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Energies, Volume 16, Issue 21 (November-1 2023) – 242 articles

Cover Story (view full-size image): In this paper, an analysis of the exhaust emissions of components such as CO, THC, and NOx in relation to the type of road surface and its condition is presented. The analysis was performed on a heavy-duty truck designed for carriage of timber. The investigations were carried out with the use of the PEMS equipment (portable emission measurement system) on bitumen-paved roads and unpaved forest access roads. The portable measurement system allowed for an accurate determination of the influence of the road conditions on the operating parameters of the vehicle powertrain and its exhaust emissions. Additionally, the influence of the type of road surface on vehicle fuel consumption calculated based on the carbon balance method is presented. View this paper
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33 pages, 9578 KiB  
Review
Data-Driven Machine Learning Methods for Nontechnical Losses of Electrical Energy Detection: A State-of-the-Art Review
by Andrey Pazderin, Firuz Kamalov, Pavel Y. Gubin, Murodbek Safaraliev, Vladislav Samoylenko, Nikita Mukhlynin, Ismoil Odinaev and Inga Zicmane
Energies 2023, 16(21), 7460; https://doi.org/10.3390/en16217460 - 6 Nov 2023
Cited by 3 | Viewed by 2026
Abstract
Nontechnical losses of electrical energy (NTLEE) have been a persistent issue in both the Russian and global electric power industries since the end of the 20th century. Every year, these losses result in tens of billions of dollars in damages. Promptly identifying unscrupulous [...] Read more.
Nontechnical losses of electrical energy (NTLEE) have been a persistent issue in both the Russian and global electric power industries since the end of the 20th century. Every year, these losses result in tens of billions of dollars in damages. Promptly identifying unscrupulous consumers can prevent the onset of NTLEE sources, substantially reduce the amount of NTLEE and economic damages to network grids, and generally improve the economic climate. The contemporary advancements in machine learning and artificial intelligence facilitate the identification of NTLEE sources through anomaly detection in energy consumption data. This article aims to analyze the current efficacy of computational methods in locating, detecting, and identifying nontechnical losses and their origins, highlighting the application of neural network technologies. Our research indicates that nearly half of the recent studies on identifying NTLEE sources (41%) employ neural networks. The most utilized tools are convolutional networks and autoencoders, the latter being recognized for their high-speed performance. This paper discusses the main metrics and criteria for assessing the effectiveness of NTLEE identification utilized in training and testing phases. Additionally, it explores the sources of initial data, their composition, and their impact on the outcomes of various algorithms. Full article
(This article belongs to the Section A: Sustainable Energy)
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<p>Classification of methods for detecting nontechnical losses of electrical energy [<a href="#B8-energies-16-07460" class="html-bibr">8</a>].</p>
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<p>One-dimensional convolutional neural network for searching theft of electrical energy [<a href="#B73-energies-16-07460" class="html-bibr">73</a>].</p>
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<p>Distribution of consumer data: (<b>a</b>) the original dataset; (<b>b</b>) data processed using the particle swarm optimization algorithm; (<b>c</b>) the result of a simple autoencoder with three hidden layers; (<b>d</b>) the result of a stack autoencoder with three hidden layers [<a href="#B92-energies-16-07460" class="html-bibr">92</a>].</p>
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<p>Dissemination of models and methods for detecting NTLEE.</p>
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<p>Displaying the accuracy of determining the NTLEE of various methods.</p>
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<p>Operating (PR) characteristic of the receiver [<a href="#B81-energies-16-07460" class="html-bibr">81</a>]. Differently colored lines with the same style correspond to experimental neural network performance in terms of one test case but with different network settings.</p>
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<p>(<b>a</b>) ROC is the curve of the autoencoder and 1D convolutional neural network; (<b>b</b>) PR is the curve of the autoencoder and 1D convolutional neural network [<a href="#B81-energies-16-07460" class="html-bibr">81</a>].</p>
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<p>Analysis of the source data used in publications: (<b>a</b>) the source data used in algorithms based on artificial intelligence; (<b>b</b>) the depth of the data retrospective; (<b>c</b>) the metric used to evaluate the effectiveness of the algorithm; (<b>d</b>) the sampling rate of the data used for energy consumption analysis; (<b>e</b>) the number of models using data from the head counter; (<b>f</b>) the presence of a “teacher” when teaching the algorithm; (<b>g</b>) the operating time of the algorithm before the detection of NTLEE.</p>
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<p>Analysis of the source data used in publications: (<b>a</b>) the source data used in algorithms based on artificial intelligence; (<b>b</b>) the depth of the data retrospective; (<b>c</b>) the metric used to evaluate the effectiveness of the algorithm; (<b>d</b>) the sampling rate of the data used for energy consumption analysis; (<b>e</b>) the number of models using data from the head counter; (<b>f</b>) the presence of a “teacher” when teaching the algorithm; (<b>g</b>) the operating time of the algorithm before the detection of NTLEE.</p>
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<p>PR characteristic for a different amount of source data and for a different size of the training sample [<a href="#B74-energies-16-07460" class="html-bibr">74</a>]. Differently colored lines with the same style correspond to experimental neural network performance in terms of one test case but with different network settings.</p>
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<p>The dependence of the accuracy of the model on the number of additional parameters [<a href="#B70-energies-16-07460" class="html-bibr">70</a>].</p>
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<p>The results of the model before (<b>a</b>) and after (<b>b</b>) balancing the source data.</p>
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<p>(<b>a</b>) The neural network training error function for the balanced initial sample; (<b>b</b>) the neural network training error function for the unbalanced initial sample [<a href="#B96-energies-16-07460" class="html-bibr">96</a>].</p>
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<p>(<b>a</b>) AUC value for ANN trained and working on a dataset balanced using different techniques; (<b>b</b>) accuracy value for ANN trained and working on a dataset balanced using different techniques.</p>
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20 pages, 3092 KiB  
Article
Kenya’s Low Carbon Futures: An Assessment Using the KCERT Model
by Jeremy Gachanja, Betsy Muriithi, Onesmus Mwabonje, Alvin Mugwe, John Olukuru, Izael Pereira Da Silva, Francis Mwangi, Alexandre Strapasson and Paisan Sukpanit
Energies 2023, 16(21), 7459; https://doi.org/10.3390/en16217459 - 6 Nov 2023
Viewed by 1526
Abstract
KCERT 2050 is a modelling tool designed to assist in the identification and evaluation of synergies and trade-offs within sectoral decarbonization pathways for Kenya. KCERT 2050 is positioned as a user-friendly and dynamic tool that bridges complex energy systems and emissions models with [...] Read more.
KCERT 2050 is a modelling tool designed to assist in the identification and evaluation of synergies and trade-offs within sectoral decarbonization pathways for Kenya. KCERT 2050 is positioned as a user-friendly and dynamic tool that bridges complex energy systems and emissions models with integrated impact assessment tools, aimed at aiding decision making towards carbon neutrality in both public and private sectors. The tool considers greenhouse gas emissions from various economic sectors and is validated through a collaborative process involving experts from diverse backgrounds. This study uses KCERT 2050 to examine the prospects of achieving a net−zero emissions pathway by 2050. In the baseline scenario, a significant emission trajectory is observed, with the transport sector emerging as the largest contributor. Transitioning to the net−zero pathway reveals substantial reductions across key sectors, such as transport, industry, and land use, driven by strategies including electrification, waste reduction, and afforestation. The sensitivity analysis underscores the potential for emission mitigation through various levers, including land use optimization and the adoption of cleaner transportation modes. In conclusion, our findings emphasize the potential and feasibility of Kenya’s ambitious net−zero emissions target. To attain this goal, it is imperative to prioritize sustainable land use and innovative waste management strategies. Full article
(This article belongs to the Section A: Sustainable Energy)
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<p>Levels of ambition [<a href="#B35-energies-16-07459" class="html-bibr">35</a>].</p>
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<p>Snapshot of KCERT interface and emissions during BAU scenario.</p>
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<p>KCERT emission trajectories under the net-zero pathway.</p>
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<p>KCERT net−zero pathway emissions in 2050.</p>
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<p>Sectoral electricity demand under the net-zero pathway for the year 2050.</p>
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<p>Electricity generation mix under the net-zero pathway.</p>
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<p>Sensitivity analysis of KCERT levers. Note: The sectors here are grouped by colour: grey for industries, blue for transport, purple for buildings, green for land use and bioenergy, orange for CO<sub>2</sub> removal, and red for electricity generation. The different shades of colour associated with each sector represent the aggregate changes in GHG emission abatement from a moderate level (level 1 to level 2, light shade) to an ambitious effort (level 2 to level 3, medium shade) to a very ambitious effort (level 3 to level 4, dark shade) as implemented by [<a href="#B37-energies-16-07459" class="html-bibr">37</a>].</p>
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16 pages, 8055 KiB  
Article
Design and Experimental Verification of Hubless Rim-Driven Propulsor Consisting of Bearingless Propeller for an Unmanned Underwater Drone
by Myoung-Su Kim and Sung-An Kim
Energies 2023, 16(21), 7458; https://doi.org/10.3390/en16217458 - 6 Nov 2023
Viewed by 1384
Abstract
This paper presents the design and experimental verification of a hubless rim-driven propulsor (HRDP) for an unmanned underwater drone. The bearings of the HRDP are required to rotate and fix the propeller. However, the bearing increases the weight and size of the propulsor. [...] Read more.
This paper presents the design and experimental verification of a hubless rim-driven propulsor (HRDP) for an unmanned underwater drone. The bearings of the HRDP are required to rotate and fix the propeller. However, the bearing increases the weight and size of the propulsor. Therefore, this paper proposes a structure in which the rotor of a surface-mounted permanent magnet synchronous motor (SPMSM) and a hubless propeller are combined without the bearings in the rim-driven propulsor. The design procedure of the propulsor is established and the response surface method (RSM) is used to design and optimize the proposed structure. The validity of the HRDP with the proposed structure is verified through simulation results using an electromagnetic field (EF) analysis and computational fluid analysis, and test results using a water tank. Finally, compared to the initial HRDP, the weight of the SPMSM in the optimized HRDP is decreased by 7.3%, and by reducing the required torque by about 19%, power consumption is reduced by about 24.66 W. Full article
(This article belongs to the Special Issue Urban Electromobility and Electric Propulsion)
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<p>Flowchart for the design and analysis of HRDP.</p>
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<p>Boundary conditions for the CFD analysis.</p>
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<p>Optimization plot of propeller.</p>
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<p>Shape comparison between initial propeller and optimized propeller: (<b>a</b>) Blade cross-sections from 0.25 R to 0.4 R; (<b>b</b>) Blade cross-sections from 0.5 R to 0.8 R; (<b>c</b>) Blade cross-sections from 0.9 R to 1 R; (<b>d</b>) Optimized propeller.</p>
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<p>Performance comparison between initial propeller and optimized propeller according to speed using CFD analysis: (<b>a</b>) Thrust; (<b>b</b>) Required torque; (<b>c</b>) Mechanical power; (<b>d</b>) <span class="html-italic">TTR</span> and <span class="html-italic">PRR</span>.</p>
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<p>Shape comparison between initial SPMSM and optimized SPMSM: (<b>a</b>) Initial SPMSM; (<b>b</b>) Optimized SPMSM.</p>
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<p>Performance comparison between initial SPMSM and optimized SPMSM using EF analysis: (<b>a</b>) Line to line BEMF; (<b>b</b>) Output torque.</p>
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<p>Optimization plot of SPMSM.</p>
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<p>Manufactured HRDP: (<b>a</b>) Hubless propeller with the rotor; (<b>b</b>) Duct with the stator.</p>
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<p>Water tank test setup of the HRDP.</p>
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<p>Comparison of simulation and experimental results: (<b>a</b>) Terminal line to line voltage and phase current of HRDP at rated speed of 3300 rpm; (<b>b</b>) Terminal line to line voltage according to speed; (<b>c</b>) Phase current according to speed; (<b>d</b>) Torque estimated from controller according to speed; (<b>e</b>) Thrust according to speed.</p>
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<p>Durability test results of HRDP.</p>
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10 pages, 256 KiB  
Article
Business Model Innovation for Digitalization in the Swedish District Heating Sector
by Jon Williamsson
Energies 2023, 16(21), 7457; https://doi.org/10.3390/en16217457 - 6 Nov 2023
Cited by 1 | Viewed by 955
Abstract
Despite decades of research and development, digitalization remains a key challenge for the Swedish district heating sector. Business model innovation is believed to be necessary to capitalize on digitalization, yet it is especially challenging for municipal companies. This study aims to identify the [...] Read more.
Despite decades of research and development, digitalization remains a key challenge for the Swedish district heating sector. Business model innovation is believed to be necessary to capitalize on digitalization, yet it is especially challenging for municipal companies. This study aims to identify the potential impact of digitalization on the business models of Swedish district heating companies and to analyze the barriers that exist for digital business model innovation. Through case studies of eight municipal district heating companies, this study demonstrates how the entire business model is potentially impacted by digitalization. This study also identifies the barriers to digital business model innovation that are linked to two conflicting views (restrictive versus comprehensive) on digitalization. The restrictive view diminishes the importance of business model innovation, outsourcing innovation to minimize both costs and risks for the company. In contrast, the comprehensive view embraces digital business model innovation through trial-and-error and opens the innovation process to stakeholder influence. These two perspectives are motivated by different beliefs about the need for digitalization to secure future business opportunities, as well as differences in owners’ risk appetite. The implications for industry outlooks and the design of policy support for the digitalization of district heating are discussed. Full article
(This article belongs to the Topic District Heating and Cooling Systems)
15 pages, 2975 KiB  
Article
Thermal Simulation and Analysis of Dry-Type Air-Core Reactors Based on Multi-Physics Coupling
by Jie Wu, Zhengwei Chang, Huajie Zhang, Man Zhang, Yumin Peng, Jun Liao and Qi Huang
Energies 2023, 16(21), 7456; https://doi.org/10.3390/en16217456 - 6 Nov 2023
Cited by 4 | Viewed by 1216
Abstract
A reactor is an important piece of equipment used for reactive power compensation in power system and has a significant impact on the safe operation of power system. Thermal behavior is one of the main causes of reactor failures. For an accurate analysis [...] Read more.
A reactor is an important piece of equipment used for reactive power compensation in power system and has a significant impact on the safe operation of power system. Thermal behavior is one of the main causes of reactor failures. For an accurate analysis of the thermal behavior of reactors, electromagnetic–thermal–fluid multi-physics coupling modeling is chosen. However, there is a huge difference in size between the overall structure of the reactor and its insulating material, which makes it difficult to perform mesh generation, resulting in dense mesh and significantly increased solution degrees of freedom, thus making the solution of the reactor’s multi-physics field model very time-consuming. To address this, this paper proposes a simplified processing method to accelerate the solution calculation of the reactor’s multi-physics model. This method calculates the equivalent turns of each encapsulate with parallel coils in the reactor, simplifying the encapsulate into a single-layer coil, thereby greatly reducing the division and solution degrees of freedom of the multi-physics model, and thus accelerating the simulation calculation. Taking a BKDCKL-20000/35 dry-type air-core shunt reactor as an example, the outer diameter of the coil is nearly 12,000 times bigger than the coil insulation, which is a huge size difference. Both refined models and simplified models are established. Compared to the simulation results of the detailed model, the simplified model demonstrates good accuracy; the maximum relative error of temperature is just 2.19%. Meanwhile, the computational time of the simplified model is reduced by 35.7%, which shows promising effectiveness and significant potential for applying the optimization design and operation prediction of dry-type air-core shunt reactors for enhanced thermal performance. Full article
(This article belongs to the Section F1: Electrical Power System)
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<p>Diagram of boundary numbering for each encapsulate of the reactor.</p>
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<p>A diagram of multi-physics modeling and modeling processes.</p>
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<p>The magnetic flux density distribution of the reactor. (<b>a</b>) Magnetic flux density nephogram; (<b>b</b>) axial distribution of magnetic flux density in the encapsulate.</p>
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<p>Temperature distribution nephogram of the reactor. (<b>a</b>) Global view of temperature distribution; (<b>b</b>) local view of temperature distribution.</p>
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<p>The simulation results of temperature in radial and axial directions. (<b>a</b>) Radial temperature distribution at different heights; (<b>b</b>) axial temperature distribution in different encapsulates; (<b>c</b>) axial temperature distribution of air passages between different encapsulates.</p>
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<p>Simulation results of fluid velocities for the reactor. (<b>a</b>) Fluid velocity distribution nephogram; (<b>b</b>) axial fluid velocity of air passage between different encapsulates.</p>
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<p>Temperature comparisons between the multi-physics refined model and the simplified model in the radial direction at different heights. (<b>a</b>) Temperature comparisons between multi-physics refined model and simplified model based on the radial direction at Height 1; (<b>b</b>) temperature comparisons between the multi-physics refined model and the simplified model based on the radial direction at Height 2; (<b>c</b>) temperature comparisons between the multi-physics refined model and the simplified model based on the radial direction at Height 3; (<b>d</b>) temperature comparisons between the multi-physics refined model and the simplified model based on the radial direction at Height 4.</p>
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4 pages, 187 KiB  
Editorial
Energy Industry Transition Transformation in the Wake of COVID-19
by George Xydis and Evanthia Nanaki
Energies 2023, 16(21), 7455; https://doi.org/10.3390/en16217455 - 6 Nov 2023
Viewed by 1138
Abstract
The COVID-19 pandemic has caused significant shifts in energy demand and generation patterns, going beyond geographical boundaries and demanding creative responses from the energy industry as a whole [...] Full article
19 pages, 4647 KiB  
Article
Robust Constant Exponent Coefficient Fixed-Time Control Based on Finite-Time Extended Sliding Mode Observer of Permanent Magnet Synchronous Motors
by Varin Cholahan, Napasool Wongvanich and Worapong Tangsrirat
Energies 2023, 16(21), 7454; https://doi.org/10.3390/en16217454 - 6 Nov 2023
Cited by 1 | Viewed by 1321
Abstract
This paper presents the Robust Constant Exponent Coefficient Fixed-Time Control (CECFSMC), an innovative control technique for precisely regulating the speed of a permanent magnet synchronous motor (PMSM) by utilizing fixed-time stability with constant exponent coefficients to provide not only faster convergence but also [...] Read more.
This paper presents the Robust Constant Exponent Coefficient Fixed-Time Control (CECFSMC), an innovative control technique for precisely regulating the speed of a permanent magnet synchronous motor (PMSM) by utilizing fixed-time stability with constant exponent coefficients to provide not only faster convergence but also in a specific period of time. The effect of chattering is also lessened. To ensure that the designed controller produces the desired performance under bounded disturbances, a finite-time extended sliding-mode observer (ESMO) is also designed to estimate the PMSM velocity while also estimating lumped load disturbances. The considered PMSM is the surface-mounted PMSM. Finally, a numerical simulation with PMSM drive shows good robustness against load disturbances, better convergence, and a reaching time of less than 2 s, thereby demonstrating that the proposed fixed-time constant exponent coefficient offers good performance and is much simpler than the conventional finite-time method. Full article
(This article belongs to the Section F: Electrical Engineering)
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<p>Block diagram of PMSM FOC variable speed control.</p>
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<p>Block diagram of fixed-time control with conventional sliding-mode surface.</p>
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<p>Block diagram of fixed-time controller with a conventional sliding mode surface and a finite-time extended sliding mode observer.</p>
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<p>Position tracking <span class="html-italic">x</span><sub>1</sub>(<span class="html-italic">t</span>) plotted versus time.</p>
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<p>Speed tracking <span class="html-italic">x</span><sub>2</sub>(<span class="html-italic">t</span>) plotted versus time.</p>
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<p>Control signal <math display="inline"><semantics> <mrow> <msubsup> <mi>i</mi> <mi>q</mi> <mo>∗</mo> </msubsup> </mrow> </semantics></math> plotted versus time.</p>
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<p>Phase plane trajectory plotted under disturbance.</p>
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<p>Trajectory of the s-variable of (18).</p>
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<p>Comparison between the system disturbance against its estimation from the ESMO (26).</p>
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<p>The comparison between a PI controller, the conventional controller, and the proposed controller for the position response.</p>
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<p>The comparison between a PI controller, the conventional controller, and the proposed controller for the speed response.</p>
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13 pages, 5296 KiB  
Article
Numerical Simulation Method for Flash Evaporation with Circulating Water Based on a Modified Lee Model
by Bingrui Li, Xin Wang, Yameng Man, Bingxi Li and Wei Wang
Energies 2023, 16(21), 7453; https://doi.org/10.3390/en16217453 - 5 Nov 2023
Cited by 2 | Viewed by 1714
Abstract
Flash evaporation processes are widely adopted in the desalination, food processing, waste heat recovery and other industries for heat extraction or product separation. In this paper, a pressure-driven phase transition model is developed by improving the Lee model and combined with the VOF [...] Read more.
Flash evaporation processes are widely adopted in the desalination, food processing, waste heat recovery and other industries for heat extraction or product separation. In this paper, a pressure-driven phase transition model is developed by improving the Lee model and combined with the VOF (Volume of Fluid) method to numerically simulate the flash evaporation process. In this modified Lee phase transition model, the driving force for the rates of the local phase transition is calculated using the local temperature and static pressure magnitude. Numerical simulations are carried out in a water-circulating flash chamber and compared with the experimental results to obtain the values of the time relaxation parameters. And the non-equilibrium fraction of the outlet water can be effectively obtained under different conditions of flow rate, inlet temperature and initial liquid level height. The time relaxation factor takes values from 0.195 to 0.43 (Pout,v = 19.9 kPa) and from 0.31 to 0.92 (Pout,v = 31.2 kPa) with increasing superheat. In addition, the model can effectively represent the evolution of the unstable flow flash evaporation from the initial rapid boiling state to dynamic equilibrium. Full article
(This article belongs to the Special Issue Numerical Simulation on Heat Transfer Technique)
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<p>Schematic diagram of flash chamber.</p>
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<p>Flow chart of the numerical model calculating.</p>
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<p>Variations in pressure and phase transition rate at a certain point.</p>
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<p>Independence test for the pressure invariant time in assumption.</p>
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<p>Grids and grids independence validation: (<b>a</b>) results of grid independence verification; (<b>b</b>) grid structure.</p>
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<p>Time relaxation parameters for different inlet superheats.</p>
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<p>Comparison of numerical and experimental data [<a href="#B7-energies-16-07453" class="html-bibr">7</a>].</p>
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<p>The two-phase distributions of flash evaporation over time (0~6 s): (<b>a</b>)~(<b>t</b>) results at different times.</p>
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<p>The mass rate of vapor generation and average water temperature over time: (<b>a</b>) mass rate of vapor generation over time (<b>b</b>) average water temperature over time.</p>
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<p>The phase, pressure, temperature and local phase transition rate distributions in the flash chamber under dynamic equilibrium state.</p>
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16 pages, 513 KiB  
Article
Coupled Effects of Lorentz Force, Radiation, and Dissipation on the Dynamics of a Hybrid Nanofluid over an Exponential Stretching Sheet
by Muhammad Zahid, Abdul Basit, Tariq Ullah, Bagh Ali and Grzegorz Liśkiewicz
Energies 2023, 16(21), 7452; https://doi.org/10.3390/en16217452 - 5 Nov 2023
Cited by 1 | Viewed by 1083
Abstract
The flow and heat transfer induced by an exponentially shrinking sheet with hybrid nanoparticles are investigated comprehensively in this paper. Nanoparticles are considered due to their unusual characteristics such as extraordinary thermal conductivity, which is significant in advanced nanotechnology, heat exchangers, material sciences, [...] Read more.
The flow and heat transfer induced by an exponentially shrinking sheet with hybrid nanoparticles are investigated comprehensively in this paper. Nanoparticles are considered due to their unusual characteristics such as extraordinary thermal conductivity, which is significant in advanced nanotechnology, heat exchangers, material sciences, and electronics. The main objective of this research is to enhance heat transportation. The flow model is first transformed and simplified to a system of ordinary differential equations utilizing non-dimensional quantities and similarity functions. Then, the desired system is solved with the help of the Runge–Kutta numerical method and the shooting technique in MATLAB script. The results show that a stronger porosity parameter raises the temperature while diminishing the velocity. Additionally, they emphasize that augmentations in the magnetic parameter, Eckert number, radiation parameter, and the volume fractions of titanium dioxide and silver nanoparticles are all proportional to the temperature profile. Full article
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<p>Geometry of the problem.</p>
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<p>Variation of the velocity <math display="inline"><semantics> <mrow> <msup> <mi>f</mi> <mo>′</mo> </msup> <mrow> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the magnetic parameter M.</p>
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<p>Variation of the velocity <math display="inline"><semantics> <mrow> <msup> <mi>f</mi> <mo>′</mo> </msup> <mrow> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the porosity parameter <math display="inline"><semantics> <msub> <mi mathvariant="normal">K</mi> <mi>p</mi> </msub> </semantics></math>.</p>
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<p>Variation of velocity <math display="inline"><semantics> <mrow> <msup> <mi>f</mi> <mo>′</mo> </msup> <mrow> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the suction parameter s.</p>
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<p>Variation of the temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of magnetic parameter M.</p>
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<p>Variation of temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the radiation parameter <math display="inline"><semantics> <msub> <mi mathvariant="normal">R</mi> <mi>d</mi> </msub> </semantics></math>.</p>
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<p>Variation of the temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the Eckert number <math display="inline"><semantics> <mrow> <mi mathvariant="normal">E</mi> <mi>c</mi> </mrow> </semantics></math>.</p>
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<p>Variation of the temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the heat source parameter <math display="inline"><semantics> <mi>β</mi> </semantics></math>.</p>
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<p>Variation of the temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the porosity parameter <math display="inline"><semantics> <msub> <mi mathvariant="normal">K</mi> <mi>p</mi> </msub> </semantics></math>.</p>
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<p>Variation of the temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the suction parameter s.</p>
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<p>Variation of the temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the volume fraction <math display="inline"><semantics> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> </semantics></math>.</p>
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<p>Variation of the temperature <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>(</mo> <mi>η</mi> <mo>)</mo> </mrow> </semantics></math> with <math display="inline"><semantics> <mi>η</mi> </semantics></math> for several values of the volume fraction <math display="inline"><semantics> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> </semantics></math>.</p>
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13 pages, 910 KiB  
Article
Empowering Sustainable Energy Solutions through Real-Time Data, Visualization, and Fuzzy Logic
by Adam Stecyk and Ireneusz Miciuła
Energies 2023, 16(21), 7451; https://doi.org/10.3390/en16217451 - 5 Nov 2023
Viewed by 4063
Abstract
This article shows the evaluation of the Integrated Real-time Energy Management Framework (IREMF), a cutting-edge system designed to develop energy management practices. The framework leverages real-time data collection, advanced visualization techniques, and fuzzy logic to optimize energy consumption patterns. To assess the performance [...] Read more.
This article shows the evaluation of the Integrated Real-time Energy Management Framework (IREMF), a cutting-edge system designed to develop energy management practices. The framework leverages real-time data collection, advanced visualization techniques, and fuzzy logic to optimize energy consumption patterns. To assess the performance and importance of each layer and main factor within IREMF, we employ a multi-step methodology. First, the Fuzzy Delphi Method is utilized to harness expert insights and collective intelligence, providing a holistic understanding of the framework’s functionality. Researchers used a fuzzy analytic hierarchy process (AHP) to determine the relative importance of each component of the energy system (first stage). This careful evaluation process helps ensure that resources are allocated effectively and that strategic decisions are made based on sound data. The findings of the study not only improve our understanding of the capabilities of the IREMF platform but also pave the way for future developments in energy system management. The study highlights the critical role of real-time data, visualization, fuzzy logic, and advanced decision-making methods in shaping a sustainable energy future. Full article
(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)
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<p>Research design and methodology. Source: own elaboration.</p>
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<p>Five layers of IREMF model with main factors. Source: own elaboration.</p>
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13 pages, 4850 KiB  
Article
Design and Analysis of High Power Density On-Board Charger with Active Power Decoupling Circuit for Electric Vehicles
by Won-Jin Son and Byoung Kuk Lee
Energies 2023, 16(21), 7450; https://doi.org/10.3390/en16217450 - 5 Nov 2023
Cited by 3 | Viewed by 1589
Abstract
This article presents a design method for the active power decoupling (APD) circuit of a PFC converter for high power density on-board chargers (OBCs) utilized in electric vehicles (EVs). The utilization of electrolytic capacitors to mitigate power ripple at the input is a [...] Read more.
This article presents a design method for the active power decoupling (APD) circuit of a PFC converter for high power density on-board chargers (OBCs) utilized in electric vehicles (EVs). The utilization of electrolytic capacitors to mitigate power ripple at the input is a common practice in PFC converters. However, these electrolytic capacitors are associated with issues such as limited lifetime and low current ratings, resulting in a significant portion of the OBC’s volume being occupied by them. To address these challenges and achieve power density, the relationship between the power of the APD circuit and DC-link voltage is derived, and a design method for the APD circuit for high power density is proposed. The feasibility of this design approach is validated through the PFC converter prototype designed for 6.6 kW OBC. Consequently, a substantial volume reduction of 19.7% is realized when compared to the utilization of the electrolytic capacitor approach, and a reduction of 36.2% is achieved in comparison to the conventional APD design method. This reduction in volume proves advantageous for fulfilling the requisites of high power density OBCs. Full article
(This article belongs to the Special Issue Power Electronics Converters for On-Board Electric Power Systems)
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<p>PFC converter in a 6.6 kW single-phase OBC with APD circuit.</p>
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<p>Control power for the APD circuit. (<b>a</b>) Input power. (<b>b</b>) Decoupling power and power ripple.</p>
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<p>Voltage and current waveform of the APD circuit according to <span class="html-italic">k</span>. (<b>a</b>) Voltage. (<b>b</b>) Current.</p>
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<p><span class="html-italic">L<sub>dec</sub></span> current waveform of APD circuit during DCM operation.</p>
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<p><span class="html-italic">L<sub>dec</sub></span> design range of the APD circuit.</p>
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<p>DC-link voltage according to <span class="html-italic">p<sub>dec</sub></span>. (<b>a</b>) Conventional design. (<b>b</b>) Proposed design.</p>
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<p>Proposed APD circuit design method process. (<b>a</b>) Input voltage and current. (<b>b</b>) Input power. (<b>c</b>) Average power and power ripple. (<b>d</b>) Power ripple and decoupling power. (<b>e</b>) DC-link voltage. (<b>f</b>) Decoupling power and DC-link voltage ripple.</p>
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<p>Proposed APD circuit design method process. (<b>a</b>) Input voltage and current. (<b>b</b>) Input power. (<b>c</b>) Average power and power ripple. (<b>d</b>) Power ripple and decoupling power. (<b>e</b>) DC-link voltage. (<b>f</b>) Decoupling power and DC-link voltage ripple.</p>
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<p>Volume comparison of the proposed APD design method.</p>
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<p>The 6.6 kW PFC converter circuit for design verification.</p>
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<p>Simulation verification waveform of the proposed APD design method. (<b>a</b>) Only PFC converter operation. (<b>b</b>) PFC converter and APD circuit simultaneous operation. (<b>c</b>) APD circuit decoupling voltage. (<b>d</b>) APD circuit decoupling current.</p>
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<p>6.6 kW PFC converter and APD circuit prototype for experimental verification.</p>
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<p>Experimental waveform of the 6.6 kW PFC converter using the proposed design method.</p>
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20 pages, 685 KiB  
Article
An Automatic PI Tuning Method for Photovoltaic Irrigation Systems Based on Voltage Perturbation Using Feedforward Input
by Francisco Jesús Guillén-Arenas, José Fernández-Ramos and Luis Narvarte
Energies 2023, 16(21), 7449; https://doi.org/10.3390/en16217449 - 5 Nov 2023
Cited by 1 | Viewed by 1070
Abstract
This paper proposes a new automatic tuning method for the proportional-integral (PI) controllers of photovoltaic irrigation systems (PVIS) without the need for any other power source or batteries. It enables the optimisation of the values of the PI parameters (Kp and [...] Read more.
This paper proposes a new automatic tuning method for the proportional-integral (PI) controllers of photovoltaic irrigation systems (PVIS) without the need for any other power source or batteries. It enables the optimisation of the values of the PI parameters (Kp and Ki) automatically, eliminating the requirement for skilled personnel during the installation phase of PVIS. This method is based on the system’s voltage response when a disturbance signal is introduced through the feedforward input of the PI controller. To automatically assess the response properties, two indicators are proposed: the total harmonic distortion (THD), used to evaluate the sine response, and the total square distortion (TSD), used to evaluate the square response. The results indicate that the tuning changes for different irradiance and temperature conditions due to the non-linearity of the system, obtaining the most conservative values at maximum irradiance and temperature. The robustness of the results of the new automatic tuning method to abrupt photovoltaic (PV) power fluctuations due to clouds passing over the PV generator has been experimentally tested and the results show that the obtained tuning values make the PVIS stable, even when PV power drops of 66% occur abruptly. Full article
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<p>PVIS architecture.</p>
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<p>Control system architecture.</p>
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<p>Comparison between the response of the system (PV generator voltage) and the sinusoidal disturbance feedforward signal in the time domain.</p>
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<p>Lissajous diagram of the signals shown in <a href="#energies-16-07449-f003" class="html-fig">Figure 3</a>.</p>
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<p>Comparison between PV generator voltage, feedforward (triangular) signal and feedforward signal derivative.</p>
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<p>Values of THD with <math display="inline"><semantics> <mrow> <msub> <mi>K</mi> <mi mathvariant="normal">p</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> and different values of <math display="inline"><semantics> <msub> <mi>K</mi> <mi mathvariant="normal">i</mi> </msub> </semantics></math> for sinusoidal feedforward signal.</p>
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<p>Values of THD with <math display="inline"><semantics> <mrow> <msub> <mi>K</mi> <mi mathvariant="normal">i</mi> </msub> <mo>=</mo> <mn>19</mn> </mrow> </semantics></math> and different values of <math display="inline"><semantics> <msub> <mi>K</mi> <mi mathvariant="normal">p</mi> </msub> </semantics></math> for sinusoidal FWD signal.</p>
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<p>Voltage response using triangle as FWD signal (<math display="inline"><semantics> <mrow> <msub> <mi>K</mi> <mi mathvariant="normal">i</mi> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math>, different values of <math display="inline"><semantics> <msub> <mi>K</mi> <mi mathvariant="normal">p</mi> </msub> </semantics></math>).</p>
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<p>Values of TSD with <math display="inline"><semantics> <mrow> <msub> <mi>K</mi> <mi mathvariant="normal">i</mi> </msub> <mo>=</mo> <mn>19</mn> </mrow> </semantics></math> and different values of <math display="inline"><semantics> <msub> <mi>K</mi> <mi mathvariant="normal">p</mi> </msub> </semantics></math> for triangular FWD signal.</p>
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<p>Fast method flowchart.</p>
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<p>Complete method flowchart.</p>
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<p>Voltage and frequency response to the cloud-pass test.</p>
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15 pages, 2945 KiB  
Article
Reliability Prediction of Distribution Network Using IAO-Optimized Mixed-Kernel LSSVM
by Chen Pan, Lijia Ren and Junjie Wan
Energies 2023, 16(21), 7448; https://doi.org/10.3390/en16217448 - 4 Nov 2023
Viewed by 1174
Abstract
For the sake of conducting distribution network reliability prediction in an accurate and efficient manner, a model for distribution network reliability prediction (IAO-LSSVM) based on an improved Aquila Optimizer (IAO) optimized mixed-kernel Least Squares Support Vector Machine (LSSVM) is thus proposed in this [...] Read more.
For the sake of conducting distribution network reliability prediction in an accurate and efficient manner, a model for distribution network reliability prediction (IAO-LSSVM) based on an improved Aquila Optimizer (IAO) optimized mixed-kernel Least Squares Support Vector Machine (LSSVM) is thus proposed in this paper. First, the influencing factors that greatly affect the distribution network reliability are screened out through grey relational analysis. Afterwards, the radial basis kernel function and polynomial kernel function are combined and a mixed kernel LSSVM model is constructed, which has better generalization ability. However, for the AO algorithm, it is easy to fall into local extremum. In such case, the AO algorithm is innovatively improved after both the improved tent chaotic initialization strategy and adaptive t-distribution strategy are introduced. Next, the parameters of the mixed-kernel LSSVM model are optimized and the IAO-LSSVM distribution network reliability prediction model is established through using the improved AO algorithm. In the end, the prediction results and errors of the IAO-LSSVM prediction model and other models are compared in the actual distribution network applications. It is revealed that the IAO-LSSVM prediction model proposed in this paper features higher accuracy and better stability. Full article
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<p>Distribution histogram of different chaotic sequences. (<b>a</b>) Logistic chaotic sequence distribution histogram. (<b>b</b>) Tent chaotic sequence distribution histogram. (<b>c</b>) Improved tent chaotic sequence distribution histogram.</p>
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<p>Distribution map of t distribution, Gaussian distribution, and Cauchy distribution function.</p>
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<p>Sphere function optimization curve.</p>
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<p>Ackley function optimization curve.</p>
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<p>AO-LSSVM and IAO-LSSVM model fitness curves.</p>
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<p>Comparison of prediction results of training samples.</p>
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<p>Histogram of sample prediction results of each model.</p>
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25 pages, 8968 KiB  
Article
Assessment of Gas Production from Complex Hydrate System in Qiongdongnan Basin of South China Sea
by Lu Yu, Hongfeng Lu, Liang Zhang, Chenlu Xu, Zenggui Kuang, Xian Li, Han Yu and Yejia Wang
Energies 2023, 16(21), 7447; https://doi.org/10.3390/en16217447 - 4 Nov 2023
Cited by 1 | Viewed by 1069
Abstract
The China Geological Survey (CGS) has carried out a large number of surveys and core drilling over the deepwater area of Qiongdongnan Basin (QDNB) in the South China Sea and discovered the natural gas hydrate system controlled by the gas chimney with a [...] Read more.
The China Geological Survey (CGS) has carried out a large number of surveys and core drilling over the deepwater area of Qiongdongnan Basin (QDNB) in the South China Sea and discovered the natural gas hydrate system controlled by the gas chimney with a high geothermal gradient. The complex hydrate system consists of a sandy hydrate reservoir distributed around a lateral transition gas-hydrate mixed zone and a free gas zone in the middle. The hydrate and gas are distributed in the same layer, which is thin but potentially valuable for commercial exploitation. In this paper, a geological model of the target hydrate system in QDNB was established based on the results of several rounds of drilling. The method of numerical simulation was utilized to assess the production capacity of the target hydrate system and clarify the evolution of hydrate and gas saturation distribution with different well positions. The simulation results indicate that the producer well built in the center of the highly-saturated hydrate zone has a limited gas production capacity, with a cumulative production of only 7.25 × 106 m3 in 9 years. The well built at the boundary of the hydrate zone can rapidly link up the gas in the transition zone through a large production pressure differential, but it lacks control over the hydrates and its dissociated gas in the transition zone—the cumulative gas production volume from hydrate accounts for only 12.3%. As for the wells built in the transition zone and gas zone, they can directly invoke the free gas production capacity. Free gas is produced as the formation pressure reduces and hydrate is induced to dissociate, making the gas from the hydrate the subsequent production capacity. The cumulative production can exceed 6 × 108 m3 in 9 years. The stable production duration can extend to 2645 days, and the cumulative proportion of gas at the wellhead from hydrate reaches close to 30%. It is necessary to avoid the free water layer. The bottom water coning would improve the water production by 40% and shorten the stable production duration. In summary, the complex hydrate system of this type in the QDNB has the potential for industrialized exploitation. In the future, the well group can be used for the further improvement of the hydrate utilization rate. Full article
(This article belongs to the Special Issue Gas Hydrates: A Future Clean Energy Resource)
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<p>Three-dimensional geological model of the target system.</p>
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<p>The distribution of hydrate and gas in the target hydrate system.</p>
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<p>The hydrate system division (hydrate zone, transition zone, and gas zone).</p>
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<p>The characteristic of the geothermal gradient and hydrate equilibrium curve in the target system.</p>
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<p>Position of different wells for capacity simulation.</p>
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<p>Depth and sediment properties of different wells for capacity simulation.</p>
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<p>Schematic diagram of sub-model.</p>
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<p>Variation of total gas water at the wellhead, gas produced from hydrate at the wellhead, and water production with time at Site 1.</p>
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<p>Evolution of hydrate and gas saturation distribution at Site 1.</p>
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<p>Variation of total gas water at the wellhead, gas produced from hydrate at the wellhead, and water production with time at Site 2.</p>
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<p>Instantaneous proportion of gas rate at the wellhead from hydrate and the cumulative proportion of gas at the wellhead from hydrate at Site 2.</p>
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<p>Change in gas saturation distribution around the producer well.</p>
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<p>Evolution of the hydrate saturation, gas saturation, and proportion of free gas in the pore in the reservoir during extraction at Site 2.</p>
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<p>Variation of total gas production rate and hydrate contribution rate at wellhead under different steady production rates at Site 3.</p>
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<p>Cumulative volume of gas produced from hydrate and total gas production under different stable production rates at Site 3.</p>
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<p>Instantaneous proportion of gas rate at the wellhead from hydrate and the proportion of cumulative gas volume from hydrate at Site 3.</p>
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<p>Evolution of hydrate saturation with different stable production gas rates at Site 3.</p>
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<p>Evolution of gas saturation with different stable production gas rates at Site 3.</p>
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<p>Variation of total gas water at the wellhead, gas produced from hydrate at the wellhead, and water production with time at Site 4.</p>
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<p>Variation of total gas water at the wellhead, gas produced from hydrate at the wellhead, and water production with time at Site 5.</p>
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<p>Instantaneous proportion of gas rate at the wellhead from hydrate and cumulative proportion of gas at the wellhead from hydrate at Site 5.</p>
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<p>Evolution of the hydrate saturation, gas saturation, and proportion of free gas in the pore in the reservoir during extraction at Site 5.</p>
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16 pages, 3760 KiB  
Article
Studies on the Migration of Sulphur and Chlorine in the Pyrolysis Products of Floor and Furniture Joinery
by Małgorzata Kajda-Szcześniak and Waldemar Ścierski
Energies 2023, 16(21), 7446; https://doi.org/10.3390/en16217446 - 4 Nov 2023
Viewed by 1049
Abstract
This article discusses research on the low-temperature pyrolysis of waste floor and furniture joinery as an example of chemical recycling. Pyrolysis was carried out at 425 °C to obtain solid, liquid, and gaseous products. In line with the circular economy concept, the waste [...] Read more.
This article discusses research on the low-temperature pyrolysis of waste floor and furniture joinery as an example of chemical recycling. Pyrolysis was carried out at 425 °C to obtain solid, liquid, and gaseous products. In line with the circular economy concept, the waste was transformed into economical and environmentally friendly raw materials suitable for application. Research results related to the chemical composition and properties of pyrolysis products are shown, with particular emphasis on the migration process of acidic impurities, i.e., sulphur and chlorine. In some processes, the presence of such substances can be a problem. Research has shown the high potential for sulphur and chlorine migration in pyrolysis products. It was shown that for woodwork, the most sulphur was discharged with the pyrolysis gas and the least was immobilised in the oil fraction. For vinyl panels, more than 50% of the sulphur was immobilised in the char. Chlorine was immobilised mainly in the char and pyrolysis gas. A high chlorine content of 12.55% was found in the vinyl panel. At the same time, a high chlorine content was also found in the pyrolysis products of these panels. This value is several times higher than in wood-based waste. Full article
(This article belongs to the Special Issue Pyrolysis and Gasification of Biomass and Waste II)
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<p>Scheme of the test stand for carrying out the pyrolysis process (author: Waldemar Ścierski).</p>
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<p>The pyrolysis chamber before and after the low-temperature pyrolysis process (author: Małgorzata Kajda-Szcześniak).</p>
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<p>Examples of pyrolysis products: (<b>a</b>) char, (<b>b</b>) pyrolysis oil, and (<b>c</b>) water contaminated with oil fraction (author: Małgorzata Kajda-Szcześniak).</p>
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<p>Thermogravimetric analysis TG/DTG curves of waste floor panels made of HDF fibreboard (own research).</p>
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<p>Thermogravimetric analysis TG/DTG curves of waste floor panels made of vinyl board (own research).</p>
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<p>Monitored process parameters for waste floor panels made of HDF fibreboard.</p>
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<p>Monitored process parameters for waste furniture made of MDF fibreboard.</p>
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<p>Monitored process parameters for waste furniture made of chipboard.</p>
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<p>Monitored process parameters for waste floor planks made of natural wood.</p>
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<p>Monitored process parameters for energy willow chips.</p>
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<p>Monitored process parameters for waste floor panels made of vinyl board.</p>
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21 pages, 4666 KiB  
Article
The State of Knowledge and Attitudes of the Inhabitants of the Polish Świętokrzyskie Province about Renewable Energy Sources
by Jolanta Latosińska and Dorota Miłek
Energies 2023, 16(21), 7445; https://doi.org/10.3390/en16217445 - 4 Nov 2023
Viewed by 877
Abstract
One of the ways to achieve an energy transformation is to reduce environmental degradation through the use of, among other things, renewable energy sources (RES). The widespread use of RES depends not only on economic and technical aspects, but also on societal acceptance. [...] Read more.
One of the ways to achieve an energy transformation is to reduce environmental degradation through the use of, among other things, renewable energy sources (RES). The widespread use of RES depends not only on economic and technical aspects, but also on societal acceptance. The aim of this research was to find out the attitudes and the state of knowledge of residents of Świętokrzyskie province regarding RES. This aim was further specified through five research questions. The research used a diagnostic survey method, and respondents’ opinions were gathered through an author’s survey. This survey included open-ended questions on solar energy (solar panels and photovoltaic panels separately), wind power, hydropower, geothermal energy (ground source heat pump and other sources separately), biomass and biogas. The research sample was selected based on data availability. Econometric modeling was used to analyze the results. The freedom in responding allowed for the exploration of a wide range of respondents’ opinions. The results confirmed the positive attitude of residents towards RES and the influence of education level on their self-assessment. Residents of Świętokrzyskie province, in comparison to residents of Poland, stand out for their high level of acceptance of the use of hydropower in their neighborhood. The opinions of the residents of Świętokrzyskie province on the impact of wind power and heat pumps on the environment did not align with the opinions of the residents of Poland. Full article
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<p>Assessment of households’ knowledge of renewable energy sources. Source: own research. N = 150.</p>
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<p>Renewable energy sources used by respondents at their place of residence; possibility to indicate more than one renewable energy source. Source: own research. N = 150.</p>
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<p>Purpose of RES use vs. nature of building used by respondents. Source: own research. N = 54.</p>
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<p>The question of the necessity of renewable energy production according to respondents. Source: own research. N = 150.</p>
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<p>Benefits of renewable energy production; possibility to indicate more than one benefit. Source: own research. N = 150.</p>
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<p>RES not accepted by respondents in the vicinity of their residence. Source: own research. N = 150.</p>
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<p>Factors influencing households’ decisions to choose an energy source at their place of residence. Source: own research. N = 150.</p>
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<p>Respondents’ choice of a source of renewable energy in the vicinity of their place of residence, if such a possibility existed. Source: own research. N = 150.</p>
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<p>RES considered by survey respondents as the least reliable. Source: own research. N = 150.</p>
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<p>State of knowledge of RES according to respondents’ education. Source: own research. N = 150.</p>
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<p>The state of knowledge about RES according to the age of respondents. Source: own research. N = 150.</p>
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35 pages, 4353 KiB  
Review
An Overview of Short-Term Load Forecasting for Electricity Systems Operational Planning: Machine Learning Methods and the Brazilian Experience
by Giancarlo Aquila, Lucas Barros Scianni Morais, Victor Augusto Durães de Faria, José Wanderley Marangon Lima, Luana Medeiros Marangon Lima and Anderson Rodrigo de Queiroz
Energies 2023, 16(21), 7444; https://doi.org/10.3390/en16217444 - 4 Nov 2023
Cited by 1 | Viewed by 1633
Abstract
The advent of smart grid technologies has facilitated the integration of new and intermittent renewable forms of electricity generation in power systems. Advancements are driving transformations in the context of energy planning and operations in many countries around the world, particularly impacting short-term [...] Read more.
The advent of smart grid technologies has facilitated the integration of new and intermittent renewable forms of electricity generation in power systems. Advancements are driving transformations in the context of energy planning and operations in many countries around the world, particularly impacting short-term horizons. Therefore, one of the primary challenges in this environment is to accurately provide forecasting of the short-term load demand. This is a critical task for creating supply strategies, system reliability decisions, and price formation in electricity power markets. In this context, nonlinear models, such as Neural Networks and Support Vector Machines, have gained popularity over the years due to advancements in mathematical techniques as well as improved computational capacity. The academic literature highlights various approaches to improve the accuracy of these machine learning models, including data segmentation by similar patterns, input variable selection, forecasting from hierarchical data, and net load forecasts. In Brazil, the national independent system operator improved the operation planning in the short term through the DESSEM model, which uses short-term load forecast models for planning the day-ahead operation of the system. Consequently, this study provides a comprehensive review of various methods used for short-term load forecasting, with a particular focus on those based on machine learning strategies, and discusses the Brazilian Experience. Full article
(This article belongs to the Section F: Electrical Engineering)
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<p>STLF process on machine learning models.</p>
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<p>Uni-RNN and Bi-RNN structures.</p>
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<p>Transformer Neural Network architecture example.</p>
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<p>Random Forest framework.</p>
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<p>Net load STLF procedures.</p>
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<p>Rolling window forecasting.</p>
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<p>Planning horizons, optimization models, and time discretization of the problems considered by ONS for generation scheduling and resource coordination.</p>
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<p>PrevCargaDESSEM flowchart.</p>
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<p>PrevCargaDESSEM overview.</p>
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<p>ANNSTLF overview.</p>
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19 pages, 7236 KiB  
Review
Key Issues and Strategies of Aqueous Zinc-Ion Batteries
by Yi Liu, Huibo Wang, Qingyuan Li, Lingfeng Zhou, Pengjun Zhao and Rudolf Holze
Energies 2023, 16(21), 7443; https://doi.org/10.3390/en16217443 - 4 Nov 2023
Cited by 2 | Viewed by 2731
Abstract
With the rapid growth of the world population and the further industrialization of modern society, the demand for energy continues to rise sharply. Hence, the development of alternative, renewable, and clean energy sources is urgently needed to address the impending energy crisis. Rechargeable [...] Read more.
With the rapid growth of the world population and the further industrialization of modern society, the demand for energy continues to rise sharply. Hence, the development of alternative, renewable, and clean energy sources is urgently needed to address the impending energy crisis. Rechargeable aqueous zinc-ion batteries are drawing increased attention and are regarded as the most promising candidates for large-scale energy storage systems. However, some challenges exist for both the anode and cathode, severely restricting the practical application of ZIBs. In this review, we focus on the issues related to the anode (such as dendrites growth, hydrogen evolution, and surface passivation). We discuss the causes of these challenges and summarize the strategies (such as surface engineering, electrolyte modification, and 3D structural skeleton and alloying) to overcome them. Finally, we discuss future opportunities and challenges of ZIBs regarding the Zn anode. Full article
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<p>(<b>A</b>) Pourbaix diagram of the Zn/H<sub>2</sub>O system. Reproduced with permission [<a href="#B10-energies-16-07443" class="html-bibr">10</a>]. Copyright 1997, Elsevier. (<b>B</b>) Hydrogen evolution reaction overpotential considerations. Reproduced with permission [<a href="#B11-energies-16-07443" class="html-bibr">11</a>]. Copyright 1991, Elsevier.</p>
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<p>Schematic illustration of the aqueous zinc-ion battery in a mildly acidic environment. Reproduced with permission [<a href="#B9-energies-16-07443" class="html-bibr">9</a>]. Copyright 2019, Elsevier.</p>
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<p>Zn anode-related issues in aqueous electrolytes. Reproduced with permission [<a href="#B25-energies-16-07443" class="html-bibr">25</a>]. Copyright 202, Elsevier.</p>
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<p>(<b>A</b>) Schematic illustration of the preparation of Cu/Ti<sub>3</sub>C<sub>2</sub>Cl<sub>2</sub> and Zn/Ti<sub>3</sub>C<sub>2</sub>Cl<sub>2</sub> composites. (<b>B</b>) XRD, XPS of bare Zn, ZMX@Zn, CMX@Zn, and Cl 2p spectrum. Reproduced with permission [<a href="#B32-energies-16-07443" class="html-bibr">32</a>]. Copyright 2024, Elsevier. (<b>C</b>) Schematic illustrating how the proposed ARB process can be used to eliminate crystallography heterogeneity of metal electrodes. Reproduced with permission [<a href="#B33-energies-16-07443" class="html-bibr">33</a>]. Copyright 2021, Wiley-VCH. (<b>D</b>) Schematic illustration of fabricating ultrathin graphene layers on the Zn foil. Reproduced with permission [<a href="#B34-energies-16-07443" class="html-bibr">34</a>]. Copyright 2021, Wiley-VCH. (<b>E</b>) XRD spectrum and SEM image of the textured Zn foil. Reproduced with permission [<a href="#B35-energies-16-07443" class="html-bibr">35</a>]. Copyright 2022, Elsevier. (<b>F</b>) Schematic illustration of main advantages of STO@Zn over bare Zn in the mildly acidic aqueous electrolyte. Reproduced with permission [<a href="#B36-energies-16-07443" class="html-bibr">36</a>]. Copyright 2023, Elsevier.</p>
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<p>Radar plots of the properties of different liquid electrolytes. Reproduced with permission [<a href="#B75-energies-16-07443" class="html-bibr">75</a>]. Copyright 2021, Wiley-VCH.</p>
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<p>(<b>A</b>,<b>D</b>) Self-healing test of MMT-PAM hydrogel and mechanism illustration of the controllable accelerated polymerization strategy. (Pink is the original color of MMT-PAM hydrogel, and the blue-green hydrogel is MMT-PAM hydrogel stained with Prussian blue.) Reproduced with permission [<a href="#B18-energies-16-07443" class="html-bibr">18</a>]. Copyright 2023, Elsevier. (<b>B</b>) Chemical structure of CA protective layer. (<b>C</b>) Digital photograph showing elasticity of CA hydrogel. (<b>E</b>) Long-term galvanostatic cycling performances of symmetrical E-Zn@CA and bare-Zn cells at a current density of 10 mA cm<sup>−2</sup> (areal capacity: 2 mAh cm<sup>−2</sup>). (<b>B</b>,<b>C</b>,<b>E</b>) Reproduced with permission [<a href="#B20-energies-16-07443" class="html-bibr">20</a>]. Copyright 2022, Elsevier. (<b>F</b>) Schematic illustrations of the hydrogel electrolyte anti-freezing mechanism. (<b>G</b>) Digital images of the CSAM, CSAM-S, and CSAM-C hydrogels after 12 h storage at −30 °C and the mechanical flexibility demonstration for the CSAM-C hydrogel. (<b>H</b>) Cycling performance of the symmetrical Zn cells with CSAM-C electrolyte under 0.5 mA cm<sup>−2</sup> at −30 °C. Reproduced with permission [<a href="#B19-energies-16-07443" class="html-bibr">19</a>]. Copyright 2022, Wiley-VCH.</p>
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<p>(<b>A</b>) Schematic of sericin molecules. (<b>B</b>) Relationship between the safe electrochemical window and the energy levels of electrodes/electrolytes according to the frontier molecular orbital theory. (<b>C</b>) Molecular orbital energies of H<sub>2</sub>O molecules and sericin molecules. (<b>D</b>) Cycling stability of the Zn symmetrical cells without and with 0.2% sericin additive at 1.0 mA cm<sup>−2</sup>/1.0 mAh cm<sup>−2</sup>. Reproduced with permission [<a href="#B30-energies-16-07443" class="html-bibr">30</a>]. Copyright 2022, Wiley-VCH. (<b>E</b>) Schematic illustration for the preparation process of the N,S-CDs. (<b>F</b>) Observations of the Zn<sup>2+</sup> ion deposition behavior. In situ OM images of the Zn plating process at 5 mA cm<sup>−2</sup> in the electrolyte without and with 0.1% N,S-CDs. Reproduced with permission [<a href="#B99-energies-16-07443" class="html-bibr">99</a>]. Copyright 2023, Royal Society of Chemistry. (<b>G</b>) Schematic illustration of the Zn plating process and in situ observation of Zn plating in the Zn//Zn cell without/with NH<sub>4</sub>OH additives. (<b>H</b>,<b>I</b>) AFM image of the Zn anode surface after cycled in electrolyte without/with NH<sub>4</sub>OH additive. Reproduced with permission [<a href="#B100-energies-16-07443" class="html-bibr">100</a>]. Copyright 2023, Springer.</p>
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<p>(<b>A</b>) Schematic illustration of eutectic strategy for dendrite and crack suppression. (<b>B</b>) Rate performance and long-term Zn stripping/plating cycling of symmetric batteries for monometallic Zn, hypoeutectic Zn50Al50, and eutectic Zn88Al12. Reproduced with permission [<a href="#B101-energies-16-07443" class="html-bibr">101</a>]. Copyright 2020, Springer. (<b>C</b>). Schematic illustration of nano-porous shell/core ZnxCuy/Zn sheets fabrication process. (<b>D</b>) Effect of surface Zn-Cu alloying on Zn deposition. Voltage–time profiles and EIS spectra of galvanostatic Zn deposition on nano-porous Cu/Zn electrode without and with Zn-Cu alloy. Reproduced with permission [<a href="#B16-energies-16-07443" class="html-bibr">16</a>]. Copyright 2022, Springer. (<b>E</b>) Schematic illustration of the procedure for fabricating the 3D Ni–Zn lattices. (<b>F</b>) SEM images with different magnifications of 3D Ni–Zn. (<b>G</b>) Voltage profiles and Rate performance of 2D Ni–Zn symmetric cell and 3D Ni–Zn symmetric cell at different GCD conditions. Reproduced with permission [<a href="#B17-energies-16-07443" class="html-bibr">17</a>]. Copyright 2021, Wiley-VCH.</p>
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21 pages, 9171 KiB  
Article
A New Wall Current Transformer for Accurate Beam Intensity Measurements in the Large Hadron Collider
by Michal Krupa and Marek Gasior
Energies 2023, 16(21), 7442; https://doi.org/10.3390/en16217442 - 4 Nov 2023
Viewed by 1259
Abstract
The Large Hadron Collider (LHC) stores two high-energy counter-rotating particle beams consisting of multiple bunches of a nanosecond length. Precise knowledge of the number of particles within each bunch, known as the bunch intensity, is crucial for physicists and accelerator operators. From the [...] Read more.
The Large Hadron Collider (LHC) stores two high-energy counter-rotating particle beams consisting of multiple bunches of a nanosecond length. Precise knowledge of the number of particles within each bunch, known as the bunch intensity, is crucial for physicists and accelerator operators. From the very beginning of the LHC operation, bunch intensity was measured by four commercial fast beam current transformers (FBCTs) coupling to the beam current. However, the FBCTs exhibited several shortcomings which degraded the measurement accuracy below the required level. A new sensor, the wall current transformer (WCT), has been developed to overcome the FBCT limitations. The WCT consists of eight small radio frequency (RF) current transformers distributed radially around the accelerator’s vacuum chamber. Each transformer couples to a fraction of the image current induced on the vacuum chamber by the passing particle beam. A network of RF combiners sums the outputs of all transformers to produce a single signal which, after integration, is proportional to the bunch intensity. In laboratory tests and during beam measurements, the WCT performance was demonstrated to convincingly exceed that of the FBCT. All originally installed FBCTs were replaced by four WCTs, which have been serving as the LHC reference bunch intensity sensors since 2016. Full article
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<p>Temporal structure of the LHC beam.</p>
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<p>Principle of operation of the fast beam current transformer (FBCT) [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Illustration of the Lorentz contraction of the electric field lines of a single charge [<a href="#B5-energies-16-07442" class="html-bibr">5</a>]. (<b>a</b>) Particle at rest. (<b>b</b>) Particle travelling below the speed of light. (<b>c</b>) Particle travelling close to the speed of light.</p>
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<p>Low-frequency electrical model of the FBCT.</p>
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<p>Baseline droop in the output signal of a sensor with no DC response.</p>
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<p>Image charge induced on the wall of a vacuum chamber by an ultra-relativistic beam [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Principle of operation of the wall current transformer (WCT) [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Electrical model of the WCT [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Schematic of the internal WCT PCBs [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Internal WCT PCBs [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>The new WCT (left) installed next to a displaced FBCT (right) [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>WCT front–end electronics diagram [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Amplitude-normalised time response of the WCT and the FBCT to a nominal LHC bunch [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>WCT response to pilot and nominal LHC bunches measured at the output of the distribution amplifier [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>WCT and FBCT frequency response measured on a laboratory coaxial test bench [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Connection diagram for frequency domain measurements [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>WCT and FBCT beam-coupling impedance measured on a laboratory coaxial test bench [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Sensitivity of the WCT and FBCT to the transverse beam position measured with the LHC beam [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Sensitivity of the WCT and FBCT to the bunch length [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Beam intensity measured by the FBCT and the WCT during RF Frequency Modulation (FM) for beam chromaticity measurements [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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<p>Beam intensity measured by the FBCT and the WCT during beam profile monitor calibration procedure [<a href="#B5-energies-16-07442" class="html-bibr">5</a>].</p>
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14 pages, 3002 KiB  
Article
Simulation Research on the Optimization of Domestic Heat Pump Water Heater Condensers
by Yang Han, Rong Feng, Taiyang Xiao, Machao Guo, Jiahui Wu and Hong Cui
Energies 2023, 16(21), 7441; https://doi.org/10.3390/en16217441 - 4 Nov 2023
Viewed by 1117
Abstract
To improve the heat transfer coefficient of a condenser, this paper proposes using a fin-tube condenser to replace a smooth-tube condenser in a domestic heat pump water heater. The finite element method is used to analyze the heat transfer coefficient of fin-tube condensers [...] Read more.
To improve the heat transfer coefficient of a condenser, this paper proposes using a fin-tube condenser to replace a smooth-tube condenser in a domestic heat pump water heater. The finite element method is used to analyze the heat transfer coefficient of fin-tube condensers with different design parameters. By comparing the results of experiments with those obtained using CFD methods, it has been determined that the CFD method used in this study is feasible. Simulation results showed that the heat transfer coefficient enhanced clearly. The total thermal resistance of the fin-tube condenser decreased by 7% through increasing fin thickness. The total thermal resistance of the fin-tube condenser increased by 1–1.3% when fin spacing was increased. The heat transfer coefficient decreased severely and the maximum total thermal resistance of the fin-tube condenser increased by 8.7% with increasing fin height. In 600 s, when the fin spacing, fin height, fin thickness and inner diameter were 14 mm, 12.5 mm, 1.2 mm and 22.5 mm, respectively, compared to the smooth-tube condenser, the fin-tube condenser could increase the final water temperature by 18.37%, and the heat transfer coefficient would increase by about 95%. This research could provide a low-cost way to improve the heat transfer coefficient of condensers in domestic heat pump water heaters. Full article
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<p>Prototype fin-tube design parameter (<b>left</b>), partial fin-tube model (<b>right</b>).</p>
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<p>Partial prototype fin-tube condenser solution domain.</p>
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<p>Solution domain with mash.</p>
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<p>Parameter design flow chart.</p>
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<p>Schematic diagram of the experimental setup.</p>
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<p>Experiment and simulation comparison.</p>
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<p>Verification of grid–temperature independence.</p>
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<p>Temperature and convective heat transfer coefficient difference between the fin-tube and the smooth-tube at different constant internal wall temperatures.</p>
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<p>Final temperature change in surrounding water after changing fin-tube design parameters.</p>
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<p>Final temperature variation of water in the different experimental groups.</p>
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<p>Profile of temperature distribution of different fin-tubes.</p>
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45 pages, 3131 KiB  
Review
Comprehensive Review of Innovative Materials for Sustainable Buildings’ Energy Performance
by Yara Nasr, Henri El Zakhem, Ameur El Amine Hamami, Makram El Bachawati and Rafik Belarbi
Energies 2023, 16(21), 7440; https://doi.org/10.3390/en16217440 - 3 Nov 2023
Cited by 2 | Viewed by 5373
Abstract
The building sector, one of the most energy-consuming, is among the most current topics due to the maturing concerns about the anthropogenic factor’s impact on CO2 quantities in the atmosphere and its association with global temperature rise. Using sustainable building materials is [...] Read more.
The building sector, one of the most energy-consuming, is among the most current topics due to the maturing concerns about the anthropogenic factor’s impact on CO2 quantities in the atmosphere and its association with global temperature rise. Using sustainable building materials is a promising alternative in building envelope applications to improve in-use energy efficiency. These materials, having a low environmental impact, the advantage of being renewable, and low embodied energy, contribute to global sustainability. This comprehensive literature review presents a broad overview of these materials’ hygrothermal characteristics, thermal performance, and energy use. The main goal is to compile the most important research findings on these materials’ capabilities for building construction and their contributions and effects on energy performance and thermal insulation. Full article
(This article belongs to the Section G: Energy and Buildings)
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<p>The steady increase in CO<sub>2</sub> is due to various emissions [<a href="#B18-energies-16-07440" class="html-bibr">18</a>].</p>
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<p>Referenced research articles as a function of the publishing year.</p>
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<p>Hy-Fi Mushroom-Brick Tower in New York [<a href="#B16-energies-16-07440" class="html-bibr">16</a>].</p>
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<p>BaleHaus, University of Bath: Straw load-bearing walls [<a href="#B43-energies-16-07440" class="html-bibr">43</a>].</p>
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<p>Flax shives: (<b>a</b>) bulk, (<b>b</b>) medium, and (<b>c</b>) large [<a href="#B49-energies-16-07440" class="html-bibr">49</a>].</p>
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<p>Scheme depicting the manufacturing of different types of bioplastics. Information collected from European Bioplastics (<a href="http://www.european-bioplastics.org" target="_blank">www.european-bioplastics.org</a>, accessed on 4 October 2023) [<a href="#B69-energies-16-07440" class="html-bibr">69</a>,<a href="#B70-energies-16-07440" class="html-bibr">70</a>].</p>
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<p>Annual production of biopolymers in 2019. Information collected from the European Bipolymers Organization (<a href="http://www.european-biopolymers.org" target="_blank">www.european-biopolymers.org</a>, accessed on 4 October 2023) [<a href="#B70-energies-16-07440" class="html-bibr">70</a>,<a href="#B101-energies-16-07440" class="html-bibr">101</a>].</p>
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<p>Passive heating with the PCM in the walls, floor, ceiling, and roof [<a href="#B113-energies-16-07440" class="html-bibr">113</a>].</p>
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<p>Representation of the different pathways to supply the PCM with heating/cooling energy [<a href="#B113-energies-16-07440" class="html-bibr">113</a>].</p>
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26 pages, 5363 KiB  
Article
Battery Energy Storage System Damper Design for a Microgrid with Wind Generators Participating in Frequency Regulation
by Bing-Kuei Chiu, Kuei-Yen Lee and Yuan-Yih Hsu
Energies 2023, 16(21), 7439; https://doi.org/10.3390/en16217439 - 3 Nov 2023
Cited by 2 | Viewed by 1047
Abstract
Ancillary frequency control schemes (e.g., droop control) are used in wind farms to improve frequency regulation in grids with substantial renewable energy penetration; however, droop controllers can have negative impacts on the damping of wind turbine torsional mode, thereby reducing the lifespan of [...] Read more.
Ancillary frequency control schemes (e.g., droop control) are used in wind farms to improve frequency regulation in grids with substantial renewable energy penetration; however, droop controllers can have negative impacts on the damping of wind turbine torsional mode, thereby reducing the lifespan of the turbine gearbox. This paper presents a battery energy storage system (BESS) damper to improve the damping of torsional vibrations when using doubly fed induction generators (DFIGs) for frequency regulation in a microgrid. We formulated a linearized model comprising diesel generators, a wind turbine with five-mass drivetrain, and BESS. We also designed a feedforward compensator to deal with phase lag between the BESS damper signal and DFIG torque. The proposed BESS damper was shown to improve the torsional mode damping by moving the eigenvalues for torsional mode leftward to desirable locations on the complex plane. Dynamic simulations performed using MATLAB/SIMULINK demonstrated the efficacy of the proposed BESS torsional mode damping scheme in terms of torsional mode 1 damping performance and frequency response. Full article
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<p>One-line diagram of microgrid with the BESS examined in this study.</p>
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<p>Linearized model of frequency control system for microgrid with BESS.</p>
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<p>BESS equivalent circuit of the battery and block diagram of power controllers and current regulators.</p>
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<p>Block diagram of BESS damper and system frequency response transfer function.</p>
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<p>Real part of eigenvalue <math display="inline"><semantics> <mrow> <msubsup> <mi mathvariant="sans-serif">σ</mi> <mn>1</mn> <mo>’</mo> </msubsup> </mrow> </semantics></math>, BESS damper constants <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">g</mi> <mn>1</mn> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">g</mi> <mn>2</mn> </msub> </mrow> </semantics></math>, and frequency nadir as functions of mode 1 frequency <math display="inline"><semantics> <mrow> <msubsup> <mi mathvariant="sans-serif-italic">ω</mi> <mn>1</mn> <mo>’</mo> </msubsup> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">B</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math>= 0.5 MW, <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">K</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math>= 20, <math display="inline"><semantics> <mrow> <msubsup> <mi mathvariant="sans-serif">ζ</mi> <mn>1</mn> <mo>’</mo> </msubsup> <mo> </mo> </mrow> </semantics></math>= 0.25): (<b>a</b>) real part of eigenvalue; (<b>b</b>) frequency nadir; (<b>c</b>) BESS damper constants <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">g</mi> <mn>1</mn> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">g</mi> <mn>2</mn> </msub> </mrow> </semantics></math>.</p>
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<p>Flowchart showing BESS damper design process.</p>
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<p>Dynamic response curves of microgrid without a BESS damper subjected to a 10% step load change at t = 1 s: (<b>a</b>) frequency, (<b>b</b>) torque <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">T</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">P</mi> <mrow> <mi mathvariant="italic">wind</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>, (<b>e</b>) torsion <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif-italic">θ</mi> <mrow> <mrow> <mn>3</mn> <mi mathvariant="italic">G</mi> </mrow> </mrow> </msub> </mrow> </semantics></math>, (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">P</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>g</b>) <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">P</mi> <mrow> <mi mathvariant="italic">diesel</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>FFT spectra of microgrid without a BESS damper: (<b>a</b>) system frequency; (<b>b</b>) torsion <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif-italic">θ</mi> <mrow> <mrow> <mn>3</mn> <mi mathvariant="italic">G</mi> </mrow> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>FFT spectra of step response: (<b>a</b>) u(t); (<b>b</b>) magnitude.</p>
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<p>Dynamic response curves of microgrid with BESS droop gain but without a BESS damper subjected to a 10% step load change: (<b>a</b>) frequency; (<b>b</b>) torque <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">T</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mrow> <mi mathvariant="italic">wind</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>e</b>) torsion <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif-italic">θ</mi> <mrow> <mrow> <mn>3</mn> <mi mathvariant="italic">G</mi> </mrow> </mrow> </msub> </mrow> </semantics></math>; (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">P</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Dynamic response curves of microgrid with a BESS damper subjected to a 10% step load change at t = 1 s (<math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">K</mi> <mrow> <mi mathvariant="italic">pw</mi> </mrow> </msub> <mrow> <mo>=</mo> </mrow> <mo> </mo> </mrow> </semantics></math>20): (<b>a</b>) frequency; (<b>b</b>) torque <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">T</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>d</b>) torsion <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif-italic">θ</mi> <mrow> <mrow> <mn>3</mn> <mi mathvariant="italic">G</mi> </mrow> </mrow> </msub> </mrow> </semantics></math>; (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">P</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mrow> <mi>damper</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Dynamic response curves of microgrid with BESS damper as a function of BESS capacity (10% step load change at t = 1 s, <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">K</mi> <mrow> <mi mathvariant="italic">pw</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math>= 20, <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">K</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math>= 20): (<b>a</b>) Frequency; (<b>b</b>) Torque <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">T</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>d</b>) Torsion <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif-italic">θ</mi> <mrow> <mrow> <mn>3</mn> <mi mathvariant="italic">G</mi> </mrow> </mrow> </msub> </mrow> </semantics></math>; (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">P</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mrow> <mi mathvariant="italic">damper</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Dynamic response curves of microgrid with WTG damper (10% step load change at t = 1 s, <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">K</mi> <mrow> <mi mathvariant="italic">pw</mi> </mrow> </msub> </mrow> </semantics></math>=20, without BESS): (<b>a</b>) frequency; (<b>b</b>) torque <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">T</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>d</b>) torsion <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif-italic">θ</mi> <mrow> <mrow> <mn>3</mn> <mi mathvariant="italic">G</mi> </mrow> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Enlargement of frequency response curves in <a href="#energies-16-07439-f010" class="html-fig">Figure 10</a>a and <a href="#energies-16-07439-f012" class="html-fig">Figure 12</a>a.</p>
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<p>Dynamic response curves obtained from a microgrid subjected to a 1 m/s stepped decrease in wind speed at t = 1 s. (<math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">B</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math> = 0.5 MW, <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">K</mi> <mrow> <mi mathvariant="italic">pw</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math> = 20, <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">K</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math> = 20): (<b>a</b>) frequency; (<b>b</b>) torque <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">T</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ω</mi> <mi mathvariant="italic">G</mi> </msub> </mrow> </semantics></math>; (<b>d</b>) torsion <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif-italic">θ</mi> <mrow> <mrow> <mn>3</mn> <mi mathvariant="italic">G</mi> </mrow> </mrow> </msub> </mrow> </semantics></math>; (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="italic">P</mi> <mrow> <mi mathvariant="italic">BESS</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mrow> <mi mathvariant="italic">damper</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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14 pages, 2033 KiB  
Article
Investigating the Performance of Efficient and Stable Planer Perovskite Solar Cell with an Effective Inorganic Carrier Transport Layer Using SCAPS-1D Simulation
by Safdar Mehmood, Yang Xia, Furong Qu and Meng He
Energies 2023, 16(21), 7438; https://doi.org/10.3390/en16217438 - 3 Nov 2023
Cited by 3 | Viewed by 1360
Abstract
Organic–inorganic metal halide perovskite (OIMHP) has emerged as a promising material for solar cell application due to their outstanding optoelectronics properties. The perovskite-based solar cell (PSC) demonstrates a significant enhancement in efficiency of more than 20%, with a certified efficiency rating of 23.13%. [...] Read more.
Organic–inorganic metal halide perovskite (OIMHP) has emerged as a promising material for solar cell application due to their outstanding optoelectronics properties. The perovskite-based solar cell (PSC) demonstrates a significant enhancement in efficiency of more than 20%, with a certified efficiency rating of 23.13%. Considering both the Shockley limit and bandgap, there exists a substantial potential for further efficiency improvement. However, stability remains a significant obstacle in the commercialization of these devices. Compared to organic carrier transport layers (CTLs), inorganic material such as ZnO, TiO2, SnO2, and NiOX offer the advantage of being deposited using atomic layer deposition (ALD), which in turn improves the efficiency and stability of the device. In this study, methylammonium lead iodide (MAPbI3)-based cells with inorganic CTL layers of SnO2 and NiOX are simulated using SCAPS-1D software. The cell structure configuration comprises ITO/SnO2/CH3NH3PbI3/NiOX/Back contact where SnO2 and NiOX act as ETL and HTL, respectively, while ITO is a transparent front-end electrode. Detailed investigation is carried out into the influence of various factors, including MAPbI3 layer size, the thickness of CTLs, operating temperature parasitic resistance, light intensity, bulk defects, and interfacial defects on the performance parameters. We found that the defects in layers and interface junctions greatly influence the performance parameter of the cell, which is eliminated through an ALD deposition approach. The optimum size of the MAPbI3 layer and CTL was found to be 400 nm and 50 nm, respectively. At the optimized configuration, the PSC demonstrates an efficiency of 22.13%, short circuit current (JSC) of 20.93 mA/m2, open circuit voltage (VOC) of 1.32 V, and fill factor (FF) of 70.86%. Full article
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<p>(<b>a</b>) Proposed PSC layer configuration; (<b>b</b>) optimum J-V curve.</p>
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<p>Optimization of MAPbI<sub>3</sub> and CTLs layer thickness on solar cell parameters:(<b>a</b>) Open-circuit voltage (<b>b</b>) Short-circuit current density (<b>c</b>) Fill factor (<b>d</b>) Efficiency.</p>
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<p>(<b>a</b>) Impact of light intensity on V<sub>OC</sub> and J<sub>SC</sub>; (<b>b</b>) quantum efficiency in response to wave-length.</p>
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<p>Effect of temperature on PSC performance parameter:(<b>a</b>) Open-circuit voltage (<b>b</b>) Short-circuit current density (<b>c</b>) Fill factor (<b>d</b>) Efficiency.</p>
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<p>Effects of defects density: (<b>a</b>) bulk defects density; (<b>b</b>) interface defects density.</p>
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<p>(<b>a</b>) Influence of shunt resistance on efficiency; (<b>b</b>) efficiency of PSC increases with the increase in shunt resistance; (<b>c</b>) impact of work function on V<sub>OC</sub> and J<sub>SC</sub>; (<b>d</b>) impact of work function on FF and efficiency.</p>
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19 pages, 6010 KiB  
Article
Modified Efficient Energy Conversion System Based on PMSG with Magnetic Flux Modulation
by Michał Krystkowiak
Energies 2023, 16(21), 7437; https://doi.org/10.3390/en16217437 - 3 Nov 2023
Cited by 2 | Viewed by 698
Abstract
The article presents the solution of a power rectifier system dedicated to cooperating with an electric generator based on a special synchronous generator, which can be used in wind or water energy systems. In this generator, a pair of three-phase windings in a [...] Read more.
The article presents the solution of a power rectifier system dedicated to cooperating with an electric generator based on a special synchronous generator, which can be used in wind or water energy systems. In this generator, a pair of three-phase windings in a stator is utilized. One of the windings is connected in a star, and the second one is connected in a delta configuration. Two six-pulse uncontrolled (diode) rectifiers are included at the outputs of the windings. The rectifiers are coupled by a pulse transformer. The primary windings of this transformer are supplied by a power-electronics current source called a current modulator. With the help of this current modulator, the quasi-sinusoidal magnetomotive force (mmf) in the stator of the machine can be obtained. Additionally, to improve the efficiency of the described system, the low-power transistor rectifier, which is connected to the DC bus of the current modulator, has been used. With the help of this converter, it is possible to control and stabilize the voltage level in a DC circuit. It works, in this case, in inverter mode. The principle of working and elaborated control methods of the current modulator and the additional rectifier are presented. Selected results of simulation and experimental tests are also presented. Full article
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<p>Block scheme of the power conversion system based on synchronous generator with magnetic flux modulation, where <span class="html-italic">i</span><sub>A1</sub>, <span class="html-italic">i</span><sub>B1</sub>, <span class="html-italic">i</span><sub>C1</sub>—phase currents for star windings; <span class="html-italic">i</span><sub>A2</sub>, <span class="html-italic">i</span><sub>B2</sub>, <span class="html-italic">i</span><sub>C2</sub>—phase currents for delta windings; <span class="html-italic">i</span><sub>RCT1</sub>, <span class="html-italic">i</span><sub>RCT2</sub>—output currents of diode rectifiers; <span class="html-italic">u</span><sub>RCT1</sub>, <span class="html-italic">u</span><sub>RCT2</sub>—output voltages of diode rectifiers; <span class="html-italic">i</span><sub>CM</sub>—current of modulator; and <span class="html-italic">i</span><sub>out</sub>—load current [<a href="#B10-energies-16-07437" class="html-bibr">10</a>].</p>
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<p>Theoretical shape of the phase current of the PMSGFM generator for a group of connections: (<b>a</b>) star (<span class="html-italic">i</span><sub>A1</sub>) and (<b>b</b>) delta (<span class="html-italic">i</span><sub>A2</sub>) [<a href="#B10-energies-16-07437" class="html-bibr">10</a>].</p>
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<p>Resultant <span class="html-italic">mmf</span> associated with a pair of windings—the first one is connected in the star, while the second in the delta configuration [<a href="#B10-energies-16-07437" class="html-bibr">10</a>].</p>
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<p>Scheme of the current modulator based on the H-bridge structure with the output filter.</p>
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<p>The linear model of the current modulator [<a href="#B13-energies-16-07437" class="html-bibr">13</a>].</p>
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<p>Amplitude and phase characteristics of an open circuit for (<b>a</b>) a current regulator with a low-pass filter structure and (<b>b</b>) a current regulator consisting of a combination of high- and low-pass filters.</p>
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<p>Amplitude and phase characteristics of an open circuit for (<b>a</b>) a current regulator with a low-pass filter structure and (<b>b</b>) a current regulator consisting of a combination of high- and low-pass filters.</p>
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<p>Reference and output signals of the current modulator for low-pass filters (<b>a</b>) and additional high-pass filters (<b>b</b>) implemented in the control system.</p>
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<p>Reference and output signals of the current modulator for low-pass filters (<b>a</b>) and additional high-pass filters (<b>b</b>) implemented in the control system.</p>
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<p>The ideal model of a generator with flux modulation (PMSGFM) and additional transistor rectifier.</p>
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<p>The idea scheme of energy flow between the current modulator and additional low-power transistor rectifier.</p>
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<p>The basic block diagram of a control system for an additional transistor rectifier.</p>
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<p>The modified block diagram of the control system with an additional voltage regulator.</p>
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<p>The modified block diagram of the control system with an additional current regulator.</p>
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<p>The scheme of the power circuit of the elaborated system that was used during the research.</p>
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<p>Average electromagnetic torque (<b>a</b>) and core losses (<b>b</b>) as functions of the equivalent current for machines with a standard design and a generator with star–delta winding [<a href="#B10-energies-16-07437" class="html-bibr">10</a>].</p>
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<p>Back <span class="html-italic">emf</span> waveforms: (<b>a</b>) phase <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi mathvariant="normal">a</mi> </msub> </mrow> </semantics></math> delta winding and line-to-line <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mrow> <mi>ab</mi> </mrow> </msub> </mrow> </semantics></math> star winding; (<b>b</b>) waveforms of <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mrow> <mi>ab</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mrow> <mi>bc</mi> </mrow> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mrow> <mi>ca</mi> </mrow> </msub> </mrow> </semantics></math> in a standard machine [<a href="#B10-energies-16-07437" class="html-bibr">10</a>].</p>
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<p>The scheme of the power circuit based on an active transistor rectifier that was used during the research.</p>
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<p>Efficiency curves of MNS and MSS vs. relative output power [<a href="#B10-energies-16-07437" class="html-bibr">10</a>,<a href="#B14-energies-16-07437" class="html-bibr">14</a>].</p>
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<p>Output and reference signal of the current modulator for: (<b>a</b>) regulator with a low-pass filter structure; (<b>b</b>) a regulator based on a high- and low-pass filter.</p>
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<p>Waveforms of the output currents of the diode bridges (black and red colors) and the output current of the current modulator (blue color).</p>
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<p>Waveform and spectral analysis of the grid current.</p>
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<p>Waveforms of current (azure) and voltage (dark blue) on the primary side of the matching transformer of the transistor rectifier and spectral analysis of the current (red).</p>
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<p>The waveform of voltage in the DC bus of the transistor rectifier and current modulator.</p>
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22 pages, 5671 KiB  
Article
Electrification of Biorefinery Concepts for Improved Productivity—Yield, Economic and GHG Performances
by Sennai Mesfun, Gabriel Gustafsson, Anton Larsson, Mahrokh Samavati and Erik Furusjö
Energies 2023, 16(21), 7436; https://doi.org/10.3390/en16217436 - 3 Nov 2023
Cited by 2 | Viewed by 1245
Abstract
Demand for biofuels will likely increase, driven by intensifying obligations to decarbonize aviation and maritime sectors. Sustainable biomass is a finite resource, and the forest harvesting level is a topic of ongoing discussions, in relation to biodiversity preservation and the short-term role of [...] Read more.
Demand for biofuels will likely increase, driven by intensifying obligations to decarbonize aviation and maritime sectors. Sustainable biomass is a finite resource, and the forest harvesting level is a topic of ongoing discussions, in relation to biodiversity preservation and the short-term role of forests as carbon sinks. State-of-the-art technologies for converting lignocellulosic feedstock into transportation biofuels achieves a carbon utilization rate ranging from 25% to 50%. Mature technologies like second-generation ethanol and gasification-based processes tend to fall toward the lower end of this spectrum. This study explores how electrification can enhance the carbon efficiency of biorefinery concepts and investigates its impact on energy, economics and greenhouse gas emissions. Results show that electrification increases carbon efficiency from 28% to 123% for gasification processes, from 28% to 45% for second-generation ethanol, and from 50% to 65% for direct liquefaction processes. Biofuels are produced to a cost range 60–140 EUR/MWh-biofuel, depending on the chosen technology pathway, feedstock and electricity prices. Notably, production in electrified biorefineries proves cost-competitive when compared to pure electrofuel (E-fuels) tracks. Depending on the selected technology pathway and the extent of electrification, a reduction in GHG emissions ranging from 75% to 98% is achievable, particularly when powered by a low-carbon electricity mix. Full article
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<p>Evaluation framework.</p>
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<p>Reference case configurations of the conversion pathways studied in detail, WGS—water gas shift, AGR—acid gas removal, MSY—methanol synthesis, FTS—Fischer–Tropsch synthesis, SMR—steam reformer, PRE—premethanation, SNGSYN—synthetic natural gas synthesis.</p>
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<p>Integrated BLG-based biofuel process system boundary.</p>
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<p>Inputs and outputs used in the definition of key performance indicators.</p>
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<p>Carbon conversion efficiency to biofuel products (<b>A</b>) and to total products including tradable co-products (<b>B</b>).</p>
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<p>Energy efficiency excluding carbon credit for excess heat, HHV basis, biofuels (<b>A</b>) and total products (<b>B</b>).</p>
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<p>Marginal electricity efficiency to biofuels (<b>A</b>) and total products (<b>B</b>). Note that reference cases are not plotted since these constitute the baseline for measuring marginal efficiency.</p>
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<p>Exergy efficiency excluding credit for excess heat, biofuels (<b>A</b>) and total products (<b>B</b>).</p>
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<p>CAPEX MEUR (<b>A</b>) and specific investment kEUR/kW-biofuel (<b>B</b>).</p>
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<p>Production cost under electricity prices 30 EUR/MWh (<b>A</b>,<b>B</b>) and 40 EUR/MWh (<b>C</b>,<b>D</b>) plotted against electricity fraction in input (<b>A</b>,<b>C</b>) and carbon conversion to biofuel (<b>B</b>,<b>D</b>).</p>
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<p>GHG performance under electricity emission factors kgCO<sub>2</sub>eq/GJ 13.1 (<b>A</b>) and 7 (<b>B</b>).</p>
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<p>GHG performance under zero-emission electricity source.</p>
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14 pages, 2056 KiB  
Article
Analysis of the Use of a Low-Power Photovoltaic System to Power a Water Pumping Station in a Tourist Town
by Kamil Świętochowski, Martyna Świętochowska, Marek Kalenik and Joanna Gwoździej-Mazur
Energies 2023, 16(21), 7435; https://doi.org/10.3390/en16217435 - 3 Nov 2023
Cited by 1 | Viewed by 773
Abstract
The increase in electricity generation prices represents a reason why water utility companies are looking for ways to reduce costs. One of the first ideas of users was to build photovoltaic installations. Water treatment plants or sewage treatment plants usually have large unused [...] Read more.
The increase in electricity generation prices represents a reason why water utility companies are looking for ways to reduce costs. One of the first ideas of users was to build photovoltaic installations. Water treatment plants or sewage treatment plants usually have large unused areas. They look different in facilities that consume a lot of energy but occupy little land, and include water intakes (wells) and water pumping stations. Facilities equipped with pumps are characterized by high electricity consumption. This article assesses the possibility of using PV installations at the water intake. An analysis of energy production from the 3.0 kW PV installation in Polanica-Zdrój was carried out, and then, simulations of the possibility of providing energy via installations with capacities of 3.0 kW, 4.2 kW, and 6.0 kW were performed. Analyses of energy production and demand, as well as analyses of water production based on annual, monthly, daily, and hourly data, were performed. An analysis of the hourly coverage of the WPS’s demand for electricity was carried out with regard to the current production of energy from the PV installation, as was an analysis of the overproduction of energy from the PV installation regarding the energy demand of the WPS. The simulation results are presented for cloudy and sunny days. Full article
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<p>Gravity-Fed Systems with pumps in the well to supply the water tank.</p>
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<p>Pumped systems with pumps in the well and the water pump station (WPS).</p>
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<p>Diagram of the arrangement of PV panels on the water intake plot (1—PV 3.0 kW variant, 2—PV 4.2 kW variant, 3—PV 6.0 kW variant).</p>
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<p>Energy production on cloudy days from the tested installation (3.0 kW).</p>
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<p>Energy production on sunny days from the tested installation (3.0 kW).</p>
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<p>Hourly non-uniformity index of pumped water during the day.</p>
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<p>Monthly non-uniformity index of pumped water during the year.</p>
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<p>Electricity production by 3.0 kW, 4.2 kW, and 6.0 kW installations and water pump station electricity consumption (WPS E.C.).</p>
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20 pages, 3555 KiB  
Article
What Is the Impact of the Renewable Energy Power Absorption Guarantee Mechanism on China’s Green Electricity Market?
by Yan Lu, Xuan Liu, Hongjian Li, Haoran Wang, Jiajie Kong, Cheng Zhong, Mingli Cui, Yan Li, Xiaoqi Sun, Jiadong Xuan and Tiantian Feng
Energies 2023, 16(21), 7434; https://doi.org/10.3390/en16217434 - 3 Nov 2023
Cited by 2 | Viewed by 1314
Abstract
In order to accelerate the construction of a clean, low-carbon, safe and efficient energy system, China set the provincial weight of responsibility for renewable energy power consumption and established a renewable energy power absorption guarantee mechanism in 2019. As a market incentive policy, [...] Read more.
In order to accelerate the construction of a clean, low-carbon, safe and efficient energy system, China set the provincial weight of responsibility for renewable energy power consumption and established a renewable energy power absorption guarantee mechanism in 2019. As a market incentive policy, it has enduring effect on the low-carbon transformation of the power industry. Firstly, the operation mechanism of the renewable energy consumption guarantee mechanism is analyzed. The general framework, core elements and supporting measures are clarified. Secondly, a stock-flow diagram is constructed based on the system dynamics method. It contains the green electricity market sub-module, the green-certificate market sub-module and the excess power absorption market sub-module. Finally, multiple scenarios are set up to simulate the impact of the green-certificate market and excess power absorption market improvements on the installed capacity and tariff of China’s green power market. The renewable energy guarantee mechanism is an effective means to promote the consumption of green electricity in China. In addition, in the short term the cost of electricity for users has increased, but in the long term the cost of electricity shows a fluctuating downward trend. This study provides theoretical references for the formulation of clean and low-carbon policy objectives in the power industry and the optimization of market mechanisms. Full article
(This article belongs to the Collection Renewable Energy and Energy Storage Systems)
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<p>Operating mechanism of renewable-energy-electricity consumption guarantee mechanism.</p>
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<p>Stock flow chart.</p>
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<p>Green-certificate price under different renewable energy consumption weights.</p>
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<p>Excess-consumption price under different renewable energy consumption weights.</p>
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<p>Renewable energy installation under different renewable energy consumption weights.</p>
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<p>Green-certificate price under different penalty prices.</p>
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<p>Excess-consumption price under different penalty prices.</p>
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<p>Renewable energy installation under different penalty prices.</p>
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<p>Profit space of renewable energy manufacturers in a comprehensive scenario.</p>
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<p>Renewable energy power generation under comprehensive scenario.</p>
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16 pages, 903 KiB  
Article
Smart Energy Borrowing and Relaying in Wireless-Powered Networks: A Deep Reinforcement Learning Approach
by Abhishek Mondal, Md. Sarfraz Alam, Deepak Mishra and Ganesh Prasad
Energies 2023, 16(21), 7433; https://doi.org/10.3390/en16217433 - 3 Nov 2023
Viewed by 903
Abstract
Wireless energy harvesting (EH) communication has long been considered a sustainable networking solution. However, it has been limited in efficiency, which has been a major obstacle. Recently, strategies such as energy relaying and borrowing have been explored to overcome these difficulties and provide [...] Read more.
Wireless energy harvesting (EH) communication has long been considered a sustainable networking solution. However, it has been limited in efficiency, which has been a major obstacle. Recently, strategies such as energy relaying and borrowing have been explored to overcome these difficulties and provide long-range wireless sensor connectivity. In this article, we examine the reliability of a wireless-powered communication network by maximizing the net bit rate. To accomplish our goal, we focus on enhancing the performance of hybrid access points and information sources by optimizing their transmit power. Additionally, we aim to maximize the use of harvested energy, by using energy-harvesting relays for both information transmission and energy relaying. However, this optimization problem is complex, as it involves non-convex variables and requires combinatorial relay selection indicator optimization for decode and forward (DF) relaying. To simplify this problem, we utilize the Markov decision process and deep reinforcement learning framework based on the deep deterministic policy gradient algorithm. This approach enables us to tackle this non-tractable problem, which conventional convex optimization techniques would have difficulty solving in complex problem environments. The proposed algorithm significantly improved the end-to-end net bit rate of the smart energy borrowing and relaying EH system by 13.22%, 27.57%, and 14.12% compared to the benchmark algorithm based on borrowing energy with an adaptive reward for Quadrature Phase Shift Keying, 8-PSK, and 16-Quadrature amplitude modulation schemes, respectively. Full article
(This article belongs to the Special Issue Energy Efficiency in IoT and Wireless Sensor Networks)
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<p>System model of the WPCN.</p>
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<p>Impact of different learning rate values on the convergence.</p>
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<p>Performance comparison of the proposed DDPG and the benchmark BEAR algorithms for various modulation schemes.</p>
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<p>Transmit power variation of the HAP over the operational period.</p>
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<p>Net bit rate using the different modulation schemes for a wide range of noise powers.</p>
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<p>Transmit power variation of IS with different modulation schemes for various noise powers.</p>
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24 pages, 4598 KiB  
Article
Power-System Flexibility: A Necessary Complement to Variable Renewable Energy Optimal Capacity Configuration
by Denis Juma, Josiah Munda and Charles Kabiri
Energies 2023, 16(21), 7432; https://doi.org/10.3390/en16217432 - 3 Nov 2023
Cited by 3 | Viewed by 1235
Abstract
Comprehending the spatiotemporal complementarity of variable renewable energy (VRE) sources and their supplemental ability to meet electricity demand is a promising move towards broadening their share in the power supply mix without sacrificing either supply security or overall cost efficiency of power system [...] Read more.
Comprehending the spatiotemporal complementarity of variable renewable energy (VRE) sources and their supplemental ability to meet electricity demand is a promising move towards broadening their share in the power supply mix without sacrificing either supply security or overall cost efficiency of power system operation. Increasing VRE share into the energy mix has to be followed with measures to manage technical challenges associated with grid operations. Most sub-Saharan countries can be considered ‘greenfield’ due to their relatively low power generation baseline and are more likely to be advantaged in planning their future grids around the idea of integrating high VRE sources into the grid from the outset. An essential measure for achieving this objective entails exploring the possibility of integrating renewable hybrid power plants into the existing hydropower grid, leveraging on existing synergies and benefiting from the use of existing infrastructure and grid connection points. This study evaluates the potential for hybridizing existing hydropower-dominated networks to accommodate solar- and wind-energy sources. The existing synergy is quantified using correlation and energy indicators by evaluating complementarity at daily, monthly and annual intervals. The proposed metric serves as a tool to improve planning on increasing the VRE fraction into the existing systems with the aim to achieve optimal power mixes. In comparison to cases in which the same kind of resource is over-planted while expanding installed capacity, the results demonstrate that wind and solar resources hold a positive degree of complementarity, allowing a greater share of VRE sources into the grid. The study shows that Kenya bears favorable climatic conditions that allow hybrid power plant concepts to be widely explored and scaled up on a large and efficient scale. The results can be applicable in other regions and represent an important contribution to promoting the integration of VRE sources into sub-Saharan power grids. Full article
(This article belongs to the Section A: Sustainable Energy)
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<p>Flow chart of the adopted analytical framework.</p>
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<p>Wind–photovoltaic–hydropower complementary space vector.</p>
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<p>The relationship between paired energy resources; (<b>a</b>) perfect similarity and (<b>b</b>) perfect complementarity.</p>
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<p>Schematic representation of the variability of stability coefficient with power output of a hybrid system.</p>
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<p>Installed capacity.</p>
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<p>The Turkwel River Basin with four sub-basins based on climatic condition, topography and land cover. Lodwar town is located at the lower end of the basin.</p>
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<p>The average annual capacity factors of solar photovoltaic (PV) and wind power, calculated over a five-year time scale (2015–2019). (<b>a</b>) for solar photovoltaic and (<b>b</b>) for wind power.</p>
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<p>Key drivers for enhancing power system flexibility in the energy sector.</p>
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<p>Normalised performance of wind (bottom) and solar PV diurnal power generation capability.</p>
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<p>Normalised time series for hourly resource.</p>
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<p>Scatterplot showing annual hourly variation for the paired power resources.</p>
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<p>Monthly variation of the complementary index.</p>
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<p>Scatterplot showing the monthly correlation of the wind and solar PV power resource for (<b>a</b>) January, (<b>b</b>) April, (<b>c</b>) July and (<b>d</b>) October.</p>
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<p>Scatterplot showing the monthly correlation of the solar PV and hydropower resource for: (<b>a</b>) January, (<b>b</b>) April, (<b>c</b>) July and (<b>d</b>) October.</p>
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<p>Scatterplot showing the monthly correlation of the wind and hydropower resource for: (<b>a</b>) January, (<b>b</b>) April, (<b>c</b>) July and (<b>d</b>) October.</p>
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<p>Scatterplot showing the diurnal variation of each paired source.</p>
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<p>Annual wind and solar power generation pattern.</p>
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<p>Histogram plots showing the distribution of solar power wind power and combined production on hourly basis across the year.</p>
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23 pages, 8459 KiB  
Article
Performance Improvement and Emission Reduction Potential of Blends of Hydrotreated Used Cooking Oil, Biodiesel and Diesel in a Compression Ignition Engine
by Ankit Sonthalia and Naveen Kumar
Energies 2023, 16(21), 7431; https://doi.org/10.3390/en16217431 - 3 Nov 2023
Cited by 2 | Viewed by 1045
Abstract
The positive effect of decarbonizing the transport sector by using bio-based fuels is high. Currently, biodiesel and ethanol are the two biofuels that are blended with fossil fuels. Another technology, namely, hydroprocessing, is also gaining momentum for producing biofuels. Hydrotreated vegetable oil (HVO) [...] Read more.
The positive effect of decarbonizing the transport sector by using bio-based fuels is high. Currently, biodiesel and ethanol are the two biofuels that are blended with fossil fuels. Another technology, namely, hydroprocessing, is also gaining momentum for producing biofuels. Hydrotreated vegetable oil (HVO) produced using this process is a potential drop-in fuel due to its improved physiochemical properties. This study aimed to reduce the fossil diesel content by blending 20% and 30% HVO and 5%, 10% and 15% waste cooking oil biodiesel on a volume basis. The blends were used to conduct a thorough performance examination of a single-cylinder compression ignition engine. The thermal efficiency of the engine was enhanced by the addition of biodiesel to the blend. The efficiency increased as the proportion of biodiesel in the mix increased, although it was still less efficient than diesel. The maximum improvement in thermal efficiency of 4.35% was observed with 20% blending of HVO and 15% blending of biodiesel compared with 20% blending of HVO and diesel. However, the HC (decrease of 30%), CO (decrease of 23.5%) and smoke (decrease of 21.1%) emissions were observed to be the lowest with 30% blending of HVO and 15% blending of biodiesel. A fuzzy-logic-based Taguchi method and Grey’s method were then applied to find the best blend of HVO, biodiesel and diesel. The combination of the two methods made it easier to carry out multi-objective optimization. The brake thermal efficiency (BTE), smoke and NO emissions were selected as the output parameters to optimize the HVO and biodiesel blend. The optimization study showed that 30% blending of HVO and 15% blending of biodiesel was the best blend, which was authenticated using the confirmation experiment. Full article
(This article belongs to the Collection Energy Transition towards Carbon Neutrality)
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<p>Schematic of the experimental setup.</p>
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<p>Variation in heat release with biodiesel mixed in blends at full load.</p>
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<p>Variation in in-cylinder pressure with biodiesel mixed in the blends at full load.</p>
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<p>Variation in peak pressure with biodiesel mixed in the blends.</p>
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<p>Variation in ignition delay with biodiesel mixed in the blends.</p>
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<p>Variation in combustion duration with biodiesel mixed in the blends.</p>
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<p>Variation in CA50 with biodiesel mixed in the blends.</p>
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<p>Variation in brake thermal efficiency with biodiesel mixed in the blends.</p>
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<p>Variation in brake-specific energy consumption with biodiesel mixed in the blends.</p>
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<p>Variation in exhaust gas temperature with biodiesel mixed in the blends.</p>
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<p>Variation in unburned hydrocarbon emissions with biodiesel mixed in the blends.</p>
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<p>Variation in carbon monoxide emissions with biodiesel mixed in the blends.</p>
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<p>Variation in oxides of nitrogen emissions with biodiesel mixed in the blends.</p>
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<p>Variation in smoke opacity with biodiesel mixed in the blends.</p>
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<p>Membership function of BTE, NO and smoke.</p>
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<p>Membership function of MPCI.</p>
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<p>Plot of mean MPCI.</p>
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