special Issue Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling)
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Figure 1

Figure 1
<p>The solar photovoltaic (PV) bifacial test site on the campus of the University of Alaska Fairbanks at 64° N.</p> Full article ">Figure 2
<p>Global horizontal insolation for the time period discussed in this paper as measured by a Hukseflux SR-30 pyranometer at the site.</p> Full article ">Figure 3
<p>The normalized monthly energy output of each south-facing PV module with the bifacial gain written above the monthly columns.</p> Full article ">Figure 4
<p>The daily average albedo for the study period when the solar elevation was greater than 5°. It should be noted that between 20 September 2019 and 1 July 2020 (shown with the two black vertical lines), the albedometer was located in an agricultural field adjacent to the solar test site to minimize horizon obstructions.</p> Full article ">Figure 5
<p>Bifacial gain calculated using Equation (2), the rear irradiance ratio (<span class="html-italic">Q<sub>rear fraction</sub></span>) calculated using Equation (4), and the average monthly albedo.</p> Full article ">Figure 6
<p>Calculated energy loss from clipping from one south-facing bifacial module.</p> Full article ">Figure 7
<p>Plane-of-array (POA) irradiance and south-facing bifacial module temperature are shown over time. The data points that correspond to the time of inverter clipping are highlighted in red.</p> Full article ">Figure 8
<p>Scatter plots show the relationship between the power output, POA irradiance, and total irradiance calculated using Equation (3), as well as the module temperature.</p> Full article ">Figure 9
<p>The relationship between the minimum total irradiance value where clipping occurred at each temperature is shown along with a line of best fit. Values that fall above the line would be clipped at a 290 W output by the inverters.</p> Full article ">Figure 10
<p>The normalized monthly energy production of the south-facing bifacial PV modules and the vertical east-west PV modules with the monthly vertical production gain (or loss) relative to the south-facing modules written above the monthly columns.</p> Full article ">Figure 11
<p>The average hourly production for south-facing bifacial PV modules and vertical east-west facing bifacial modules is shown for each month of the study period in Alaska Standard Time.</p> Full article ">Figure 12
<p>A load profile for a Rural Alaska community is scaled to 100 kW max load and shown along with June production profiles scaled to never exceed the load for south-facing bifacial, east-west vertical bifacial, and a combination of these orientations.</p> Full article ">Figure 13
<p>One year of cumulative energy production data are shown for each PV module included in this study. Unlike the graphs above, this graph includes winter data, when the snow on the modules affected performance.</p> Full article ">
36 pages, 8356 KiB  
Article
Influence of Electrification Pathways in the Electricity Sector of Ethiopia—Policy Implications Linking Spatial Electrification Analysis and Medium to Long-Term Energy Planning
by Ioannis Pappis, Andreas Sahlberg, Tewodros Walle, Oliver Broad, Elusiyan Eludoyin, Mark Howells and Will Usher
Energies 2021, 14(4), 1209; https://doi.org/10.3390/en14041209 - 23 Feb 2021
Cited by 28 | Viewed by 6289
Abstract
Ethiopia is a low-income country, with low electricity access (45%) and an inefficient power transmission network. The government aims to achieve universal access and become an electricity exporter in the region by 2025. This study provides an invaluable perspective on different aspects of [...] Read more.
Ethiopia is a low-income country, with low electricity access (45%) and an inefficient power transmission network. The government aims to achieve universal access and become an electricity exporter in the region by 2025. This study provides an invaluable perspective on different aspects of Ethiopia’s energy transition, focusing on achieving universal access and covering the country’s electricity needs during 2015–2065. We co-developed and investigated three scenarios to examine the policy and technology levels available to the government to meet their national priorities. To conduct this analysis, we soft-linked OnSSET, a modelling tool used for geospatial analysis, with OSeMOSYS, a cost-optimization modelling tool used for medium to long-run energy planning. Our results show that the country needs to diversify its power generation system to achieve universal access and cover its future electricity needs by increasing its overall carbon dioxide emissions and fully exploit hydropower. With the aim of achieving universal access by 2025, the newly electrified population is supplied primarily by the grid (65%), followed by stand-alone (32%) technologies. Similarly, until 2065, most of the electrified people by 2025 will continue to be grid-connected (99%). The country’s exports will increase to 17 TWh by 2065, up from 832 GWh in 2015, leading to a cumulative rise in electricity export revenues of 184 billion USD. Full article
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<p>Summary of the approach followed to support the development of electrification pathways policies.</p> Full article ">Figure 2
<p>Overview of the modeling approach: soft-linking the OSeMOSYS model with the OnSSET model.</p> Full article ">Figure 3
<p>Evolution of the electricity demand (TWh) in each scenario.</p> Full article ">Figure 4
<p>Power generation capacity of grid-connected technologies in the New Policies scenario.</p> Full article ">Figure 5
<p>Electricity supply mix of grid-connected technologies in the New Policies scenario.</p> Full article ">Figure 6
<p>Population (million people) connected per technology (grid, mini grid, stand-alone) in the New Policy scenario.</p> Full article ">Figure 7
<p>Total system costs and electricity export revenues in the New Policies scenario.</p> Full article ">Figure 8
<p>Comparison of power generation capacity between Slow Down vs New Policies scenarios.</p> Full article ">Figure 9
<p>Comparison of power generation capacity between Big Business vs New Policies scenarios.</p> Full article ">Figure 10
<p>Comparison of electricity supply mix between Slow Down vs New Policies scenario.</p> Full article ">Figure 11
<p>Newly connected population (million people) per technology (grid, mini grid, stand-alone) in residential areas in the Slow Down vs New Policy scenario.</p> Full article ">Figure 12
<p>Comparison of electricity supply mix between Big Business vs New Policies scenario.</p> Full article ">Figure 13
<p>Newly connected population (million people) per technology (grid, mini grid, stand-alone) in residential areas in the Big Business vs New Policy scenario.</p> Full article ">Figure 14
<p>Technology split in 2025 (left map) and 2070 (right map) in the New Policies scenario. Blue areas are national grid-connected, red ones by mini grids, green by hydro mini grids and yellow by stand-alone PV.</p> Full article ">Figure 15
<p>Technology split in 2025 (left map) and 2070 (right map) in the Slow Down scenario. Blue areas are national grid-connected, red ones by mini grids, green by hydro mini grids and yellow by stand-alone PV.</p> Full article ">Figure 16
<p>Technology split in 2025 (left map) and 2070 (right map) in the Big Business scenario. Blue areas are national grid-connected, red ones by mini grids, green by hydro mini grids and yellow by stand-alone PV.</p> Full article ">Figure 17
<p>Comparison of total system costs between Slow Down vs New Policies scenario.</p> Full article ">Figure 18
<p>Comparison of carbon dioxide emissions among the scenarios.</p> Full article ">Figure 19
<p>Electricity exports capacity (GW) in the New Policies scenario.</p> Full article ">Figure 20
<p>Comparison of electricity exports capacity (GW) between Slow Down vs New Policies.</p> Full article ">Figure 21
<p>Comparison of electricity exports (GWh) among the scenarios.</p> Full article ">
11 pages, 9373 KiB  
Article
Analysis and Experimental Verification of a Variable Speed Turbo Air Centrifugal Compressor System for Energy Saving
by Sung-An Kim and Kyung-Pyo Hong
Energies 2021, 14(4), 1208; https://doi.org/10.3390/en14041208 - 23 Feb 2021
Cited by 2 | Viewed by 3348
Abstract
Conventional constant speed turbo air centrifugal compressor systems (TACCSs) consist of an electric motor driven at the constant speed and an inlet guide vane (IGV) for pressure control. TACCSs with an inverter for a variable speed drive (VSD) of the electric motor are [...] Read more.
Conventional constant speed turbo air centrifugal compressor systems (TACCSs) consist of an electric motor driven at the constant speed and an inlet guide vane (IGV) for pressure control. TACCSs with an inverter for a variable speed drive (VSD) of the electric motor are more efficient than the conventional constant speed TACCS because they have a wide operating range and can minimize the power consumption. Therefore, this paper proposes a quadratic V/f control and VSD to reduce electrical and mechanical energy losses. To verify the energy saving effect of the TACCS with the proposed controls, this paper analyzes the performances of an electric motor drive system (EMDS) using the proposed quadratic V/f control considering load conditions of the turbo air centrifugal compressor (TACC) to reduce electrical energy losses. Furthermore, the performances of the conventional constant speed drive (CSD) using the IGV control and the proposed VSD were compared and analyzed in the test bench that represented an actual factory environment. As a result, the proposed quadratic V/f control and VSD experimentally verified energy savings of 4.44% and 23.37% compared to conventional controls. In addition, the economic feasibility of the proposed VSD was verified in the TACCS by analyzing the recovery period of the initial investment due to the addition of the inverter. Full article
(This article belongs to the Section F: Electrical Engineering)
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Figure 1
<p>Block diagram of a turbo air centrifugal compressor system (TACCS). IGV: inlet guide vane; BOV: blow of valve; CV: control valve.</p> Full article ">Figure 2
<p>Experimental configuration for performance evaluation of the electric motor drive system (EMDS) according to load curves. (<b>a</b>) Ideal load curves; (<b>b</b>) diagram of experimental configuration.</p> Full article ">Figure 3
<p>Experimental setups for performance evaluation of the EMDS. (<b>a</b>) Induction motor and dynamometer; (<b>b</b>) multi-level inverter.</p> Full article ">Figure 4
<p>Operating principle according to linear V/f control and quadratic V/f control. (<b>a</b>) Voltage pattern curves; (<b>b</b>) control configuration. SPWM: sinusoidal pulse width modulation.</p> Full article ">Figure 5
<p>Performance curves measured at the input terminals of induction motor according to linear and quadratic V/f controls. (<b>a</b>) Line to line voltages curves; (<b>b</b>) phase current curves; (<b>c</b>) power curves; (<b>d</b>) efficiency curves of the induction motor.</p> Full article ">Figure 6
<p>Performance curves measured at the input terminals of multi-level inverter according to linear and quadratic V/f controls. (<b>a</b>) Line to line voltages curves; (<b>b</b>) phase current curves; (<b>c</b>) power curves; (<b>d</b>) efficiency curves of EMDS.</p> Full article ">Figure 6 Cont.
<p>Performance curves measured at the input terminals of multi-level inverter according to linear and quadratic V/f controls. (<b>a</b>) Line to line voltages curves; (<b>b</b>) phase current curves; (<b>c</b>) power curves; (<b>d</b>) efficiency curves of EMDS.</p> Full article ">Figure 7
<p>Experimental setup for performance evaluation of TACCS. TACC: turbo air centrifugal compressor.</p> Full article ">Figure 8
<p>Performance curves of the TACCS using the constant speed drive (CSD). (<b>a</b>) Pressure curves; (<b>b</b>) isothermal efficiency curves; (<b>c</b>) power curves.</p> Full article ">Figure 9
<p>Performance curves of the TACCS with the variable speed drive (VSD). (<b>a</b>) Pressure curves; (<b>b</b>) isothermal efficiency curves; (<b>c</b>) power curves.</p> Full article ">Figure 10
<p>Power consumption curves of the TACCS according to the CSD and VSD. (<b>a</b>) Power curve of the TACCS at no load condition; (<b>b</b>) comparison of power and power consumption curves.</p> Full article ">Figure 11
<p>Recovery period of the initial investment in Korea.</p> Full article ">
35 pages, 7417 KiB  
Article
Longitudinal Dynamics Simulation Tool for Hybrid APU and Full Electric Vehicle
by Giulia Sandrini, Marco Gadola and Daniel Chindamo
Energies 2021, 14(4), 1207; https://doi.org/10.3390/en14041207 - 23 Feb 2021
Cited by 13 | Viewed by 3517
Abstract
Due to problems related to environmental pollution and fossil fuels consumption that have not infinite availability, the automotive sector is increasingly moving towards electric powertrains. The most limiting aspect of this category of vehicles is certainly the battery pack, regarding the difficulty in [...] Read more.
Due to problems related to environmental pollution and fossil fuels consumption that have not infinite availability, the automotive sector is increasingly moving towards electric powertrains. The most limiting aspect of this category of vehicles is certainly the battery pack, regarding the difficulty in obtaining high range with good performance and low weights. The aim of this work is to provide a simulation tool, which allows for the analysis of the performance of different types of electric and hybrid powertrains, concerning both mechanical and electrical aspects. Through this model it is possible to test different vehicle configurations before prototype realization or to investigate the impact that subsystems’ modifications may have on a vehicle under development. This will allow to speed-up the model-based design process typical for fully electric and hybrid vehicles. The model aims to be at the same time complete but simple enough to lower the simulation time and computational burden so that it can be used in real-time applications, such as driving simulators. All this reduces the time and costs of vehicle design. Validation is also provided, based on a real vehicle and comparison with another consolidated simulation tool. Maximum error on mechanical quantities is proved to be within 5% while on electrical quantities it is always lower than 10%. Full article
(This article belongs to the Special Issue Vehicle Dynamics and Control)
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<p>Conceptual scheme of the Simulink model developed for the simulation of the longitudinal dynamics of an electric or hybrid vehicle that follows a target speed profile.</p> Full article ">Figure 2
<p>The “Datasheet Battery” block and its connections with model parameters. The “Datasheet Battery” block is present in the “Simulink Library Browser” in the “Powertrain Blockset”.</p> Full article ">Figure 3
<p>Simulink logical scheme adopted to obtain the instantaneous vehicle speed.</p> Full article ">Figure 4
<p>Different panels of the Graphic User Interface. In particular, the panels allow you to enter the inputs regarding: (<b>a</b>) The simulation parameters; (<b>b</b>) Environmental and other parameters; (<b>c</b>) Vehicle and Wheels parameters; (<b>d</b>) Brakes parameters; (<b>e</b>) Battery Pack parameters; (<b>f</b>) Motor and Transmission parameters; (<b>g</b>) Generators parameters.</p> Full article ">Figure 5
<p>Peak torque and the continuous torque of the traction motor vs. the speed of rotation of the electric motor itself (in RPM).</p> Full article ">Figure 6
<p>Discharge and charge current limits (in Ampere) vs. the State of Charge (SOC) of the battery pack.</p> Full article ">Figure 7
<p>General overview of the results screen, where the abscissa axes show the time expressed in seconds. The units of measure and the parameters of the ordinate axes are shown in the legends. In the two graphs showing the acceleration and deceleration limitations, the value of the limitation is equal to one if this has intervened, 0 vice versa.</p> Full article ">Figure 8
<p>Motor torque (in Nm) vs. lap time expressed in seconds. In particular, in the figure, there are the motor torque resulting from the model (in red) and the motor torque acquired through the Vehicle Control Unit (VCU) of the waste collection vehicle prototype (in blue).</p> Full article ">Figure 9
<p>Battery power (in kW) vs. lap time expressed in seconds. In particular, in the figure, there are the battery power resulting from the calibrated model (in red) and the battery power acquired through the VCU of the waste collection vehicle prototype (in blue).</p> Full article ">Figure 10
<p>Battery current (in Ampere, first graph) and the battery voltage (in Volt, second graph) vs. lap time expressed in seconds. In particular, in the figure, there are the battery current and voltage resulting from the calibrated model (in red) and the battery current and voltage acquired through the VCU of the waste collection vehicle prototype (in blue).</p> Full article ">Figure 11
<p>Battery SOC vs. lap time expressed in seconds. In particular, in the figure, there are the battery SOC (in percentage) resulting from the calibrated model (in red) and the battery SOC (in percentage) acquired through the VCU (in particular from the BMS) of the waste collection vehicle prototype (in blue).</p> Full article ">Figure 12
<p>Maximum motor torque vs. motor RPM. The graph is relating to the hypercar electric motors in maximum admission condition.</p> Full article ">Figure 13
<p>Discharge (positive) and charge (negative) current limits (in Watt) vs. the SOC of the battery pack.</p> Full article ">Figure 14
<p>OCV (Open Circuit Voltage) vs. the SOC of the battery pack.</p> Full article ">Figure 15
<p>Nürburgring track, in its Nordschleife variant.</p> Full article ">Figure 16
<p>Elevation profile of the Nordschleife circuit. In particular, the graph shows the elevation vs. the “longitudinal” position of the hypercar on the track (the space travelled by the hypercar on the Nordschleife circuit).</p> Full article ">Figure 17
<p>Speed profile imposed for the calibration of the model, for the simulation of the hypercar.</p> Full article ">Figure 18
<p>Comparison between TEST (without calibration) and PROPS total torques during the execution of the calibration speed profile.</p> Full article ">Figure 19
<p>Ratio between the TEST and PROPS torques vs. vehicle speed.</p> Full article ">Figure 20
<p>Second degree polynomial (in red) that approximate the ratio between the TEST and PROPS torques (in blue).</p> Full article ">Figure 21
<p>TEST (in blue) and PROPS (in red) battery SOC (in percentage) vs. Lap Time (in seconds).</p> Full article ">Figure 22
<p>This graph shows TEST (in blue) and PROPS (in red) total motor torque (in Nm) vs. Lap Time (in seconds).</p> Full article ">Figure 23
<p>TEST (in blue) and PROPS (in red) battery power (in kW) vs. Lap Time (in seconds).</p> Full article ">Figure 24
<p>TEST (in blue) and PROPS (in red) battery current (in Ampere) vs. Lap Time (in seconds).</p> Full article ">Figure 25
<p>TEST (in blue) and PROPS (in red) battery voltage (in Volt) vs. Lap Time (in seconds).</p> Full article ">
15 pages, 7876 KiB  
Article
Elbows of Internal Resistance Rise Curves in Li-Ion Cells
by Calum Strange, Shawn Li, Richard Gilchrist and Gonçalo dos Reis
Energies 2021, 14(4), 1206; https://doi.org/10.3390/en14041206 - 23 Feb 2021
Cited by 24 | Viewed by 4311
Abstract
The degradation of lithium-ion cells with respect to increases of internal resistance (IR) has negative implications for rapid charging protocols, thermal management and power output of cells. Despite this, IR receives much less attention than capacity degradation in Li-ion cell research. Building on [...] Read more.
The degradation of lithium-ion cells with respect to increases of internal resistance (IR) has negative implications for rapid charging protocols, thermal management and power output of cells. Despite this, IR receives much less attention than capacity degradation in Li-ion cell research. Building on recent developments on ‘knee’ identification for capacity degradation curves, we propose the new concepts of ‘elbow-point’ and ‘elbow-onset’ for IR rise curves, and a robust identification algorithm for those variables. We report on the relations between capacity’s knees, IR’s elbows and end of life for the large dataset of the study. We enhance our discussion with two applications. We use neural network techniques to build independent state of health capacity and IR predictor models achieving a mean absolute percentage error (MAPE) of 0.4% and 1.6%, respectively, and an overall root mean squared error below 0.0061. A relevance vector machine, using the first 50 cycles of life data, is employed for the early prediction of elbow-points and elbow-onsets achieving a MAPE of 11.5% and 14.0%, respectively. Full article
(This article belongs to the Special Issue Li-Ion Batteries: Modelling and Control from Manufacturing to Performance Evaluation)
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<p>Schematic of machine learning model for internal resistance (IR) prediction.</p> Full article ">Figure 2
<p>The predicted IR data for cell b8c4 are given by the black continuous line and is formed from the average of 20 predictions. We display 80% and 95% prediction intervals. Beyond the intuition of extrapolation, these intervals show that predictions past the EOL (capacity) should not be trusted.</p> Full article ">Figure 3
<p>Graphical abstract for the proposed algorithmic framework.</p> Full article ">Figure 4
<p>Steps of Algorithm 1 applied to the internal resistance degradation curve of cell b1c29 (non-predicted data). (<b>a</b>), step 1. (<b>b</b>), step 3. (<b>c</b>), step 4. (<b>d</b>), step 5. Step 2 is omitted as it has no impact here: <math display="inline"><semantics> <msup> <mi>n</mi> <mo>*</mo> </msup> </semantics></math> is chosen as the final cycle number. The width of the 95% confidence interval (computed by the non-parametric bootstrapping procedure) for the elbow-point of this curve is 23 cycles, and for the elbow-onset it is 38 cycles.</p> Full article ">Figure 5
<p>(<b>a</b>), Comparison of elbow-points obtained with Algorithm 1, [<a href="#B19-energies-14-01206" class="html-bibr">19</a>]’s Bacon–Watts, maximum curvature and slope changing ratio methods on a sample of cells from the A123 dataset (from left to right b2c34, b1c30, b3c15, b3c1, b1c3). (<b>b</b>), Comparison of elbow-points for all cells in the A123 dataset. One expects to see a linear relationship between EOL and elbow-point; of the methods compared only Algorithm 1 and the algorithm of Satopaa et al. [2011] recover a linear relationship reliably, however, by examining plot (<b>a</b>), we see that Satopaa’s algorithm selects the end point as the elbow.</p> Full article ">Figure 6
<p>(<b>a</b>), Linear regression model linking the knee-point to end of life. (<b>b</b>), elbow-point to end of life. (<b>c</b>), knee-point to elbow-point. (<b>d</b>), knee-onset to elbow-onset. Every linear model is presented with a 95% confidence band on the plotted regression line; all linear relations here are calculated from the A123 dataset enriched with the predicted IR data for batch 8. Elbow points derived from the predicted IR data are highlighted as open black circles; the reader will appreciate that their inclusion did not significantly influence the linear regression results obtained.</p> Full article ">
23 pages, 2075 KiB  
Review
A Survey on Applications of Hybrid PV/T Panels
by Zain Ul Abdin and Ahmed Rachid
Energies 2021, 14(4), 1205; https://doi.org/10.3390/en14041205 - 23 Feb 2021
Cited by 34 | Viewed by 5711
Abstract
Photovoltaic-thermal (PV/T) collectors have gained a lot of attention in recent years due to their substantial advantages as compared to ST or PV systems alone and even to other non-solar technologies. However, PV/Ts are still not as popular in industry or construction and [...] Read more.
Photovoltaic-thermal (PV/T) collectors have gained a lot of attention in recent years due to their substantial advantages as compared to ST or PV systems alone and even to other non-solar technologies. However, PV/Ts are still not as popular in industry or construction and they are not even known to major players implementing solar energy installations. In this article, a general presentation of PV/Ts and a review of their applications are given. First, different heat extraction media (e.g., air, water, bi-fluid, etc.) and hybrid design configurations of hybrid PV/T collectors are addressed. Next, the main applications of PV/T collectors are discussed in order to highlight their feasibility and usefulness and to raise awareness for adoption in the industry and buildings sector. Applications include desalination, air-conditioning, drying, trigeneration, etc. This paper should be considered as a reference form of PV/Ts to extract key points for future research and development as well as for other applications. Full article
(This article belongs to the Special Issue Accelerating the Adoption of Solar Energy towards a Low-Carbon Future)
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<p>Sectional view of water-based photovoltaic-thermal (PV/T) collector.</p> Full article ">Figure 2
<p>Flow passages of a liqid-based PV/T collector: (<b>a</b>) oscillatory flow, (<b>b</b>) serpentine flow, (<b>c</b>) web flow, (<b>d</b>) parallel flow and (<b>e</b>) parallel-serpentine flow.</p> Full article ">Figure 3
<p>Schematic diagram of a nano-fluid based PV/T collector [<a href="#B31-energies-14-01205" class="html-bibr">31</a>].</p> Full article ">Figure 4
<p>Sectional view of PCM- based PV/T collector.</p> Full article ">Figure 5
<p>Different configurations of air-based PV/T collectors.</p> Full article ">Figure 6
<p>Sectional view of bi-fluid based PV/T collector.</p> Full article ">Figure 7
<p>PV/T roof-top array supplying heating and electricity to building.</p> Full article ">Figure 8
<p>Schematic diagram of solar absorption cooling [<a href="#B56-energies-14-01205" class="html-bibr">56</a>].</p> Full article ">Figure 9
<p>Schematic diagram of PV/T hybrid active solar still [<a href="#B70-energies-14-01205" class="html-bibr">70</a>].</p> Full article ">Figure 10
<p>Schematic diagram of PV/T integrated greenhouse dryer [<a href="#B73-energies-14-01205" class="html-bibr">73</a>].</p> Full article ">Figure 11
<p>PV/T district heating and cooling.</p> Full article ">Figure 12
<p>Structure of Community Energy Internet (CEI) with photovoltaic-thermal and heat pump (PV/T-HP) prosumers [<a href="#B80-energies-14-01205" class="html-bibr">80</a>].</p> Full article ">Figure 13
<p>Schematic diagram of PV/T tri-generation system setup [<a href="#B84-energies-14-01205" class="html-bibr">84</a>].</p> Full article ">Figure 14
<p>Schematic diagram of the proposed PV/T heat pump system on refrigeration mode [<a href="#B11-energies-14-01205" class="html-bibr">11</a>].</p> Full article ">Figure 15
<p>Solar driven direct-expansion heat pump system employing the novel PV/minichannels-evaporator modules [<a href="#B90-energies-14-01205" class="html-bibr">90</a>].</p> Full article ">
25 pages, 7160 KiB  
Article
A Back-of-Queue Model of a Signal-Controlled Intersection Approach Developed Based on Analysis of Vehicle Driver Behavior
by Elżbieta Macioszek and Damian Iwanowicz
Energies 2021, 14(4), 1204; https://doi.org/10.3390/en14041204 - 23 Feb 2021
Cited by 25 | Viewed by 4056
Abstract
In smart cities, it is expected that transport, communication as well as the movement of people and goods will take place in the shortest possible time while maintaining a high level of safety. In recent years, due to the significant increase in the [...] Read more.
In smart cities, it is expected that transport, communication as well as the movement of people and goods will take place in the shortest possible time while maintaining a high level of safety. In recent years, due to the significant increase in the number of passengers and vehicles on the road and the capacity limitations of transport networks, it has become necessary to use new technologies for intelligent control and traffic management. Intelligent transport systems use advanced technologies in the field of data gathering, information processing, and traffic control to meet current transport needs. To be able to effectively control and manage road traffic, it is necessary to have reliable mathematical models that allow for a faithful representation of the real traffic conditions. Models of this type are usually the basis of complex algorithms used in practice in road traffic control. The application of appropriate models reflecting the behavior of road users contributes to the reduction of congestion, the vehicles travel time on the transport network, fuel consumption and the emissions, which in turn support broadly understood energy savings. The article proposes a model that allows for the estimation of the maximum queue size at the signal-controlled intersection approach (so-called: maximum back-of-queue). This model takes into account the most important traffic characteristics of the vehicles forming this queue. The verification allowed for the conclusion that the proposed model is characterized by high compliance with the actual traffic and road conditions at the intersections with signal controllers located in built-up areas in Poland. The obtained compliance confirms the possibility of using the model for practical applications in calculating the maximum back-of-queue at signal-controlled intersections located in built-up areas in Poland. Full article
(This article belongs to the Special Issue New Perspectives and Challenges in Traffic and Transportation Engineering Supporting Energy Saving in Smart Cities)
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<p>The idea of the modeling of delays and the back-of-queues at signal-controlled intersection approach in a typical period of vehicle service (in the period of no traffic overload). Source: Own research based on [<a href="#B3-energies-14-01204" class="html-bibr">3</a>,<a href="#B4-energies-14-01204" class="html-bibr">4</a>].</p> Full article ">Figure 2
<p>An example of a measuring section adopted as a model for research (Poland, Torun city, intersection approach Czerwona Droga Street/west/): (<b>a</b>). measuring section location; (<b>b</b>). view of the queue of the vehicle on a measuring section; (<b>c</b>). situational plan. Source: Own work based on Open Street map, Google Earth and WZDR System [<a href="#B95-energies-14-01204" class="html-bibr">95</a>].</p> Full article ">Figure 2 Cont.
<p>An example of a measuring section adopted as a model for research (Poland, Torun city, intersection approach Czerwona Droga Street/west/): (<b>a</b>). measuring section location; (<b>b</b>). view of the queue of the vehicle on a measuring section; (<b>c</b>). situational plan. Source: Own work based on Open Street map, Google Earth and WZDR System [<a href="#B95-energies-14-01204" class="html-bibr">95</a>].</p> Full article ">Figure 3
<p>Arrangement of measurement kits along Kamienna Street in Bydgoszcz, Poland (where: 1—camera, 2—power bank, 3—memory card, 4—power supply cable, 5—camera holder, 6—weatherproof enclosure, 7—support sections, 8—clamps).</p> Full article ">Figure 4
<p>Diagram of the process of the volatility of the back-of-queue size in time and the formation of the maximum back-of-queue size in a given signaling cycle <span class="html-italic">i</span>.</p> Full article ">Figure 5
<p>Diagram of the process of forming the remaining queue length in a given signaling cycle <span class="html-italic">i</span> (or a process of forming the initial queue length for the next signaling cycle <span class="html-italic">i +</span> 1).</p> Full article ">Figure 6
<p>Distribution of the number of vehicles from the arrival stream in signaling cycles in a given measurement period taking into account the portion of heavy vehicles.</p> Full article ">Figure 7
<p>Distribution of the number of vehicles in the maximum back-of-queue for a given lane at the approach in individual signaling cycles in a given measurement period (including vehicles <a href="#energies-14-01204-f008" class="html-fig">Figure 8</a>. Starting-up times for the vehicles forming the maximum back-of-queues for a given lane controlled by traffic signal heads with the same signal control parameters, i.e., green signal and cycle length.</p> Full article ">Figure 8
<p>Starting-up times for the vehicles forming the maximum back-of-queues for a given lane controlled by traffic signal heads with the same signal control parameters, i.e., green signal and cycle length.</p> Full article ">Figure 9
<p>Results of the analysis of average values of cumulative time headways in the stream of starting-up vehicles from the maximum back-of-queue after turning on the green signal in a given cycle for subsequent vehicles.</p> Full article ">Figure 10
<p>Results of the correlation analysis of the average values of the intensity of starting vehicles from the maximum queue as a function of the average values of the maximum intensity of the service.</p> Full article ">Figure 11
<p>Results of regression and correlation analysis between empirical values of maximum queue size and theoretical values determined by the proposed model.</p> Full article ">Figure 12
<p>Distribution of errors in estimating the maximum queue size at signal-controlled intersection approach obtained by the proposed model.</p> Full article ">Figure 13
<p>Results of regression and correlation analysis between empirical values of maximum queue size and calibrated theoretical values determined by the proposed model.</p> Full article ">Figure 14
<p>Distribution of errors in estimating the maximum queue size at signal-controlled intersection approach obtained by the proposed model after calibration.</p> Full article ">
24 pages, 6100 KiB  
Article
Multi-Objective Optimisation-Based Design of an Electric Vehicle Cabin Heating Control System for Improved Thermal Comfort and Driving Range
by Ivan Cvok, Igor Ratković and Joško Deur
Energies 2021, 14(4), 1203; https://doi.org/10.3390/en14041203 - 23 Feb 2021
Cited by 16 | Viewed by 4087
Abstract
Modern electric vehicle heating, ventilation, and air-conditioning (HVAC) systems operate in more efficient heat pump mode, thus, improving the driving range under cold ambient conditions. Coupling those HVAC systems with novel heating technologies such as infrared heating panels (IRP) results in a complex [...] Read more.
Modern electric vehicle heating, ventilation, and air-conditioning (HVAC) systems operate in more efficient heat pump mode, thus, improving the driving range under cold ambient conditions. Coupling those HVAC systems with novel heating technologies such as infrared heating panels (IRP) results in a complex system with multiple actuators, which needs to be optimally coordinated to maximise the efficiency and comfort. The paper presents a multi-objective genetic algorithm-based control input allocation method, which relies on a multi-physical HVAC model and a CFD-evaluated cabin airflow distribution model implemented in Dymola. The considered control inputs include the cabin inlet air temperature, blower and radiator fan air mass flows, secondary coolant loop pump speeds, and IRP control settings. The optimisation objective is to minimise total electric power consumption and thermal comfort described by predictive mean vote (PMV) index. Optimisation results indicate that HVAC and IRP controls are effectively decoupled, and that a significant reduction of power consumption (typically from 20% to 30%) can be achieved using IRPs while maintaining the same level of thermal comfort. The previously proposed hierarchical HVAC control strategy is parameterised and extended with a PMV-based controller acting via IRP control inputs. The performance is verified through simulations in a heat-up scenario, and the power consumption reduction potential is analysed for different cabin air temperature setpoints. Full article
(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>System schematic for heat pump (HP) mode.</p> Full article ">Figure 2
<p>Block diagram of cabin thermal system model including airflow distribution model used for Predicted Mean Vote (PMV) evaluation.</p> Full article ">Figure 3
<p>System model used within optimisation framework (<b>a</b>) and driver’s average thermal comfort index (PMV) map in dependence of cabin air temperature and inlet air mass flow rate (<b>b</b>).</p> Full article ">Figure 4
<p>Optimisation framework implemented within ModeFrontier environment.</p> Full article ">Figure 5
<p>Comparison of multi-objective Pareto optimal results for cases with (circles) and without use of infrared heating panels (IRPs) (squares) at different cabin temperatures (<b>a</b>–<b>f</b>).</p> Full article ">Figure 6
<p>Pareto frontiers expressed in terms of HVAC-only power consumption for cases with (circles) and without use of IRPs (squares) at different cabin temperatures (<b>a</b>–<b>f</b>).</p> Full article ">Figure 7
<p>Optimised control inputs corresponding to Pareto frontiers from <a href="#energies-14-01203-f005" class="html-fig">Figure 5</a>a (<b>a</b>–<b>d</b>, <span class="html-italic">T<sub>cab</sub></span> = −10 °C) and <a href="#energies-14-01203-f005" class="html-fig">Figure 5</a>e (<b>e</b>–<b>h</b>, <span class="html-italic">T<sub>cab</sub></span> = 20 °C).</p> Full article ">Figure 8
<p>Optimised IRP control inputs corresponding to Pareto frontiers from <a href="#energies-14-01203-f005" class="html-fig">Figure 5</a>a (<b>a</b>,<b>b</b>, <span class="html-italic">T<sub>cab</sub></span> = −10 °C) and <a href="#energies-14-01203-f005" class="html-fig">Figure 5</a>e (<b>c</b>,<b>d</b>, <span class="html-italic">T<sub>cab</sub></span> = 20 °C).</p> Full article ">Figure 9
<p>Power consumption reduction analysis (<b>c</b>) based on optimisation results (<b>a</b>,<b>b</b>) for the same thermal comfort level and different cabin air temperatures under steady-state conditions.</p> Full article ">Figure 10
<p>Overall hierarchical structure of HVAC control system including decoupled IRP-based PMV controller.</p> Full article ">Figure 11
<p>Simulation results of HVAC-only and HVAC+IRP systems for scenario of constant cabin air temperature target difference of 5 °C.</p> Full article ">Figure 12
<p>Simulation results of HVAC-only and HVAC+IRP systems for scenario of increasing cabin air temperature target difference.</p> Full article ">Figure 13
<p>Comparative heat-up responses of HVAC-only system (solid line) and HVAC+IRP system (dashed line) for target cabin air temperature of 22.5 °C.</p> Full article ">Figure A1
<p>Multi-objective optimisation results for A/C mode.</p> Full article ">
18 pages, 1769 KiB  
Article
Optimal Selection of Metering Points for Power Quality Measurements in Distribution System
by Krzysztof Piatek, Andrzej Firlit, Krzysztof Chmielowiec, Mateusz Dutka, Szymon Barczentewicz and Zbigniew Hanzelka
Energies 2021, 14(4), 1202; https://doi.org/10.3390/en14041202 - 23 Feb 2021
Cited by 13 | Viewed by 2481
Abstract
Quality of power supply in power distribution systems requires continuous measurement using power quality analyzers installed in the grid. The paper reviews the published methods for optimal location of metering points in distribution systems in the context of power quality metering and assessment. [...] Read more.
Quality of power supply in power distribution systems requires continuous measurement using power quality analyzers installed in the grid. The paper reviews the published methods for optimal location of metering points in distribution systems in the context of power quality metering and assessment. Three methods have been selected for detailed analysis and comparative tests. It has been found that utilization of the methods is possible, but their performance varies highly depending on the test grid’s topology. Since the methods rely on the state estimation approach, their performance is strictly related to observability analysis. It has been found that standard observability analysis used for typical state estimation problem yields ambiguous results when applied to power quality assessment. Inherited properties of the selected methods are also analyzed, which allows for the formulation of general recommendations about optimal selection of metering points in a distribution system. Full article
(This article belongs to the Special Issue Selected Papers from The 12th International Conference on Electrical Power Quality and Utilization (EPQU2020))
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<p>Schematic diagram of the test grids: (<b>a</b>) IEEE 37-node test feeder; (<b>b</b>) a typical MV feeder in an urban area.</p> Full article ">Figure 2
<p>Measurement locations selected by the discussed methods: (<b>a</b>) elements selected by the method 1; (<b>b</b>) nodes selected to monitor by method 2.</p> Full article ">Figure 3
<p>Nodes and branches selected for metering by Method 3.</p> Full article ">Figure 4
<p>Application results to IEEE 13-node test feeder: (<b>a</b>) elements selected by the Method 1; (<b>b</b>) nodes selected to monitor by Method 2; (<b>c</b>) nodes for voltage metering and branches for current metering selected by Method 3.</p> Full article ">Figure 5
<p>Application results to IEEE 34-node test feeder: (<b>a</b>) elements selected by the Method 1; (<b>b</b>) nodes selected to monitor by Method 2; (<b>c</b>) nodes for voltage metering and branches for current metering selected by Method 3.</p> Full article ">Figure 6
<p>Results of the method applied to a typical feeder in an urban area: (<b>a</b>) elements selected by the Method 1; (<b>b</b>) nodes selected to monitor by Method 2; (<b>c</b>) nodes for voltage metering and branches for current metering selected by Method 3.</p> Full article ">
18 pages, 1266 KiB  
Article
On Adaptive Moving Average Algorithms for the Application of the Conservative Power Theory in Systems with Variable Frequency
by Daniel dos Santos Mota and Elisabetta Tedeschi
Energies 2021, 14(4), 1201; https://doi.org/10.3390/en14041201 - 23 Feb 2021
Cited by 12 | Viewed by 3126
Abstract
The Conservative Power Theory (CPT) emerged in recent decades as a theoretical framework for coping with harmonically distorted and unbalanced electric networks of ac power systems with a high participation of converter interfaced loads and generation. The CPT measurements are intrinsically linked to [...] Read more.
The Conservative Power Theory (CPT) emerged in recent decades as a theoretical framework for coping with harmonically distorted and unbalanced electric networks of ac power systems with a high participation of converter interfaced loads and generation. The CPT measurements are intrinsically linked to moving averages (MA) over one period of the grid. If the CPT is to be used in a low-inertia isolated-grid scenario, which is subjected to frequency variations, adaptive moving averages (AMA) are necessary. This paper reviews an efficient way of computing MAs and turns it into an adaptive one. It shows that an easily available variable time delay block, from MATLAB, causes steady-state errors in the measurements when the grid frequency varies. A new variable time delay block is, thus, proposed. Nonetheless, natural pulsations in the instantaneous power slip through MAs when the discrete moving average window does not fit perfectly the continuously varying period of the grid. A method consisting of weighing two MAs is reviewed and a new and effective hybrid AMA is proposed. The CPT transducers with the different choices of AMAs are compared via computer simulations of a single-phase voltage source feeding either a linear or a nonlinear load. Full article
(This article belongs to the Special Issue Active Power Filters and Power Quality)
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<p>A MA block built from Equation (<a href="#FD14-energies-14-01201" class="html-disp-formula">14</a>), adapted from [<a href="#B10-energies-14-01201" class="html-bibr">10</a>].</p> Full article ">Figure 2
<p>Inner workings of a LVTD. A double decumulation happens at <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>141</mn> </mrow> </semantics></math> due to a frequency decrease. A missed decumulation happens at <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>142</mn> </mrow> </semantics></math> due to a frequency increase. The circular buffer length is <math display="inline"><semantics> <mrow> <msub> <mi>N</mi> <mi>b</mi> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math>.</p> Full article ">Figure 3
<p>Block diagram representation of the CPT’s active measurements in the discrete time domain.</p> Full article ">Figure 4
<p>Block diagram representation of the CPT’s reactive measurements in the discrete time domain.</p> Full article ">Figure 5
<p>Computer simulation model for testing the CPT transducer with different AMAs.</p> Full article ">Figure 6
<p>Negative steps applied at different instants to the frequency of the source voltage for the RL-load scenario</p> Full article ">Figure 7
<p>Positive steps applied at different instants to the frequency of the source voltage for the DB-load scenario.</p> Full article ">Figure 8
<p>Continuous variation of the source frequency. LVTD in red versus CVTD in blue</p> Full article ">Figure 9
<p>Single AMA with rounded MAW in red versus WAMA in blue</p> Full article ">Figure 10
<p>WAMA in red versus HAMA in blue</p> Full article ">
28 pages, 4332 KiB  
Article
Improvement Effect of Green Remodeling and Building Value Assessment Criteria for Aging Public Buildings
by Yong-Joon Jun, Seung-ho Ahn and Kyung-Soon Park
Energies 2021, 14(4), 1200; https://doi.org/10.3390/en14041200 - 23 Feb 2021
Cited by 12 | Viewed by 2732
Abstract
The Green Remodeling Project under South Korea’s Green New Deal policy is a government-led project intended to strengthen the performance sector directly correlated with energy performance among various elements of improvement applicable to building remodeling by replacing insulation materials, introducing new and renewable [...] Read more.
The Green Remodeling Project under South Korea’s Green New Deal policy is a government-led project intended to strengthen the performance sector directly correlated with energy performance among various elements of improvement applicable to building remodeling by replacing insulation materials, introducing new and renewable energy, introducing high-efficiency equipment, etc., with public buildings taking the lead in green remodeling in order to induce energy efficiency enhancement in private buildings. However, there is an ongoing policy that involves the application of a fragmentary value judgment criterion, i.e., whether to apply technical elements confined to the enhancement of the energy performance of target buildings and the prediction of improvement effects according thereto, thus resulting in the phenomenon of another important value criterion for green remodeling, i.e., the enhancement of the occupant (user) comfort performance of target buildings as one of its purposes, being neglected instead. In order to accurately grasp the current status of these problems and to promote ‘expansion of the value judgment criteria for green remodeling’ as an alternative, this study collected energy usage data of buildings actually used by public institutions and then conducted a total analysis. After that, the characteristics of energy usage were analyzed for each of the groups of buildings classified by year of completion, thereby carrying out an analysis of the correlation between the non-architectural elements affecting the actual energy usage and the actual energy usage data. The correlation between the improvement performance of each technical element and the actual improvement effect was also analyzed, thereby ascertaining the relationship between the direction of major policy strategies and the actual energy usage. As a result of the relationship analysis, it was confirmed that the actual energy usage is more affected by the operating conditions of the relevant building than the application of individual strategic elements such as the performance of the envelope insulation and the performance of the high-efficiency system. In addition, it was also confirmed that the usage of public buildings does not increase in proportion to their aging. The primary goal of reducing energy usage in target buildings can be achieved if public sector (government)-led green remodeling is pushed ahead with in accordance with biased value judgment criteria, just as in the case of a campaign to refrain from operating cooling facilities in aging public buildings. However, it was possible to grasp through the progress of this study that the remodeling may also result in the deterioration of environmental comfort and stability, such as the numerical value of the indoor thermal environment. The results of this study have the significance of providing basic data for pushing ahead with a green remodeling policy in which the value judgment criteria for aging existing public buildings are more expanded, and it is necessary to continue research in such a direction that the quantitative purpose of green remodeling, which is to reduce energy usage in aging public buildings, and its qualitative purpose, which is to enhance their environmental performance for occupants’ comfort, can be mutually balanced and secured at the same time. Full article
(This article belongs to the Section G: Energy and Buildings)
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<p>Research flowchart.</p> Full article ">Figure 2
<p>2010~2015 range scale of Correlation analysis between market price and Annual electric energy fee.</p> Full article ">Figure 3
<p>Visualization of the percentages of the applied technologies for green remodeling in urban regeneration projects in Europe and the United States.</p> Full article ">Figure 4
<p>Percentages of the applied technologies for green remodeling of aging buildings in urban regeneration projects in South Korea.</p> Full article ">Figure 5
<p>Histogram of the number of buildings according to the year of public buildings.</p> Full article ">Figure 6
<p>Insulation standards for each building part in vintage groups.</p> Full article ">Figure 7
<p>(<b>a</b>) Visualization of the bar chart in <a href="#energies-14-01200-t005" class="html-table">Table 5</a>; (<b>b</b>) Visualization of the box plot in <a href="#energies-14-01200-t005" class="html-table">Table 5</a>; Ascertainment of the decreasing trend in the median (kW/m2y) in the amounts of energy usage by year from 2017, as compared to 2015 and 2016</p> Full article ">Figure 8
<p>PMV in the energy saving environment in a public institution building against a blackout.</p> Full article ">Figure 9
<p>A box plot of annual energy consumption per unit area by vintage group in 2019.</p> Full article ">Figure 10
<p>Visualization bar chart of vintage groups by highest energy use among the medians (kW/m<sup>2</sup>y) by vintage group in the amounts of energy usage by facility use in each group in <a href="#energies-14-01200-t009" class="html-table">Table 9</a>.</p> Full article ">Figure 11
<p>A visualization bar chart comparing correlation coefficients between the amount of energy usage and the green remodeling implementation strategy.</p> Full article ">
2 pages, 147 KiB  
Editorial
Special Issue on Global Market for Crude Oil
by Pierre Failler
Energies 2021, 14(4), 1199; https://doi.org/10.3390/en14041199 - 23 Feb 2021
Cited by 4 | Viewed by 2063
Abstract
The dynamic of the world’s crude oil market has drastically changed over the last decade [...] Full article
(This article belongs to the Special Issue Global Market for Crude Oil)
12 pages, 4075 KiB  
Article
Modified SPWM Technique with Zero-Sequence Voltage Injection for a Five-Phase, Three-Level NPC Inverter
by Charles Odeh, Dmytro Kondratenko, Arkadiusz Lewicki and Andrzej Jąderko
Energies 2021, 14(4), 1198; https://doi.org/10.3390/en14041198 - 23 Feb 2021
Cited by 5 | Viewed by 3450
Abstract
This article presents a modified sinusoidal pulse-width modulation (SPWM) scheme for a five-phase, three-level neutral-point-clamped inverter. The modulation scheme deploys a modified min–max function to inject the zero-sequence components into the reference modulating signals; hence enabling the effective utilization of the DC-link voltage. [...] Read more.
This article presents a modified sinusoidal pulse-width modulation (SPWM) scheme for a five-phase, three-level neutral-point-clamped inverter. The modulation scheme deploys a modified min–max function to inject the zero-sequence components into the reference modulating signals; hence enabling the effective utilization of the DC-link voltage. Balanced split-input DC-link voltages were achieved through further incorporation of adjustable voltage-dependent variables into the reference signals. The dynamic performance of the control approach is demonstrated through simulations and experiments on a laboratory inverter prototype; the results are well presented. Full article
(This article belongs to the Special Issue Control and Modeling of Power Converters and Inverters)
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<p>(<b>a</b>) Five-phase, three-level inverter power circuit; (<b>b</b>) proposed sinusoidal pulse width modulation (SPWM) control block diagram.</p> Full article ">Figure 2
<p>DC-link capacitor voltage control.</p> Full article ">Figure 3
<p>SPWM modulation signals: (<b>a</b>) absence of neutral voltage balancing; (<b>b</b>) neutral voltage balancing in place.</p> Full article ">Figure 4
<p>Simulated output voltage and current waveforms for the output power factor of 0.8. (<b>a</b>) Neutral-point phase voltages; (<b>b</b>) line voltages and currents.</p> Full article ">Figure 5
<p>DC-link capacitor voltages’ variations with and without the neutral-point voltage balancing scheme.</p> Full article ">Figure 6
<p>Load currents and DC-link capacitor voltage profiles under power factor variations. (<b>a</b>) Line current waveforms; (<b>b</b>) DC-link capacitor voltages.</p> Full article ">Figure 7
<p>The a, b, c, d, and e stator currents and their corresponding fundamental and third harmonic d-q components (<b>a</b>) without third harmonic injection and (<b>b</b>) with third harmonic injection.</p> Full article ">Figure 8
<p>FFT analyses of the SPWM-controlled inverter’s phase current with DC-link voltage balancing.</p> Full article ">Figure 9
<p>A laboratory prototype of the five-phase, three-level neutral-point-clamped inverter.</p> Full article ">Figure 10
<p>Experimental output voltage waveforms. (<b>a</b>) Neutral-point phase voltages; (<b>b</b>) line voltages.</p> Full article ">Figure 11
<p>Experimental output voltage waveforms with 5x zoomed area. (<b>a</b>) Neutral-point phase voltages; (<b>b</b>) line voltages.</p> Full article ">Figure 12
<p>Experimental output currents’ waveforms and their corresponding FFT analyses. (<b>a</b>) Inverter output load currents with third harmonic injection; (<b>b</b>) FFT analysis of a load current waveform with third harmonic injection; (<b>c</b>) inverter output load currents without third harmonic injection; (<b>d</b>) FFT analysis of a load current waveform without third harmonic injection.</p> Full article ">Figure 13
<p>Experimental dynamic response of the inverter for step changes in the modulation index. (<b>a</b>) Load current waveform when modulation index was changed from 0.6 to 1; (<b>b</b>) Load current waveform when modulation index was changed from 1 to 0.6.</p> Full article ">Figure 14
<p>Experimental dynamic response of the inverter for step changes in the modulation index. (<b>a</b>) Load current and voltage waveforms when modulation index was changed from 0.6 to 1; (<b>b</b>) Load current and voltage waveforms when modulation index was changed from 1 to 0.6.</p> Full article ">
15 pages, 509 KiB  
Review
Molten Salts for Sensible Thermal Energy Storage: A Review and an Energy Performance Analysis
by Adrián Caraballo, Santos Galán-Casado, Ángel Caballero and Sara Serena
Energies 2021, 14(4), 1197; https://doi.org/10.3390/en14041197 - 23 Feb 2021
Cited by 118 | Viewed by 10701
Abstract
A comprehensive review of different thermal energy storage materials for concentrated solar power has been conducted. Fifteen candidates were selected due to their nature, thermophysical properties, and economic impact. Three key energy performance indicators were defined in order to evaluate the performance of [...] Read more.
A comprehensive review of different thermal energy storage materials for concentrated solar power has been conducted. Fifteen candidates were selected due to their nature, thermophysical properties, and economic impact. Three key energy performance indicators were defined in order to evaluate the performance of the different molten salts, using Solar Salt as a reference for low and high temperatures. The analysis provided evidence that nitrate-based materials are the best choice for the former and chloride-based materials are best for the latter instead of fluoride and carbonate-based candidates, mainly due to their low cost. Full article
(This article belongs to the Section D: Energy Storage and Application)
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<p>Nitrate-based TES materials KPIs comparison (Solar Salt = 1).</p> Full article ">Figure 2
<p>Chloride-based TES materials KPIs comparison (Solar Salt = 1).</p> Full article ">
18 pages, 6545 KiB  
Article
An Innovative Metaheuristic Strategy for Solar Energy Management through a Neural Networks Framework
by Hossein Moayedi and Amir Mosavi
Energies 2021, 14(4), 1196; https://doi.org/10.3390/en14041196 - 23 Feb 2021
Cited by 45 | Viewed by 4092
Abstract
Proper management of solar energy as an effective renewable source is of high importance toward sustainable energy harvesting. This paper offers a novel sophisticated method for predicting solar irradiance (SIr) from environmental conditions. To this end, an efficient metaheuristic technique, namely electromagnetic field [...] Read more.
Proper management of solar energy as an effective renewable source is of high importance toward sustainable energy harvesting. This paper offers a novel sophisticated method for predicting solar irradiance (SIr) from environmental conditions. To this end, an efficient metaheuristic technique, namely electromagnetic field optimization (EFO), is employed for optimizing a neural network. This algorithm quickly mines a publicly available dataset for nonlinearly tuning the network parameters. To suggest an optimal configuration, five influential parameters of the EFO are optimized by an extensive trial and error practice. Analyzing the results showed that the proposed model can learn the SIr pattern and predict it for unseen conditions with high accuracy. Furthermore, it provided about 10% and 16% higher accuracy compared to two benchmark optimizers, namely shuffled complex evolution and shuffled frog leaping algorithm. Hence, the EFO-supervised neural network can be a promising tool for the early prediction of SIr in practice. The findings of this research may shed light on the use of advanced intelligent models for efficient energy development. Full article
(This article belongs to the Special Issue Modeling, Design, Development and Testing for Solar System)
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<p>A schematic view of solar radiation and solar energy (SE) production.</p> Full article ">Figure 2
<p>The variation of the solar irradiance (SIr) over 29 September 2016.</p> Full article ">Figure 3
<p>Scattering plots of the SIr versus input parameters (<b>a</b>) T, (<b>b</b>) BP, (<b>c</b>) H, (<b>d</b>) WD, and (<b>e</b>) WS.</p> Full article ">Figure 3 Cont.
<p>Scattering plots of the SIr versus input parameters (<b>a</b>) T, (<b>b</b>) BP, (<b>c</b>) H, (<b>d</b>) WD, and (<b>e</b>) WS.</p> Full article ">Figure 4
<p>The creation of a new electromagnetic particle (EMP).</p> Full article ">Figure 5
<p>Optimizing the effect of electromagnetic field optimization (EFO) parameters including (<b>a</b>) N<sub>Pop</sub>, (<b>b</b>) R_rate, (<b>c</b>) Ps_rate, (<b>d</b>) P_field, and (<b>e</b>) N_field.</p> Full article ">Figure 5 Cont.
<p>Optimizing the effect of electromagnetic field optimization (EFO) parameters including (<b>a</b>) N<sub>Pop</sub>, (<b>b</b>) R_rate, (<b>c</b>) Ps_rate, (<b>d</b>) P_field, and (<b>e</b>) N_field.</p> Full article ">Figure 6
<p>The error analysis in terms of (<b>a</b>,<b>c</b>,<b>e</b>) magnitude and (<b>b</b>,<b>d</b>,<b>f</b>) frequency for the EFO-multi-layer perceptron (MLP), shuffled complex evolution (SCE)-MLP, and shuffled frog leaping algorithm (SFLA)-MLP, respectively.</p> Full article ">
19 pages, 5943 KiB  
Article
Model Predictive Control Strategies to Activate the Energy Flexibility for Zones with Hydronic Radiant Systems
by Ali Saberi Derakhtenjani and Andreas K. Athienitis
Energies 2021, 14(4), 1195; https://doi.org/10.3390/en14041195 - 23 Feb 2021
Cited by 7 | Viewed by 2466
Abstract
This paper presents control strategies to activate energy flexibility for zones with radiant heating systems in response to changes in electricity prices. The focus is on zones with radiant floor heating systems for which the hydronic pipes are located deep in the concrete [...] Read more.
This paper presents control strategies to activate energy flexibility for zones with radiant heating systems in response to changes in electricity prices. The focus is on zones with radiant floor heating systems for which the hydronic pipes are located deep in the concrete and, therefore, there is a significant thermal lag. A perimeter zone test-room equipped with a hydronic radiant floor system in an environmental chamber is used as a case study. A low order thermal network model for the perimeter zone, validated with experimental measurements, is utilized to study various control strategies in response to changes in the electrical grid price signal, including short term (nearly reactive) changes of the order of 10–15 min notice. An index is utilized to quantify the building energy flexibility with the focus on peak demand reduction for specific periods of time when the electricity prices are higher than usual. It is shown that the developed control strategies can aid greatly in enhancing the zone energy flexibility and minimizing the cost of electricity and up to 100% reduction in peak power demand and energy consumption is attained during the high-price and peak-demand periods, while maintaining acceptable comfort conditions. Full article
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<p>Schematic illustration of Building Energy Flexibility Index (BEFI).</p> Full article ">Figure 2
<p>Second-order model thermal network of floor heating system.</p> Full article ">Figure 3
<p>Radiant floor piping before (<b>left</b>), during (<b>middle</b>) and after (<b>right</b>) pouring the concrete.</p> Full article ">Figure 4
<p>Schematic of Solar Simulator-Environmental Chamber (SSEC) with Perimeter Zone Test Cell (PZTC) and radiant floor.</p> Full article ">Figure 5
<p>Second-order model versus experimental measurements and model error.</p> Full article ">Figure 6
<p>Ambient temperature profile.</p> Full article ">Figure 7
<p>Reference conditions and power price for floor surface temperature setpoint of 24 °C.</p> Full article ">Figure 8
<p>Reactive response to sudden increase in the price signal.</p> Full article ">Figure 9
<p>Reactive responses to sudden increase in the price signal.</p> Full article ">Figure 10
<p>Example of dynamic price signal considered.</p> Full article ">Figure 11
<p>Application of the nearly reactive strategy to deal with the changing price signal.</p> Full article ">Figure 12
<p>BEFI during high price signal periods.</p> Full article ">Figure 13
<p>Predictive strategy for price signal #1.</p> Full article ">Figure 14
<p>Predictive strategy for price signal #2.</p> Full article ">Figure 15
<p>Predictive strategy for price signal #3.</p> Full article ">Figure 16
<p>Unexpected increase in the price signal #2.</p> Full article ">Figure 17
<p>Unexpected change in the price signal.</p> Full article ">Figure 18
<p>Modified setpoint to correct the heating load.</p> Full article ">Figure 19
<p>Predictive strategy for dynamic energy price signal.</p> Full article ">
28 pages, 5906 KiB  
Article
The Innovative FlexPlan Grid-Planning Methodology: How Storage and Flexible Resources Could Help in De-Bottlenecking the European System
by Gianluigi Migliavacca, Marco Rossi, Dario Siface, Matteo Marzoli, Hakan Ergun, Raúl Rodríguez-Sánchez, Maxime Hanot, Guillaume Leclerq, Nuno Amaro, Aleksandr Egorov, Jawana Gabrielski, Björn Matthes and Andrei Morch
Energies 2021, 14(4), 1194; https://doi.org/10.3390/en14041194 - 23 Feb 2021
Cited by 25 | Viewed by 5075
Abstract
The FlexPlan Horizon2020 project aims at establishing a new grid-planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the [...] Read more.
The FlexPlan Horizon2020 project aims at establishing a new grid-planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the Clean Energy for all Europeans regulatory package of the European Commission. FlexPlan creates a new innovative grid-planning tool whose ambition is to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of the best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030, 2040, 2050), incorporation of a full range of cost–benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly renewable energy sources (RES) and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. FlexPlan will end up formulating guidelines for regulators and planning offices of system operators by indicating to what extent system flexibility can contribute to reducing overall system costs (operational + investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper provides a complete description of the modelling features of the planning tool and pre-processor and provides the first results of their application in small-scale scenarios. Full article
(This article belongs to the Special Issue Verifying the Targets—Selected Papers from the 55th International Universities Power Engineering Conference (UPEC 2020))
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<p>Building blocks, input parameters and output parameters of the planning tool.</p> Full article ">Figure 2
<p>Reliability modelling within the FlexPlan model.</p> Full article ">Figure 3
<p>Schematic view of the results of the Monte Carlo scenario generation [<a href="#B15-energies-14-01194" class="html-bibr">15</a>].</p> Full article ">Figure 4
<p>Conceptual scheme of the application on Benders decomposition.</p> Full article ">Figure 5
<p>Interaction between planning tool and pre-processor.</p> Full article ">Figure 6
<p>Power transfer distribution factor (PTDF) analysis approach.</p> Full article ">Figure 7
<p>Relationship between the saturation of the congested line and other lines.</p> Full article ">Figure 8
<p>Steps by the flexibility candidate pre-processor.</p> Full article ">Figure 9
<p>Distributed Energy (DE) scenario: evolution of installed capacities per technology, from 2030 to 2050.</p> Full article ">Figure 10
<p>Methodology for spatial distribution of wind power plants in France.</p> Full article ">Figure 11
<p>Normalised hourly wind power generation potential from 1980 to 2019 in selected European countries.</p> Full article ">Figure 12
<p>Variability in historical solar, wind onshore and hydro run-of-river as well as load capacity factors.</p> Full article ">Figure 13
<p>Schematic overview of the process generating meteorological variants for the Monte Carlo approach.</p> Full article ">Figure 14
<p>Italian test system used for proof-of-concept validation.</p> Full article ">Figure 15
<p>Total system cost for flex (<b>left</b>) and non-flex (<b>right</b>) cases.</p> Full article ">Figure 16
<p>Optimal transmission grid layout for flex and non-flex cases.</p> Full article ">
11 pages, 780 KiB  
Article
Integrated Electric Vehicle Shunt Current Sensing System for Concurrent Revenue Metering and Detection of DC Injection
by Olga Mironenko, Garrett Ejzak and Willett Kempton
Energies 2021, 14(4), 1193; https://doi.org/10.3390/en14041193 - 23 Feb 2021
Cited by 3 | Viewed by 2790
Abstract
Certified electric vehicle power converters can inject DC current into the AC grid if they fail. Verification of DC injection by electric vehicle supply equipment can be a cost-effective extra measure to ensure power quality from a variety of plugged-in electric vehicles. As [...] Read more.
Certified electric vehicle power converters can inject DC current into the AC grid if they fail. Verification of DC injection by electric vehicle supply equipment can be a cost-effective extra measure to ensure power quality from a variety of plugged-in electric vehicles. As electric vehicle supply equipment typically performs high-accuracy revenue energy metering, we propose that measurement of AC current and DC injection with a single sensor is the most economically efficient design. This article presents an integrated shunt current sensing system with separation of AC and DC signals for concurrent revenue metering and DC injection detection. It also shows how the combined sensor is integrated into 19.2 kW single-phase electric vehicle supply equipment, and outlines how the design would be extended to 100 kW three-phase electric vehicle supply equipment. The prototype can detect DC injection of ?400 mA in an AC current up to 80 A in accordance with the IEEE 1547-2018 standard. The prototype can also conduct revenue metering within the 1.0 accuracy class. The prototype does not have high power dissipation at high currents typical for shunt systems. Finally, the prototype is less costly than common electric vehicle supply equipment revenue metering CT systems with the addition of the popular Hall-effect sensor. Full article
(This article belongs to the Special Issue Advanced Electric Vehicle Techniques)
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<p>Current sensing single-phase system block diagram.</p> Full article ">Figure 2
<p>Setting the DC injection alarm threshold for positive (right line) and negative (left line) DC injection.</p> Full article ">
15 pages, 1125 KiB  
Article
Assessment of Cow Dung Pellets as a Renewable Solid Fuel in Direct Combustion Technologies
by Aneta Szymajda, Grażyna Łaska and Magdalena Joka
Energies 2021, 14(4), 1192; https://doi.org/10.3390/en14041192 - 23 Feb 2021
Cited by 28 | Viewed by 7635
Abstract
Recently, biomass application as a renewable energy source is increasing worldwide. However, its availability differs in dependence on the location and climate, therefore, agricultural residues as cow dung (CD) are being considered to supply heat and/or power installation. This paper aims at a [...] Read more.
Recently, biomass application as a renewable energy source is increasing worldwide. However, its availability differs in dependence on the location and climate, therefore, agricultural residues as cow dung (CD) are being considered to supply heat and/or power installation. This paper aims at a wide evaluation of CD fuel properties and its prospect to apply in the form of pellets to direct combustion installations. Therefore, the proximate, ultimate composition and calorific value were analyzed, then pelletization and combustion tests were performed, and the ash characteristics were tested. It was found that CD is a promising source of bioenergy in terms of LHV (16.34 MJ·kg?1), carbon (44.24%), and fixed carbon (18.33%) content. During pelletization, CD showed high compaction properties and at a moisture content of 18%,and the received pellets’ bulk density reached ca. 470 kg·m?3 with kinetic durability of 98.7%. While combustion, in a fixed grate 25 kW boiler, high emissions of CO, SO2, NO, and HCl were observed. The future energy sector might be based on biomass and this work shows a novel approach of CD pellets as a potential source of renewable energy available wherever cattle production is located. Full article
(This article belongs to the Special Issue Thermal Analysis of Biomass Energy Production Process)
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<p>Share of biomass sources for energy purposes in Poland [<a href="#B5-energies-14-01192" class="html-bibr">5</a>].</p> Full article ">Figure 2
<p>Systematic scheme of the research.</p> Full article ">Figure 3
<p>The influence of analytical moisture content on the low heating value (LHV).</p> Full article ">
22 pages, 4722 KiB  
Article
A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification
by Renko Buhr, Hassan Kassem, Gerald Steinfeld, Michael Alletto, Björn Witha and Martin Dörenkämper
Energies 2021, 14(4), 1191; https://doi.org/10.3390/en14041191 - 23 Feb 2021
Cited by 3 | Viewed by 3469
Abstract
In wind energy site assessment, one major challenge is to represent both the local characteristics as well as general representation of the wind climate on site. Micro-scale models (e.g., Reynolds-Averaged-Navier-Stokes (RANS)) excel in the former, while meso-scale models (e.g., Weather Research and Forecasting [...] Read more.
In wind energy site assessment, one major challenge is to represent both the local characteristics as well as general representation of the wind climate on site. Micro-scale models (e.g., Reynolds-Averaged-Navier-Stokes (RANS)) excel in the former, while meso-scale models (e.g., Weather Research and Forecasting (WRF)) in the latter. This paper presents a fast approach for meso–micro downscaling to an industry-applicable computational fluid dynamics (CFD) modeling framework. The model independent postprocessing tool chain is applied using the New European Wind Atlas (NEWA) on the meso-scale and THETA on the micro-scale side. We adapt on a previously developed methodology and extend it using a micro-scale model including stratification. We compare a single- and multi-point downscaling in critical flow situations and proof the concept on long-term mast data at Rödeser Berg in central Germany. In the longterm analysis, in respect to the pure meso-scale results, the statistical bias can be reduced up to 45% with a single-point downscaling and up to 107% (overcorrection of 7%) with a multi-point downscaling. We conclude that single-point downscaling is vital to combine meso-scale wind climate and micro-scale accuracy. The multi-point downscaling is further capable to include wind shear or veer from the meso-scale model into the downscaled velocity field. This adds both, accuracy and robustness, by minimal computational cost. The new introduction of stratification in the micro-scale model provides a marginal difference for the selected stability conditions, but gives a prospect on handling stratification in wind energy site assessment for future applications. Full article
(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)
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<p>Two examples of setups of downscaling of meso-scale data with a micro-scale model: the size of the domain of the micro-scale model is given in blue (inflow domain with smoothed topography) and red (region of interest) colors, the grid below exemplary illustrates the grid of the meso-scale model. In the setup on the left-hand side, the small micro-scale model domain is within one grid cell of the meso-scale model and therefore only one reference point can be used. With larger computational power, the domain of the micro-scale simulation can be increased and the meso-scale model resolution can become finer (right). Therefore, to use several reference points becomes possible.</p> Full article ">Figure 2
<p>Terrain height (<b>a</b>) and forest heights (<b>b</b>) of the Rödeser Berg site close to Kassel in central Germany. The red dot marks the position of the met mast at the hill top (MM200), the orange dot the second met mast (MM140). (<b>c</b>,<b>d</b>) show the respective wind roses during the measurement period. (Terrain and forest height data source (ALS data): Hessische Verwaltung für Bodenmanagement und Geoinformation).</p> Full article ">Figure 3
<p>Snapshots from the micro-scale simulation grid. (<b>a</b>) top view on the southwestern section of the domain, (<b>b</b>) sideview on the central eastern part of the domain and (<b>c</b>) closeup on the left hill in (<b>b</b>).</p> Full article ">Figure 4
<p>Stability range at Rödeser Berg (meso-scale model data) for the time window of the measurement campaign. The colors depict the stability, which is assumed by the downscaling method, when stability is applied. convective in red, stable in blue and neutral in green.</p> Full article ">Figure 5
<p>Different characteristic profiles in comparison: Average profiles of N evenly distributed profiles were extracted from the micro-scale simulations, and an absolute Bias was calculated, for both wind speed and wind direction (average between 0 and 200 m, 5 m steps), compared to 961 profiles (3 km by 3 km with profiles every 100 m).</p> Full article ">Figure 6
<p>Spatial standard deviation of wind direction (red) and spatial average wind speed (blue) both changing with time (30 min resolution) in October 2012 at Rödeser Berg. Based on the New European Wind Atlas (NEWA) data.</p> Full article ">Figure 7
<p>Comparison between no interpolation (<b>a</b>), bi-linear method (BILIN) (<b>b</b>), inverse distance weighting (IDW) (<b>c</b>) and squared inverse distance weighting (ISDW) (<b>d</b>) interpolation schemes described in <a href="#sec2-energies-14-01191" class="html-sec">Section 2</a>. The stars represent the reference positions, e.g., meso-scale grid cells. Metmasts at circle (MM200) and triangle (MM140). Neutral stratification assumed.</p> Full article ">Figure 8
<p>Comparison of different wind roses at Rödeser Berg: (<b>a</b>) wind rose from meso-scale data of NEWA database (grid point closest to MM200), (<b>b</b>) wind rose from meso-scale data of NEWA (grid point closest to MM140), (<b>c</b>) single point downscaled data based on meso-scale data of (<b>a</b>) (at MM200, neutral micro-scale CFD only) (<b>d</b>) single point downscaled data based on meso-scale data of (<b>b</b>) (at MM140, neutral micro-scale CFD only).</p> Full article ">Figure 9
<p>Scatter plots between measurements and downscaled data: (<b>a</b>) MM200 downscaled data, and (<b>b</b>) MM200 corrected (based on regression at MM140; exemplary for single point downscaling).</p> Full article ">Figure 10
<p>Corrected wind roses from single point downscaling at MM200 (<b>a</b>) and MM140 (<b>b</b>).</p> Full article ">Figure 11
<p>Wind roses after correction and downscaling based on multiple meso-scale grid points(four) for the two met mast locations on hill top (MM200-(<b>a</b>)) and southwest of the hill (MM140-(<b>b</b>)).</p> Full article ">
20 pages, 8239 KiB  
Article
Strength Tests of Hardened Cement Slurries for Energy Piles, with the Addition of Graphite and Graphene, in Terms of Increasing the Heat Transfer Efficiency
by Tomasz Sliwa, Aneta Sapińska-Śliwa, Tomasz Wysogląd, Tomasz Kowalski and Izabela Konopka
Energies 2021, 14(4), 1190; https://doi.org/10.3390/en14041190 - 23 Feb 2021
Cited by 8 | Viewed by 2886
Abstract
The development of civilization, and subsequent increase in the number of new buildings, poses engineering problems which are progressively more difficult to solve, especially in the field of geotechnics and geoengineering. When designing new facilities, particular attention should be paid to environmental aspects, [...] Read more.
The development of civilization, and subsequent increase in the number of new buildings, poses engineering problems which are progressively more difficult to solve, especially in the field of geotechnics and geoengineering. When designing new facilities, particular attention should be paid to environmental aspects, and thus any new facility should be a passive building, fully self-sufficient in energy. The use of load-bearing energy piles could be a solution. This article presents research on the cement slurry formulas with the addition of graphite and graphene, that can be used as a material for load-bearing piles. The proposed solution is to introduce U-tubes into the pile to exchange heat with the rock mass (the so-called energy piles). A comparison of four slurry formulas is presented: the first one consisting mainly of cement (CEM I), graphite, and water, and the remaining three with different percentages of graphene relative to the weight of dry cement. The results could contribute to the industrial application of those formulas in the future. Full article
(This article belongs to the Special Issue Advancements in Thermal and Energy Geotechnics)
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<p>(<b>a</b>) Piling machine (<b>b</b>) Auger.</p> Full article ">Figure 2
<p>Installation diagram with ground source heat pumps (GSHPs) and BHEs, (<b>a</b>) two BHEs with double supply U-tubes, connected to the evaporator or GSHP condenser inside the building, (<b>b</b>) visualization of a building with GSHP and BHEs [<a href="#B13-energies-14-01190" class="html-bibr">13</a>].</p> Full article ">Figure 3
<p>(<b>a</b>) The reinforcement of the energy pile, (<b>b</b>) the insertion of the reinforcement in the form of a basket equipped with a U-tube system into the borehole [<a href="#B52-energies-14-01190" class="html-bibr">52</a>].</p> Full article ">Figure 4
<p>An example of an energy pile, (<b>a</b>) the interior of the pile reinforcement with arranged pipes [<a href="#B53-energies-14-01190" class="html-bibr">53</a>], (<b>b</b>) pipe arrangement in a reinforcing structure (slurry wall) [<a href="#B54-energies-14-01190" class="html-bibr">54</a>].</p> Full article ">Figure 5
<p>Laying the heat exchanger pipes in the load-bearing pile structure [<a href="#B55-energies-14-01190" class="html-bibr">55</a>].</p> Full article ">Figure 6
<p>Execution of the energy piles in Krakow (the building of the National Archives), (<b>a</b>) reinforcement of the energy pile with an I-beam with a welded circular element, (<b>b</b>) execution of the energy pile.</p> Full article ">Figure 7
<p>(<b>a</b>) A photo of the energy piles layout for the building of the National Archives in Krakow, and (<b>b</b>) a photo with a thermal imaging camera.</p> Full article ">Figure 8
<p>(<b>a</b>) and (<b>b</b>) examples of individual energy piles at the construction site of the National Archives in Krakow (a thermal image).</p> Full article ">Figure 9
<p>The molds for the beams.</p> Full article ">Figure 10
<p>An example of a standard beam subjected to strength testing.</p> Full article ">Figure 11
<p>Hydraulic press Servo-Plus Evolution E183.</p> Full article ">Figure 12
<p>The relationship between the strength of cement samples (S) and the graphene percentage (G).</p> Full article ">Figure 13
<p>An example of a prepared round samples subjected to thermal conductivity testing.</p> Full article ">Figure 14
<p>FOX 50: thermal conductivity measurement apparatus.</p> Full article ">Figure 15
<p>The relationship between the thermal conductivity (T) and the graphene percentage (G).</p> Full article ">
14 pages, 2613 KiB  
Communication
DEAP Actuator Composed of a Soft Pneumatic Spring Bias with Pressure Signal Sensing
by Jakub Bernat and Jakub Kołota
Energies 2021, 14(4), 1189; https://doi.org/10.3390/en14041189 - 23 Feb 2021
Cited by 5 | Viewed by 2295
Abstract
Dielectric electroactive actuators are novel and significant smart actuators. The crucial aspect of construction of these devices is the bias mechanism. The current literature presents three main types of biases used in the construction of the DEAP actuators. In these solutions, the bias [...] Read more.
Dielectric electroactive actuators are novel and significant smart actuators. The crucial aspect of construction of these devices is the bias mechanism. The current literature presents three main types of biases used in the construction of the DEAP actuators. In these solutions, the bias is caused by the action of a spring, a force of a permanent magnet or an applied mass. The purpose of this article is to present a novel type of DEAP bias mechanism using soft pneumatic spring. In contrast to the solutions presented so far, the soft pneumatic spring has been equipped with a sensor that measures the variable pressure of its inner chamber. We performed the modeling process of a soft pneumatic spring with the finite element method to predict its mechanical behavior. Furthermore, a prototype of the soft spring was molded and used to construct a dielectric electroactive polymer actuator. The principle of operation has been confirmed by the experiments with measurement of static and dynamics characteristics. The presented device can be used to control systems with an additional pressure-sensing feedback. Full article
(This article belongs to the Special Issue Bio-Inspired Materials for Energy and Environmental Applications)
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<p>Example of biases in DEAP actuators: Membrane with spring bias (<b>a</b>); membrane with permanent magnet bias (<b>b</b>); membrane with mass bias (<b>c</b>).</p> Full article ">Figure 1 Cont.
<p>Example of biases in DEAP actuators: Membrane with spring bias (<b>a</b>); membrane with permanent magnet bias (<b>b</b>); membrane with mass bias (<b>c</b>).</p> Full article ">Figure 2
<p>The concept of soft pneumatic bias: Unbiased membrane (<b>a</b>); biased membrane with spring without voltage (<b>b</b>); biased membrane with spring with voltage (<b>c</b>).</p> Full article ">Figure 3
<p>The FEM mesh with fixed point and load force (the internal pressure inside the chamber is not visible) (<b>a</b>), and the dimensions of the soft pneumatic spring model alone (<b>b</b>).</p> Full article ">Figure 4
<p>The results of simulations for the FEM model of pneumatic spring without a DEAP membrane for two cases: without a load force (<b>a</b>) and with a load force (<b>b</b>).</p> Full article ">Figure 5
<p>The soft pneumatic spring molded from silicon.</p> Full article ">Figure 6
<p>Comparison of force–pressure characteristics for the FEM simulation and three different spring measurements.</p> Full article ">Figure 7
<p>The DEAP actuator with soft pneumatic spring bias.</p> Full article ">Figure 8
<p>The laboratory setup of the DEAP actuator measurement.</p> Full article ">Figure 9
<p>Example of the voltage transient applied to measure the step response of pressure and distance.</p> Full article ">Figure 10
<p>Comparison of distance and pressure of example step responses for voltages from 2 to <math display="inline"><semantics> <mrow> <mn>6.75</mn> </mrow> </semantics></math> <math display="inline"><semantics> <mi mathvariant="normal">k</mi> </semantics></math><math display="inline"><semantics> <mi mathvariant="normal">V</mi> </semantics></math>: Pressure (<b>a</b>,<b>c</b>,<b>e</b>) and normalized distance (<b>b</b>,<b>d</b>,<b>f</b>). Trial numbers: 1 (<b>a</b>,<b>b</b>), 2 (<b>c</b>,<b>d</b>), 3 (<b>e</b>,<b>f</b>).</p> Full article ">Figure 11
<p>Comparison of responses for sinus voltage excitation with different amplitudes for a large frequency range.</p> Full article ">Figure 12
<p>Comparison of responses for sinus voltage excitation with different amplitudes for frequencies around the resonance.</p> Full article ">Figure 13
<p>Comparison of the ratio <math display="inline"><semantics> <msub> <mi>R</mi> <mi>i</mi> </msub> </semantics></math> for sinus voltage excitation with different amplitudes for low frequencies.</p> Full article ">
16 pages, 694 KiB  
Article
Solar Prosumers in the German Energy Transition: A Multi-Level Perspective Analysis of the German ‘Mieterstrom’ Model
by Raphael Moser, Chun Xia-Bauer, Johannes Thema and Florin Vondung
Energies 2021, 14(4), 1188; https://doi.org/10.3390/en14041188 - 23 Feb 2021
Cited by 18 | Viewed by 6303
Abstract
The expansion of photovoltaics in German cities has so far fallen short of expectations. The concept of ‘tenant electricity’ (‘Mieterstrom’ in German), in which tenants of a building are supplied with solar power produced on site, offers great potential here. A [...] Read more.
The expansion of photovoltaics in German cities has so far fallen short of expectations. The concept of ‘tenant electricity’ (‘Mieterstrom’ in German), in which tenants of a building are supplied with solar power produced on site, offers great potential here. A study on behalf of the German Federal Ministry for Economic Affairs and Energy estimated the number of tenant households with good conditions for solar tenant electricity at 3.8 million. At the same time, the federal tenant electricity promotion scheme has been in place since 2017, but only about 1% of the annual budget has been claimed. The aim of this study is to identify the barriers for and drivers of diffusion of the tenant electricity model. To this end, a qualitative document analysis and a range of semi-structured expert interviews have been conducted. The theoretical framework used to guide the analysis is the multi-level perspective. The main barrier found for tenant electricity diffusion is the legal framework on the regime level, which also leads to high transaction costs of implementing tenant electricity. A social barrier is the inertia of some residents to actively concern themselves with their electricity supply and switch to a tenant electricity contract. Among its drivers are long-term trends such as the increasing electricity demand in urban areas, technical developments like blockchain technology and the increasing deployment of smart meters, and the EU Renewable Energy Directive. As long as the restrictive legal framework prevails, the further diffusion of tenant electricity will remain limited. Full article
(This article belongs to the Special Issue Selected Papers from the SDEWES 2020 Conference on Sustainable Development of Energy, Water, and Environment Systems)
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<p>Transition of the energy system with tenant electricity; the length of the arrows refers to the time, the width to the intensity of the influence exerted; Source: Own illustration, based on [<a href="#B50-energies-14-01188" class="html-bibr">50</a>].</p> Full article ">
16 pages, 4197 KiB  
Article
Impact of Actual Weather Datasets for Calibrating White-Box Building Energy Models Base on Monitored Data
by Vicente Gutiérrez González, Germán Ramos Ruiz and Carlos Fernández Bandera
Energies 2021, 14(4), 1187; https://doi.org/10.3390/en14041187 - 23 Feb 2021
Cited by 12 | Viewed by 3975
Abstract
The need to reduce energy consumption in buildings is an urgent task. Increasing the use of calibrated building energy models (BEM) could accelerate this need. The calibration process of these models is a highly under-determined problem that normally yields multiple solutions. Among the [...] Read more.
The need to reduce energy consumption in buildings is an urgent task. Increasing the use of calibrated building energy models (BEM) could accelerate this need. The calibration process of these models is a highly under-determined problem that normally yields multiple solutions. Among the uncertainties of calibration, the weather file has a primary position. The objective of this paper is to provide a methodology for selecting the optimal weather file when an on-site weather station with local sensors is available and what is the alternative option when it is not and a mathematically evaluation has to be done with sensors from nearby stations (third-party providers). We provide a quality assessment of models based on the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) and the Square Pearson Correlation Coefficient (R2). The research was developed on a control experiment conducted by Annex 58 and a previous calibration study. This is based on the results obtained with the study case based on the data provided by their N2 house. Full article
(This article belongs to the Special Issue Energy Efficiency and Indoor Environment Quality)
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<p>Plan and external views of the N2 house. Holzkirchen, Germany.</p> Full article ">Figure 2
<p>Generic process diagram for achieving calibration mode.</p> Full article ">Figure 3
<p>Calibration environment with a genetic algorithm. The coefficient of variation of the root mean square error (CV(RMSE)) and the genetic algorithm non-dominated sorting genetic algorithm (NSGA-II) [<a href="#B9-energies-14-01187" class="html-bibr">9</a>].</p> Full article ">Figure 4
<p>The simulation result of the base model with all the proposed weather files. CV(RMSE) Index.</p> Full article ">Figure 5
<p>The simulation result of the base model with all the proposed weather files. R<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math> Index.</p> Full article ">Figure 6
<p>The process diagram for achieving the calibrated model.</p> Full article ">
27 pages, 22223 KiB  
Article
Microseismic Temporal-Spatial Precursory Characteristics and Early Warning Method of Rockburst in Steeply Inclined and Extremely Thick Coal Seam
by Zhenlei Li, Shengquan He, Dazhao Song, Xueqiu He, Linming Dou, Jianqiang Chen, Xudong Liu and Panfei Feng
Energies 2021, 14(4), 1186; https://doi.org/10.3390/en14041186 - 23 Feb 2021
Cited by 19 | Viewed by 2391
Abstract
Early warning of a potential rockburst risk and its area of occurrence helps to take effective and targeted measures to mitigate rockburst hazards. This study investigates the microseismic (MS) spatial-temporal precursory characteristic parameters in a typical steeply inclined and extremely thick coal seam [...] Read more.
Early warning of a potential rockburst risk and its area of occurrence helps to take effective and targeted measures to mitigate rockburst hazards. This study investigates the microseismic (MS) spatial-temporal precursory characteristic parameters in a typical steeply inclined and extremely thick coal seam (SIETCS) with high rockburst risk and proposes three spatial/temporal quantification parameters and a spatial-temporal early warning method. Analysis results of temporal parameters show that the sharp-rise-sharp-drop variation in total daily energy and event count can be regarded as a precursor for high energy tremor. The appearance of peak values of both energy deviation (?20) and event count deviation (?1) can be regarded as precursors that indicate imminent rockburst danger. A laboratory acoustic emission (AE) experiment reveals that precursor characteristics obtained from the study can be feasibly used to warn the rockburst risk. The spatial evolution laws of spatial parameters show that the high energy density index of MS (EDIM), velocity, velocity anomaly regions correlate well with stress concentration and rockburst risk areas. The field application verifies that the temporal-spatial early warning method can identify the potential rockburst risk in a temporal sequence and rockburst risk areas during the temporal early warning period. Full article
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<p>Stress-strain curve of coal-rock specimens during the deformation-failure process (Dou et al. 2017).</p> Full article ">Figure 2
<p>Temporal evolution law of acoustic emission (AE) pulses on the process coal specimen’s failure. (<b>a</b>) specimen A, (<b>b</b>) specimen B.</p> Full article ">Figure 3
<p>Flowchart of the temporal-spatial comprehensive early warning method to accurately forecast rockburst and risk area. EDIM: energy density index of MS.</p> Full article ">Figure 4
<p>Geologic section of WCM.</p> Full article ">Figure 5
<p>In situ record photos showing damage to the rockburst and high energy tremor in +450 horizontal No. B3 + 6 working face (<b>a</b>) rockburst “2·1”, (<b>b</b>) high energy tremor “3·21”.</p> Full article ">Figure 6
<p>Probes installation position of the MS monitoring system when the “4·26” rockburst occurred.</p> Full article ">Figure 7
<p>Daily total energy and event count evolution law before one month the high energy tremors. (<b>a</b>) “12·9”, (<b>b</b>) “12·23”, (<b>c</b>) “3·7”, (<b>d</b>) “3·21”.</p> Full article ">Figure 8
<p>Energy deviation temporal evolution law before and after the rockbursts and high energy tremors.</p> Full article ">Figure 9
<p>Event count deviation temporal evolution law before and after the rockbursts and high energy tremors.</p> Full article ">Figure 10
<p>Temporal evolution law of AE energy on the process coal specimen’s failure. (<b>a</b>) specimen A, (<b>b</b>) specimen B.</p> Full article ">Figure 11
<p>“Critical value+ trend” rockburst temporal early warning method. <span class="html-italic">E</span>: maximum energy.</p> Full article ">Figure 12
<p>Spatial evolution of the EDIM before each rockburst. (<b>a</b>) “11·24”, (<b>b</b>) “2·1”, (<b>c</b>) “4·26”.</p> Full article ">Figure 12 Cont.
<p>Spatial evolution of the EDIM before each rockburst. (<b>a</b>) “11·24”, (<b>b</b>) “2·1”, (<b>c</b>) “4·26”.</p> Full article ">Figure 13
<p>Elevation of each rockburst source spatial distribution.</p> Full article ">Figure 14
<p>Principle of induced rockburst in a steeply inclined and extremely thick coal seam (SIETCS). σ<sub>s</sub> is the static stress, σ<sub>d</sub> is the dynamic stress, and σ<sub>c</sub> is the critical value stress when rockburst occurs [<a href="#B51-energies-14-01186" class="html-bibr">51</a>].</p> Full article ">Figure 15
<p>Tomographic images obtained using MS events on 22 April 2017 (with the 125 MS events that occurred). (<b>a</b>) Velocity inversion result, (<b>b</b>) Velocity anomaly inversion result.</p> Full article ">Figure 15 Cont.
<p>Tomographic images obtained using MS events on 22 April 2017 (with the 125 MS events that occurred). (<b>a</b>) Velocity inversion result, (<b>b</b>) Velocity anomaly inversion result.</p> Full article ">Figure 16
<p>Tomographic images obtained using MS events on 23 April 2017 (with the 181 MS events that occurred). (<b>a</b>) Velocity inversion result, (<b>b</b>) Velocity anomaly inversion result.</p> Full article ">Figure 17
<p>Early warning results of “critical value + trend” early warning method (precursor analysis stage).</p> Full article ">Figure 18
<p>Early warning results of “critical value + trend” early warning method (application stage).</p> Full article ">Figure 19
<p>Spatial evolution law of the EDIM from 11 July 2017 to 16 July 2017.</p> Full article ">Figure 20
<p>Schematic diagram of pressure-relief boreholes: (<b>a</b>) Plan view of the alternate layout of deep and shallow boreholes, (<b>b</b>) Sectional plan of shallow de-stress blasting borehole, (<b>c</b>) Sectional plan of deep de-stress blasting borehole.</p> Full article ">
21 pages, 3581 KiB  
Article
Energy Efficiency in OECD Countries: A DEA Approach
by Filip Fidanoski, Kiril Simeonovski and Violeta Cvetkoska
Energies 2021, 14(4), 1185; https://doi.org/10.3390/en14041185 - 23 Feb 2021
Cited by 18 | Viewed by 3563
Abstract
This paper deals with energy efficiency examined through an integrated model that links energy with environment, technology, and urbanisation as related areas. Our main goal is to discover how efficiently developed countries use primary energy and electricity (secondary energy). We additionally want to [...] Read more.
This paper deals with energy efficiency examined through an integrated model that links energy with environment, technology, and urbanisation as related areas. Our main goal is to discover how efficiently developed countries use primary energy and electricity (secondary energy). We additionally want to find out how the inclusion of environmental care and renewable energy capacity affects efficiency. For that purpose, we set up an output-oriented BCC data envelopment analysis that employs a set of input variables with non-negative values to calculate the efficiency scores on minimising energy use and losses as well as environmental emissions for a sample of 30 OECD member states during the period from 2001 to 2018. We develop a couple of baseline models in which we find that countries have mean inefficiency margins of 16.1% for primary energy and from 10.8 to 13.5% for electricity. The results from the extended models show that taking care about environment does not affect efficiency in general, while the reliance on energy produced from renewable sources does slightly reduce it. Full article
(This article belongs to the Special Issue Impact of Sustainable Financial and Economic Development on Greenhouse Gas Emission)
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<p>Time evolution of the input variables.</p> Full article ">Figure A2
<p>Time evolution of the output variables.</p> Full article ">Figure A3
<p>Primary energy intensity and nominal GDP per capita.</p> Full article ">Figure A4
<p>Electricity intensity and nominal GDP per capita.</p> Full article ">Figure A5
<p>Electricity loss ratio and nominal GDP per capita.</p> Full article ">Figure A6
<p>(In)efficiency scores for primary energy.</p> Full article ">Figure A7
<p>(In)efficiency scores for electricity.</p> Full article ">Figure A8
<p>(In)efficiency scores for electricity with renewable electricity capacity.</p> Full article ">
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