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Volume 17
Issue 19
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Energies, Volume 17, Issue 19 (October-1 2024) – 258 articles

Cover Story (view full-size image): Energy transition challenges transportation, prompting a shift to electric machines like motors and generators to reduce emissions. This study focuses on improving efficiency in electric vehicles with limited battery capacity. It explores control strategies to minimize energy loss and enhance performance. The research compares Permanent Magnet Synchronous Motors (PMSMs) and Induction Motors (IMs) using real-time loss measurements during simulated driving cycles. The Energetic Macroscopic Representation (EMR) formalism was used for analysis. Results show significant loss reductions, suggesting the controls effectively improve electric motor efficiency, benefiting the automotive industry. View this paper
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24 pages, 4416 KiB  
Article
Cybersecurity Certification Requirements for Distributed Energy Resources: A Survey of SunSpec Alliance Standards
by Sean Tsikteris, Odyssefs Diamantopoulos Pantaleon and Eirini Eleni Tsiropoulou
Energies 2024, 17(19), 5017; https://doi.org/10.3390/en17195017 (registering DOI) - 9 Oct 2024
Viewed by 517
Abstract
This survey paper explores the cybersecurity certification requirements defined by the SunSpec Alliance for Distributed Energy Resource (DER) devices, focusing on aspects such as software updates, device communications, authentication mechanisms, device security, logging, and test procedures. The SunSpec cybersecurity standards mandate support for [...] Read more.
This survey paper explores the cybersecurity certification requirements defined by the SunSpec Alliance for Distributed Energy Resource (DER) devices, focusing on aspects such as software updates, device communications, authentication mechanisms, device security, logging, and test procedures. The SunSpec cybersecurity standards mandate support for remote and automated software updates, secure communication protocols, stringent authentication practices, and robust logging mechanisms to ensure operational integrity. Furthermore, the paper discusses the implementation of the SAE J3072 standard using the IEEE 2030.5 protocol, emphasizing the secure interactions between electric vehicle supply equipment (EVSE) and plug-in electric vehicles (PEVs) for functionalities like vehicle-to-grid (V2G) capabilities. This research also examines the SunSpec Modbus standard, which enhances the interoperability among DER system components, facilitating compliance with grid interconnection standards. This paper also analyzes the existing SunSpec Device Information Models, which standardize data exchange formats for DER systems across communication interfaces. Finally, this paper concludes with a detailed discussion of the energy storage cybersecurity specification and the blockchain cybersecurity requirements as proposed by SunSpec Alliance. Full article
(This article belongs to the Section F2: Distributed Energy System)
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19 pages, 4532 KiB  
Article
Modular Microgrid Technology with a Single Development Environment Per Life Cycle
by Teodora Mîndra, Oana Chenaru, Radu Dobrescu and Lucian Toma
Energies 2024, 17(19), 5016; https://doi.org/10.3390/en17195016 - 9 Oct 2024
Viewed by 537
Abstract
The life cycle of a microgrid covers all the stages from idea to implementation, through exploitation until the end of its life, with a lifespan of around 25 years. Covering them usually requires several software tools, which can make the integration of results [...] Read more.
The life cycle of a microgrid covers all the stages from idea to implementation, through exploitation until the end of its life, with a lifespan of around 25 years. Covering them usually requires several software tools, which can make the integration of results from different stages difficult and may imply costs being hard to estimate from the beginning of a project. This paper proposes a unified platform composed of four modules developed in MATLAB 2022b, designed to assist all the processes a microgrid passes through during its lifetime. This entire platform can be used by a user with low IT knowledge, because it is completed with fill-in-the-blank alone, as a major advantage. The authors detail the architecture, functions and development of the platform, either by highlighting the novel integration of existing MATLAB tools or by developing new ones and designing new user interfaces linked with scripts based on its complex mathematical libraries. By consolidating processes into a single platform, the proposed solution enhances integration, reduces complexity and provides better cost predictability throughout the project’s duration. A proof-of-concept for this platform was presented by applying the life-cycle assessment process on a real-case study, a microgrid consisting of a photovoltaic plant, and an office building as the consumer and energy storage units. This platform has also been developed by involving students within summer internships, as a process strengthening the cooperation between industry and academia. Being an open-source application, the platform will be used within the educational process, where the students will have the possibility to add functionalities, improve the graphical representation, create new reports, etc. Full article
(This article belongs to the Special Issue Planning and Operation of Distributed Energy Resources in Smart Grids II)
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18 pages, 3643 KiB  
Article
MMD-TSC: An Adaptive Multi-Objective Traffic Signal Control for Energy Saving with Traffic Efficiency
by Yuqi Zhang, Yingying Zhou, Beilei Wang and Jie Song
Energies 2024, 17(19), 5015; https://doi.org/10.3390/en17195015 - 9 Oct 2024
Viewed by 430
Abstract
Reducing traffic energy consumption is crucial for smart cities, and vehicle carbon emissions are a key energy indicator. Traffic signal control (TSC) is a useful method because it can affect the energy consumption of vehicles on the road by controlling the stop-and-go of [...] Read more.
Reducing traffic energy consumption is crucial for smart cities, and vehicle carbon emissions are a key energy indicator. Traffic signal control (TSC) is a useful method because it can affect the energy consumption of vehicles on the road by controlling the stop-and-go of vehicles at traffic intersections. However, setting traffic signals to reduce energy consumption will affect traffic efficiency and this is not in line with traffic management objectives. Current studies adopt multi-objective optimization methods with high traffic efficiency and low carbon emissions to solve this problem. However, most methods use static weights, which cannot adapt to complex and dynamic traffic states, resulting in non-optimal performance. Current energy indicators for urban transportation often fail to consider passenger fairness. This fairness is significant because the purpose of urban transportation is to serve people’s mobility needs not vehicles. Therefore, this paper proposes Multi-objective Adaptive Meta-DQN TSC (MMD-TSC), which introduces a dynamic weight adaptation mechanism to simultaneously optimize traffic efficiency and energy saving, and incorporates the per capita carbon emissions as the energy indicator. Firstly, this paper integrates traffic state data such as vehicle positions, velocities, vehicle types, and the number of passengers and incorporates fairness into the energy indicators, using per capita carbon emissions as the target for reducing energy consumption. Then, it proposes MMD-TSC with dynamic weights between energy consumption and traffic efficiency as reward functions. The MMD-TSC model includes two agents, the TSC agent and the weight agent, which are responsible for traffic signal adjustment and weight calculation, respectively. The weights are calculated by a function of traffic states. Finally, the paper describes the design of the MMD-TSC model learning algorithm and uses a SUMO (Simulation of Urban Mobility) v.1.20.0 for traffic simulation. The results show that in non-highly congested traffic states, the MMD-TSC model has higher traffic efficiency and lower energy consumption compared to static multi-objective TSC models and single-objective TSC models, and can adaptively achieve traffic management objectives. Compared with using vehicle average carbon emissions as the energy consumption indicator, using per capita carbon emissions achieves Pareto improvements in traffic efficiency and energy consumption indicators. The energy utilization efficiency of the MMD-TSC model is improved by 35% compared to the fixed-time TSC. Full article
(This article belongs to the Special Issue Hybrid Intelligent Modeling Technology and Optimization Strategy for Industrial Energy Consumption Processes)
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16 pages, 1278 KiB  
Article
Evaluation of the Energy Management System in Water and Wastewater Utilities in the Context of Sustainable Development—A Case Study
by Joanna Machnik-Slomka, Elżbieta Pawlowska, Iwona Klosok-Bazan and Miroslava Goňo
Energies 2024, 17(19), 5014; https://doi.org/10.3390/en17195014 - 9 Oct 2024
Viewed by 413
Abstract
Energy management in enterprises is an important issue in the context of improving energy efficiency, energy use, and energy consumption. This is consistent with the Sustainable Development Goals. The purpose of this study was to evaluate the energy management system of water and [...] Read more.
Energy management in enterprises is an important issue in the context of improving energy efficiency, energy use, and energy consumption. This is consistent with the Sustainable Development Goals. The purpose of this study was to evaluate the energy management system of water and wastewater utility in the context of sustainable development based on the opinions of managers and employees. The results indicate the involvement of the surveyed enterprise in energy management system development activity. This demonstrates the orientation of the surveyed enterprise to support activities to improve energy performance in line with the implementation of sustainable development. The added value is that the developed research tool can be used in studies of other enterprises to assess the level of energy management. Full article
(This article belongs to the Topic Energy Management and Sustainable Development from Economic, Social and Environmental Aspects)
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19 pages, 4781 KiB  
Article
The Impact of Ambient Weather Conditions and Energy Usage Patterns on the Performance of a Domestic Off-Grid Photovoltaic System
by Iviwe Mcingani, Edson L. Meyer and Ochuko K. Overen
Energies 2024, 17(19), 5013; https://doi.org/10.3390/en17195013 - 9 Oct 2024
Viewed by 639
Abstract
Solar photovoltaic (PV) systems are growing rapidly as a renewable energy source. Evaluating the performance of a PV system based on local weather conditions is crucial for its adoption and deployment. However, the current IEC 61724 standard, used for assessing PV system performance, [...] Read more.
Solar photovoltaic (PV) systems are growing rapidly as a renewable energy source. Evaluating the performance of a PV system based on local weather conditions is crucial for its adoption and deployment. However, the current IEC 61724 standard, used for assessing PV system performance, is limited to grid-connected systems. This standard may not accurately reflect the performance of off-grid PV systems. This study aims to evaluate how ambient weather conditions and energy usage patterns affect the performance of an off-grid PV system. This study uses a 3.8 kWp building-integrated photovoltaic (BIPV) system located at SolarWatt Park, University of Fort Hare, Alice, as a case study. Meteorological and electrical data from August and November are analyzed to assess the winter and summer performance of the BIPV system using the IEC 61724 standard. The BIPV system generated 376.29 kWh in winter and 366.38 kWh in summer, with a total energy consumption of 209.50 kWh in winter and 236.65 kWh in summer. Solar irradiation during winter was 130.18 kWh/m2, while it was 210.24 kWh/m2 during summer. The average daily performance ratio (PR) was 44.01% in winter and 28.94% in summer. The observed decrease in PR during the summer month was attributed to the higher levels of solar irradiance experienced during this time, which outweighs the increased AC energy output. The low-performance ratio does not indicate technical issues but rather a mismatch between the load demand and PV generation. The results of this study highlight the need for a separate method to assess the performance of off-grid PV systems. Full article
(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)
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12 pages, 2984 KiB  
Article
Influence of Reaction Conditions on the Yield of Supercritical Multicomponent Thermal Fluids
by Wei Zhang, Zhilin Qi, Jie Tian, Fang Xu, Deyu Kong, Mingda Dong, Shenyao Yang and Wende Yan
Energies 2024, 17(19), 5012; https://doi.org/10.3390/en17195012 - 9 Oct 2024
Viewed by 363
Abstract
Supercritical multicomponent thermal fluid (scMCTF) is a novel medium with great potential for heavy oil thermal recovery. The production rate of scMCTF will affect the injection efficiency of thermal fluid, and then affect the development effect of thermal recovery. However, at present, there [...] Read more.
Supercritical multicomponent thermal fluid (scMCTF) is a novel medium with great potential for heavy oil thermal recovery. The production rate of scMCTF will affect the injection efficiency of thermal fluid, and then affect the development effect of thermal recovery. However, at present, there are few reports on the production rate of each component of scMCTF, and their understanding is not clear. According to the existing production rate data of supercritical water (scH2O) gasification products, based on the generation mechanism of scMCTF, the production rate of thermal fluid generation products under different generation conditions was calculated, and its influencing factors were identified. The results show the following: (1) The factors affecting the production rate of scMCTF generation products can be divided into three categories: reaction raw material factors, reaction condition factors, and catalytic factors. (2) The hydrocarbon number of raw material, reaction temperature, reaction time, and catalyst concentration were positively correlated with the production rate of the product. (3) The concentration of the reaction raw material is negatively correlated with the production rate of the product. The higher the concentration of the raw material is, the lower the concentration of H2O is, and the steam reforming reaction is inhibited, which leads to the decrease in the production rate. (4) The effect of reaction pressure and catalyst load on the product is not significant. (5) The reaction product production rate increased first and then decreased with the ratio of H2O to oil in the raw material emulsion and the ratio of preheated H2O to raw material discharge. (6) The effect of metal salt catalysts is relatively stable, and the catalytic effect of simple metal catalysts is significantly different under the action of different types of accelerators, so it is necessary to study the degree of synergization of different accelerators on the catalytic effect. The results can lay a foundation for the subsequent experimental and theoretical research design. Full article
(This article belongs to the Special Issue New Advances in Oil, Gas and Geothermal Reservoirs: 2nd Edition)
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16 pages, 3505 KiB  
Article
LCCO2 Assessment and Fertilizer Production from Absorbed-CO2 Solid Matter in a Small-Scale DACCU Plant
by Tianjiao Cheng, Takeji Hirota, Hiroshi Onoda and Andante Hadi Pandyaswargo
Energies 2024, 17(19), 5011; https://doi.org/10.3390/en17195011 - 9 Oct 2024
Viewed by 507
Abstract
This study investigates a novel method of utilizing Direct Air Capture (DAC) technology for fertilizer production. Unlike traditional Direct Air Carbon Capture and Utilization (DACCU) technologies, Direct Air Carbon Capture for Fertilizers (FDAC) has the potential to produce fertilizers directly. This study aims [...] Read more.
This study investigates a novel method of utilizing Direct Air Capture (DAC) technology for fertilizer production. Unlike traditional Direct Air Carbon Capture and Utilization (DACCU) technologies, Direct Air Carbon Capture for Fertilizers (FDAC) has the potential to produce fertilizers directly. This study aims to assess the feasibility of FDAC-based fertilizer production by examining the current state of traditional DAC technologies, evaluating the CO2 fixation potential of FDAC, and analyzing the decarbonization effect of producing fertilizers using FDAC. Our evaluation results indicate that CO2 emissions from producing 1 ton of conventional chemical fertilizer, FDAC fertilizer (current status), FDAC fertilizer with ingredient adjustment (sodium hydroxide), and FDAC fertilizer with ingredient adjustment (magnesium hydroxide) are 1.69, 1.12, 1.04, and 1.06 tons of CO2, respectively. The FDAC fertilizer (current status) emits 0.57 tons of CO2 per ton less than commercial fertilizers. FDAC fertilizers also have the potential to reduce CO2 emissions further when the fertilizer composition is adjusted, offering a promising solution for lowering the environmental impact of fertilizer production. Significant CO2 reduction can be expected by replacing conventional low-intensity chemical fertilizers with FDAC-produced fertilizers. Full article
(This article belongs to the Special Issue Carbon Capture, Storage and Utilization Technologies: Advances and Challenges)
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11 pages, 2294 KiB  
Article
CO2 Conversion by Oxygen-Enriched Gasification of Wood Chips
by Clemens Schmittmann and Peter Quicker
Energies 2024, 17(19), 5010; https://doi.org/10.3390/en17195010 - 9 Oct 2024
Viewed by 475
Abstract
With increasing efforts to lower CO2 emissions globally, the demand for carbon-based resources in industries remains on a high level, leading to new technologies being able to provide those essential carbon sources. To the best of our knowledge, we were able to [...] Read more.
With increasing efforts to lower CO2 emissions globally, the demand for carbon-based resources in industries remains on a high level, leading to new technologies being able to provide those essential carbon sources. To the best of our knowledge, we were able to show for the first time the adaption of a readily available gasifier for the gasification of wood chips using only O2 (18.4–23.1 Vol.-%) and CO2 as gasification agents, creating a nitrogen-free product gas. It was found that the setup used was able to convert up to 27.2% of the CO2 from the gasification agent to CO, creating a promising route for the production of renewable carbon sources for future carbon-based applications. Furthermore, no decrease in gasification performance was observed as the cold gas efficiency was at 83.5–95.5% with only minor formation of tar. Full article
(This article belongs to the Special Issue Advanced Bioenergy, Biomass and Waste Conversion Technologies)
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19 pages, 9356 KiB  
Article
Scaling Law of Flow and Heat Transfer Characteristics in Turbulent Radiative Rayleigh-Bénard Convection of Optically Thick Media
by Jiajun Song, Panxin Li, Lu Chen, Yuhang Zhao, Fengshi Tian and Benwen Li
Energies 2024, 17(19), 5009; https://doi.org/10.3390/en17195009 - 8 Oct 2024
Viewed by 663
Abstract
Radiative natural convection is of vital importance in the process of energy storage, power generation, and thermal storage technology. As the attenuation coefficients of many heat transfer media in these fields are high enough to be considered as optically thick media, like nanofluids [...] Read more.
Radiative natural convection is of vital importance in the process of energy storage, power generation, and thermal storage technology. As the attenuation coefficients of many heat transfer media in these fields are high enough to be considered as optically thick media, like nanofluids or molten salts in concentrated solar power or phase change thermal storage, Rosseland approximation is commonly used. In this paper, we delve into the impact of thermal radiation on the Rayleigh-Bénard (RB) convection. Theoretical analysis has been conducted by modifying the Grossmann-Lohse (GL) model. Based on turbulent dissipation theory, the corresponding scaling laws in four main regimes are proposed. Direct numerical simulation (DNS) was also performed, revealing that radiation exerts a notable influence on both flow and heat transfer, particularly on the formation of large-scale circulation. By comparing with DNS results, it is found that due to the presence of radiation, the modified Nu scaling law in small Pr range of the GL model is more suitable for predicting the transport characteristics of optical thick media with large Pr. The maximum deviation between the results of DNS and prediction model is about 10%, suggesting the summarized scaling law can effectively predict the Nu of radiative RB convection. Full article
(This article belongs to the Special Issue Advanced Technology for Solar Thermal Cooling, Heating, and Energy Storage)
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27 pages, 5679 KiB  
Article
Analysis of Optimal HVDC Back-to-Back Placement Based on Composite System Reliability
by Nanang Hariyanto, Niko B. Simamora, Kevin M. Banjar-Nahor and Hendry Timotiyas Paradongan
Energies 2024, 17(19), 5008; https://doi.org/10.3390/en17195008 - 8 Oct 2024
Viewed by 448
Abstract
HVDC is a promising interconnection solution for connecting asynchronous systems and ensuring power control. In Indonesia, a remote industrial system in Sumatra is experiencing load growth and has the option to draw power from the Sumatra system. However, due to frequency differences, the [...] Read more.
HVDC is a promising interconnection solution for connecting asynchronous systems and ensuring power control. In Indonesia, a remote industrial system in Sumatra is experiencing load growth and has the option to draw power from the Sumatra system. However, due to frequency differences, the use of HVDC is crucial. The Generation Expansion Planning has proposed six converters but not their interconnection points. This study will determine the most reliable interconnection locations. The chosen converters are modular multilevel converters (MMCs) with high modularity. The converter reliability modeling considers voltage levels, the number of modules, and redundancy strategies. This modeling is then implemented at the power system level to obtain the best placement at the available high-voltage (HV) substation options. Determining the best placement is based on the optimal reliability index. The optimal placement also includes the option to convert from HV to medium-voltage (MV) interconnection. MV interconnection offers higher flexibility but tends to be more expensive. The availability for HV converters is 99.69%, while for MV converters, it is slightly higher, at 99.81%. Additionally, converting from HV to MV reduces the SAIFI (system average interruption frequency index) from 0.2668 to 0.2284 occurrences per year, lowering the interruption cost from 7.804 million USD to 5.737 million USD per year. The sensitivity of interruption, investment, and maintenance costs shows that converting at least one HV converter to MV remains economical. In this case study, the optimal converter placement includes Area VI–2, recommended for conversion from HV to a more distributed MV configuration, improving reliability and economic efficiency. Full article
(This article belongs to the Special Issue The Planning, Operation and Control of Renewable Energy Power Grid)
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33 pages, 3482 KiB  
Review
Literature Review on Thermodynamic and Kinetic Limitations of Thermal Decomposition of Methane
by Andrzej Mianowski, Mateusz Szul, Tomasz Radko, Aleksander Sobolewski and Tomasz Iluk
Energies 2024, 17(19), 5007; https://doi.org/10.3390/en17195007 - 8 Oct 2024
Viewed by 475
Abstract
The state of the art in methane pyrolysis does not yet provide a definitive answer as to whether the concept of an elementary reaction is universally applicable to the apparently simple process of methane dissociation. Similarly, the literature currently lacks a comprehensive and [...] Read more.
The state of the art in methane pyrolysis does not yet provide a definitive answer as to whether the concept of an elementary reaction is universally applicable to the apparently simple process of methane dissociation. Similarly, the literature currently lacks a comprehensive and unambiguous description of the methane pyrolysis process and, in particular, a single model that would well represent its course at both the micro and macro scales. Given the wide range of conditions under which this reaction can occur—whether thermal or thermo-catalytic, in solid or fluidized bed reactors—it is crucial to evaluate the usefulness of different kinetic models and their compatibility with basic thermodynamic principles and design assumptions. To address these research gaps, the authors analysed the thermodynamic and kinetic dependencies involved in the thermal decomposition of methane, using the synthesis of methane from its elemental components and its reversibility as a basis for exploring suitable kinetic models. Using experimental data available in the literature, a wide range of kinetic models have been analysed to determine how they all relate to the reaction rate constant. It was found that regardless of whether the process is catalytic or purely thermal, for temperatures above 900 °C the reversibility of the reaction has a negligible effect on the hydrogen yield. This work shows how the determined kinetic parameters are consistent with the Kinetic Compensation Effect (KCE) and, by incorporating elements of Transition State Theory (TST), the possibility of the existence of Entropy–Enthalpy Compensation (EEC). The indicated correspondence between KCE and EEC is strengthened by the calculated average activation entropy at isokinetic temperature (∆SB=−275.0 J·(mol·K)−1). Based on these results, the authors also show that changes in the activation energy (E=20–421 kJ·mol−1) can only serve as an estimate of the optimal process conditions, since the isoconversion temperature (Tiso=1200−1450 K>Teq) is shown to depend not only on thermodynamic principles but also on the way the reaction is carried out, with temperature (T) and pressure (P) locally compensating each other. Full article
(This article belongs to the Section J: Thermal Management)
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17 pages, 3255 KiB  
Article
Bidding Strategy for the Alliance of Prosumer Aggregators in the Distribution Market
by Chunyi Wang, Jiawei Xing, Yuejiao Wang, Jing Xu, Zhixin Fu, Benjie Xu and Haoming Liu
Energies 2024, 17(19), 5006; https://doi.org/10.3390/en17195006 - 8 Oct 2024
Viewed by 420
Abstract
Photovoltaic energy storage system (PV-ESS) prosumer aggregators are characterized by a large number but small scale in the distribution system and are not competitive enough to participate in market transactions. For this reason, a prosumer aggregator alliance is proposed to participate in the [...] Read more.
Photovoltaic energy storage system (PV-ESS) prosumer aggregators are characterized by a large number but small scale in the distribution system and are not competitive enough to participate in market transactions. For this reason, a prosumer aggregator alliance is proposed to participate in the distribution market bidding strategy. Firstly, based on the framework for prosumer aggregator alliances participating in distribution market trading, a bilevel bidding model is constructed. The upper level represents the optimal decision-making model for the prosumer aggregators, while the lower level constitutes the distribution market-clearing model. Secondly, the additional benefits obtained by the alliance are distributed more fairly using the improved Shapley value based on the PV self-consumption rate. Given the problem that the traditional diagonalization algorithm (DA) has an excessive number of iterations when solving the game equilibrium problem of multiple subjects, the DA is improved by optimizing the initial value of the inputs. Finally, case studies are conducted based on the improved IEEE-33 bus distribution system to validate the feasibility and economic viability of the proposed strategy. The case study results show that forming cooperative alliances to participate in market bidding can significantly increase overall profits. The improved DA reduces the number of bids and computation time by 75% and 80%, respectively. Additionally, the improved Shapley value facilitates compensation for some of the aggregators. Full article
(This article belongs to the Special Issue Operation and Control of Distributed Power Resources Under Market Environment)
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17 pages, 5718 KiB  
Article
Analysis of Electricity Supply and Demand Balance in Residential Microgrids Integrated with Micro-CAES in Northern Portugal
by Jan Markowski, Jacek Leszczyński, Paula Fernanda Varandas Ferreira, Géremi Gilson Dranka and Dominik Gryboś
Energies 2024, 17(19), 5005; https://doi.org/10.3390/en17195005 - 8 Oct 2024
Viewed by 527
Abstract
As global energy demand continues to rise, integrating renewable energy sources (RES) into power systems has become increasingly important. However, the intermittent nature of RES, such as solar and wind, presents challenges for maintaining a stable energy supply. To address this issue, energy [...] Read more.
As global energy demand continues to rise, integrating renewable energy sources (RES) into power systems has become increasingly important. However, the intermittent nature of RES, such as solar and wind, presents challenges for maintaining a stable energy supply. To address this issue, energy storage systems are essential. One promising technology is micro-compressed air energy storage (micro-CAES), which stores excess energy as compressed air and releases it when needed to balance supply and demand. This study investigates the integration of micro-CAES with RES in a 19-home microgrid in northern Portugal. The research aims to evaluate the effectiveness of a microgrid configuration that includes 100 kW of solar PV, 70 kW of wind power, and a 50 kWh micro-CAES system. Using real-world data on electricity consumption and local renewable potential, a simulation is conducted to assess the performance of this system. The findings reveal that this configuration can supply up to 68.8% of the annual energy demand, significantly reducing reliance on the external grid and enhancing the system’s resilience. These results highlight the potential of micro-CAES to improve the efficiency and sustainability of small-scale renewable energy systems, demonstrating its value as a key component in future energy solutions. Full article
(This article belongs to the Section F1: Electrical Power System)
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18 pages, 2110 KiB  
Article
Solar Chimney Operation Variant
by Marta Gortych, Zygmunt Lipnicki, Tomasz Małolepszy and Piotr Grabas
Energies 2024, 17(19), 5004; https://doi.org/10.3390/en17195004 - 8 Oct 2024
Viewed by 398
Abstract
This paper presents a solar chimney that acts as a heat accumulator. It is based on its alternating charging (melting of the phase change material—PCM) and discharging (solidification), which helps to save energy and ensures stable operation of the solar chimney. In this [...] Read more.
This paper presents a solar chimney that acts as a heat accumulator. It is based on its alternating charging (melting of the phase change material—PCM) and discharging (solidification), which helps to save energy and ensures stable operation of the solar chimney. In this paper, special attention has been paid to the heat dissipation process (solidification of the PCM). The theoretical model of solidification has been solved in an original way. This paper presents a new simple theoretical model for the solidification of the PCM on a flat plate and presents the results of numerical tests. The theoretical model presents a method for determining the heat transfer coefficient at the solidification front of the PCM. In addition, the heat transfer coefficient from the flowing air to the outer surface of the solidifying front plate was determined experimentally in an original way. The heat transfer coefficient values resulting from the experiments may be employed in order to calculate the heat transfer coefficient for air flowing through the slot of the collector in the solar chimney. The calculated value of the heat transfer coefficient was 18.55 W/m²K. Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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28 pages, 2842 KiB  
Review
Heat Transfer Performance Factors in a Vertical Ground Heat Exchanger for a Geothermal Heat Pump System
by Khaled Salhein, C. J. Kobus, Mohamed Zohdy, Ahmed M. Annekaa, Edrees Yahya Alhawsawi and Sabriya Alghennai Salheen
Energies 2024, 17(19), 5003; https://doi.org/10.3390/en17195003 - 8 Oct 2024
Viewed by 726
Abstract
Ground heat pump systems (GHPSs) are esteemed for their high efficiency within renewable energy technologies, providing effective solutions for heating and cooling requirements. These GHPSs operate by utilizing the relatively constant temperature of the Earth’s subsurface as a thermal source or sink. This [...] Read more.
Ground heat pump systems (GHPSs) are esteemed for their high efficiency within renewable energy technologies, providing effective solutions for heating and cooling requirements. These GHPSs operate by utilizing the relatively constant temperature of the Earth’s subsurface as a thermal source or sink. This feature allows them to perform greater energy transfer than traditional heating and cooling systems (i.e., heating, ventilation, and air conditioning (HVAC)). The GHPSs represent a sustainable and cost-effective temperature-regulating solution in diverse applications. The ground heat exchanger (GHE) technology is well known, with extensive research and development conducted in recent decades significantly advancing its applications. Improving GHE performance factors is vital for enhancing heat transfer efficiency and overall GHPS performance. Therefore, this paper provides a comprehensive review of research on various factors affecting GHE performance, such as soil thermal properties, backfill material properties, borehole depth, spacing, U-tube pipe properties, and heat carrier fluid type and velocity. It also discusses their impact on heat transfer efficiency and proposes optimal solutions for improving GHE performance. Full article
(This article belongs to the Special Issue Advances in Refrigeration and Heat Pump Technologies)
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25 pages, 9915 KiB  
Article
Thermoelectric Materials: A Scientometric Analysis of Recent Advancements and Future Research Directions
by Sami M. Ibn Shamsah
Energies 2024, 17(19), 5002; https://doi.org/10.3390/en17195002 - 8 Oct 2024
Viewed by 585
Abstract
This scientometric study looks at the current trend in thermoelectric materials research and explores the evolving domain of thermoelectric materials research using a combination of bibliometric and scientometric methodologies. The analysis examines global research trends from a dataset of over 37,739 research articles, [...] Read more.
This scientometric study looks at the current trend in thermoelectric materials research and explores the evolving domain of thermoelectric materials research using a combination of bibliometric and scientometric methodologies. The analysis examines global research trends from a dataset of over 37,739 research articles, focusing on thematic evolution, annual growth rates, and significant contributions. Six principal research clusters were identified, encompassing energy conversion, material synthesis and nanostructures (the most prominent cluster), computational modeling and material properties, measurement and characterization, material performance enhancement, and material processing and microstructure. Each cluster highlights a critical aspect of the field, reflecting its broad scope and depth. The key findings reveal a marked annual increase in research output, highlighting the growing global importance of thermoelectric materials in sustainable energy solutions. This is especially evident in the significant contributions from China and the USA, emphasizing their leadership in the field. The study also highlights the collaborative nature of thermoelectric research, showing the impact of global partnerships and the synergistic effects of international collaboration in advancing the field. Overall, this analysis provides a comprehensive overview of the thermoelectric materials research landscape over the past decade, offering insights into trends, geographic contributions, collaborative networks, and research growth. The findings underscore thermoelectric materials’ vital role in addressing global energy challenges, highlighting recent advancements and industrial applications for energy efficiency and sustainability. Full article
(This article belongs to the Special Issue Recent Advances in Thermoelectric Energy Conversion)
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16 pages, 4458 KiB  
Article
Relevance-Based Reconstruction Using an Empirical Mode Decomposition Informer for Lithium-Ion Battery Surface-Temperature Prediction
by Chao Li, Yigang Kong, Changjiang Wang, Xueliang Wang, Min Wang and Yulong Wang
Energies 2024, 17(19), 5001; https://doi.org/10.3390/en17195001 (registering DOI) - 8 Oct 2024
Viewed by 577
Abstract
Accurate monitoring of lithium-ion battery temperature is essential to ensure these batteries’ efficient and safe operation. This paper proposes a relevance-based reconstruction-oriented EMD-Informer machine learning model, which combines empirical mode decomposition (EMD) and the Informer framework to estimate the surface temperature of 18,650 [...] Read more.
Accurate monitoring of lithium-ion battery temperature is essential to ensure these batteries’ efficient and safe operation. This paper proposes a relevance-based reconstruction-oriented EMD-Informer machine learning model, which combines empirical mode decomposition (EMD) and the Informer framework to estimate the surface temperature of 18,650 lithium-ion batteries during charging and discharging processes under complex operating conditions. Initially, based on 9000 data points from the U.S. NASA Prognostics Center of Excellence’s random battery-usage dataset, where each data point includes three features: temperature, voltage, and current, EMD is used to decompose the temperature data into intrinsic mode functions (IMFs). Subsequently, the IMFs are reconstructed into low-, medium-, and high-correlation components based on their correlation with the original data. These components, along with voltage and current data, are fed into sub-models. Finally, the model captures the long-term dependencies among temperature, voltage, and current. The experimental results show that, in single-step prediction, the mean squared error, mean absolute error, and maximum absolute error of the model’s predictions are 0.00095, 0.02114, and 0.32164 °C; these metrics indicate the accurate prediction of the surface temperature of lithium-ion batteries. In multi-step predictions, when the prediction horizon is set to 12 steps, the model achieves a hit rate of 93.57% where the maximum absolute error is within 0.5 °C; under these conditions, the model combines high predictive accuracy with a broad predictive range, which is conducive to the effective prevention of thermal runaway in lithium-ion batteries. Full article
(This article belongs to the Section D2: Electrochem: Batteries, Fuel Cells, Capacitors)
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35 pages, 2134 KiB  
Review
Geochemistry in Geological CO2 Sequestration: A Comprehensive Review
by Jemal Worku Fentaw, Hossein Emadi, Athar Hussain, Diana Maury Fernandez and Sugan Raj Thiyagarajan
Energies 2024, 17(19), 5000; https://doi.org/10.3390/en17195000 - 8 Oct 2024
Viewed by 737
Abstract
The increasing level of anthropogenic CO2 in the atmosphere has made it imperative to investigate an efficient method for carbon sequestration. Geological carbon sequestration presents a viable path to mitigate greenhouse gas emissions by sequestering the captured CO2 deep underground in [...] Read more.
The increasing level of anthropogenic CO2 in the atmosphere has made it imperative to investigate an efficient method for carbon sequestration. Geological carbon sequestration presents a viable path to mitigate greenhouse gas emissions by sequestering the captured CO2 deep underground in rock formations to store it permanently. Geochemistry, as the cornerstone of geological CO2 sequestration (GCS), plays an indispensable role. Therefore, it is not just timely but also urgent to undertake a comprehensive review of studies conducted in this area, articulate gaps and findings, and give directions for future research areas. This paper reviews geochemistry in terms of the sequestration of CO2 in geological formations, addressing mechanisms of trapping, challenges, and ways of mitigating challenges in trapping mechanisms; mineralization and methods of accelerating mineralization; and the interaction between rock, brine, and CO2 for the long-term containment and storage of CO2. Mixing CO2 with brine before or during injection, using microbes, selecting sedimentary reservoirs with reactive minerals, co-injection of carbonate anhydrase, and enhancing the surface area of reactive minerals are some of the mechanisms used to enhance mineral trapping in GCS applications. This review also addresses the potential challenges and opportunities associated with geological CO2 storage. Challenges include caprock integrity, understanding the lasting effects of storing CO2 on geological formations, developing reliable models for monitoring CO2–brine–rock interactions, CO2 impurities, and addressing public concerns about safety and environmental impacts. Conversely, opportunities in the sequestration of CO2 lie in the vast potential for storing CO2 in geological formations like depleted oil and gas reservoirs, saline aquifers, coal seams, and enhanced oil recovery (EOR) sites. Opportunities include improved geochemical trapping of CO2, optimized storage capacity, improved sealing integrity, managed wellbore leakage risk, and use of sealant materials to reduce leakage risk. Furthermore, the potential impact of advancements in geochemical research, understanding geochemical reactions, addressing the challenges, and leveraging the opportunities in GCS are crucial for achieving sustainable carbon mitigation and combating global warming effectively. Full article
(This article belongs to the Collection Feature Papers in Carbon Capture, Utilization, and Storage)
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1 pages, 133 KiB  
Correction
Correction: Ebner et al. Photovoltaic Roofing for Motorways and Other High-Ranking Road Networks: Technical Feasibility, Yield Estimation, and Final Demonstrator. Energies 2024, 17, 3991
by Rita Ebner, Christoph Mayr, Marcus Rennhofer, Karl A. Berger, Martin Heinrich, Felix Basler, Andreas J. Beinert, Jonas D. Huyeng, Manfred Haider, Dominik Prammer, Alois Vorwagner, Markus Fehringer and Tobias Beck
Energies 2024, 17(19), 4999; https://doi.org/10.3390/en17194999 - 8 Oct 2024
Viewed by 257
Abstract
In the published publication [...] Full article
(This article belongs to the Collection Renewable Energy and Energy Storage Systems)
18 pages, 4198 KiB  
Article
Two-Stage Optimization Model Based on Neo4j-Dueling Deep Q Network
by Tie Chen, Pingping Yang, Hongxin Li, Jiaqi Gao and Yimin Yuan
Energies 2024, 17(19), 4998; https://doi.org/10.3390/en17194998 - 8 Oct 2024
Viewed by 354
Abstract
To alleviate the power flow congestion in active distribution networks (ADNs), this paper proposes a two-stage load transfer optimization model based on Neo4j-Dueling DQN. First, the Neo4j graph model was established as the training environment for Dueling DQN. Meanwhile, the power supply paths [...] Read more.
To alleviate the power flow congestion in active distribution networks (ADNs), this paper proposes a two-stage load transfer optimization model based on Neo4j-Dueling DQN. First, the Neo4j graph model was established as the training environment for Dueling DQN. Meanwhile, the power supply paths from the congestion point to the power source point were obtained using the Cypher language built into Neo4j, forming a load transfer space that served as the action space. Secondly, based on various constraints in the load transfer process, a reward and penalty function was formulated to establish the Dueling DQN training model. Finally, according to the ε−greedy action selection strategy, actions were selected from the action space and interacted with the Neo4j environment, resulting in the optimal load transfer operation sequence. In this paper, Python was used as the programming language, TensorFlow open-source software library was used to form a deep reinforcement network, and Py2neo toolkit was used to complete the linkage between the python platform and Neo4j. We conducted experiments on a real 79-node system, using three power flow congestion scenarios for validation. Under the three power flow congestion scenarios, the time required to obtain the results was 2.87 s, 4.37 s and 3.45 s, respectively. For scenario 1 before and after load transfer, the line loss, voltage deviation and line load rate were reduced by about 56.0%, 76.0% and 55.7%, respectively. For scenario 2 before and after load transfer, the line loss, voltage deviation and line load rate were reduced by 41.7%, 72.9% and 56.7%, respectively. For scenario 3 before and after load transfer, the line loss, voltage deviation and line load rate were reduced by 13.6%, 47.1% and 37.7%, respectively. The experimental results show that the trained model can quickly and accurately derive the optimal load transfer operation sequence under different power flow congestion conditions, thereby validating the effectiveness of the proposed model. Full article
(This article belongs to the Section F1: Electrical Power System)
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21 pages, 1904 KiB  
Article
Evaluating Microgrid Investments: Introducing the MPIR Index for Economic and Environmental Synergy
by Agis M. Papadopoulos and Maria Symeonidou
Energies 2024, 17(19), 4997; https://doi.org/10.3390/en17194997 - 8 Oct 2024
Viewed by 444
Abstract
In view of the increasing environmental challenges and the growing demand for sustainable energy solutions, the optimization of microgrid systems with regard to economic efficiency and environmental compatibility is becoming ever more important. This paper presents the Microgrid Performance and Investment Rating (MPIR) [...] Read more.
In view of the increasing environmental challenges and the growing demand for sustainable energy solutions, the optimization of microgrid systems with regard to economic efficiency and environmental compatibility is becoming ever more important. This paper presents the Microgrid Performance and Investment Rating (MPIR) index, a novel assessment framework developed to link economic and environmental objectives within microgrid configurations. The MPIR index evaluates microgrid configurations based on five critical dimensions: financial viability, sustainability, regional renewable integration readiness, energy demand, and community engagement, facilitating comprehensive and balanced decision making. The current cases focus on the area of Greece; however, the model can have a wider application. Developed using a two-target optimization model, this index integrates various energy sources—including photovoltaics, micro-wind turbines, and different types of batteries—with advanced energy management strategies to assess and improve microgrid performance. This paper presents case studies in which the MPIR index is applied to different microgrid scenarios. It demonstrates its effectiveness in identifying optimal configurations that reduce the carbon footprint while maximizing economic returns. The MPIR index provides a quantifiable, scalable tool for stakeholders, not only advancing the field of microgrid optimization, but also aligning with global sustainability goals and promoting the transition to a more resilient and sustainable energy future. Full article
(This article belongs to the Special Issue Techno-Economic Analysis and Optimization for Energy Systems: 2nd Edition on the Way to Green Transition)
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16 pages, 6232 KiB  
Article
An Approach to Estimate the Temperature of an Induction Motor under Nonlinear Parameter Perturbations Using a Data-Driven Digital Twin Technique
by Yu Luo, Liguo Wang, Denis Sidorov, Aliona Dreglea and Elena Chistyakova
Energies 2024, 17(19), 4996; https://doi.org/10.3390/en17194996 - 8 Oct 2024
Viewed by 441
Abstract
To monitor temperature as a function of varying inductance and resistance, we propose a data-driven digital twin approach for the rapid and efficient real-time estimation of the rotor temperature in an induction motor. By integrating differential equations with online signal processing, the proposed [...] Read more.
To monitor temperature as a function of varying inductance and resistance, we propose a data-driven digital twin approach for the rapid and efficient real-time estimation of the rotor temperature in an induction motor. By integrating differential equations with online signal processing, the proposed data-driven digital twin approach is structured into three key stages: (1) transforming the nonlinear differential equations into discrete algebraic equations by substituting the differential operator with the difference quotient based on the sampled voltage and current; (2) deriving approximate analytical solutions for rotor resistance and stator inductance, which can be utilized to estimate the rotor temperature; and (3) developing a general procedure for obtaining approximate analytical solutions to nonlinear differential equations. The feasibility and validity of the proposed method were demonstrated by comparing the test results with a 1.5 kW AC motor. The experimental results indicate that our method achieves a minimum estimation error that falls within the standards set by IEC 60034-2-1. This work provides a valuable reference for the overheating protection of induction motors where direct temperature measurement is challenging. Full article
(This article belongs to the Section F: Electrical Engineering)
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21 pages, 1080 KiB  
Article
Heating Energy Performance Gap in Vulnerable Households: Identification and Impact of Associated Variables
by Sebastián Seguel-Vargas, Carlos Rubio-Bellido, Lucía Pereira-Ruchansky and Alexis Pérez-Fargallo
Energies 2024, 17(19), 4995; https://doi.org/10.3390/en17194995 - 8 Oct 2024
Viewed by 463
Abstract
Reducing energy consumption in the construction sector is urgently needed. In Chile, where income distribution is unequal and the cost of energy is high, energy demand is seriously affected, especially in vulnerable households. Hence, it is essential to establish public policies with more [...] Read more.
Reducing energy consumption in the construction sector is urgently needed. In Chile, where income distribution is unequal and the cost of energy is high, energy demand is seriously affected, especially in vulnerable households. Hence, it is essential to establish public policies with more realistic energy-saving goals to address this situation. However, reliably predicting the energy performance of buildings remains a challenge. For this reason, this study aims to identify and evaluate the impact of the variables associated with energy performance in vulnerable households in Central-Southern Chile and propose values that would reduce the gap. A sensitivity analysis was conducted to achieve this, adjusting the energy performance parameters in a base model with data analyzed using local standards. In addition, field information was collected in 93 households to obtain the actual energy consumption. The main results show that the variables that most impacted performance were infiltration, COP, heating setpoints, and schedules, which generated a 60% difference between the theoretical and actual consumption. Full article
(This article belongs to the Special Issue Building Energy Audits-Diagnosis and Retrofitting towards Decarbonization and Sustainable Cities II)
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11 pages, 2792 KiB  
Article
Optimizing Microgrid Load Fluctuations through Dynamic Pricing and Electric Vehicle Flexibility: A Comparative Analysis
by Mahdi A. Mahdi, Ahmed N. Abdalla, Lei Liu, Rendong Ji, Haiyi Bian and Tao Hai
Energies 2024, 17(19), 4994; https://doi.org/10.3390/en17194994 - 8 Oct 2024
Viewed by 570
Abstract
In the context of modern power systems, the reliance on a single-time-of-use electricity pricing model presents challenges in managing electric vehicle (EV) charging in a way that can effectively accommodate the variable supply and demand patterns, particularly in the presence of wind power [...] Read more.
In the context of modern power systems, the reliance on a single-time-of-use electricity pricing model presents challenges in managing electric vehicle (EV) charging in a way that can effectively accommodate the variable supply and demand patterns, particularly in the presence of wind power generation. This often results in undesirable peak–valley differences in microgrid load profiles. To address this challenge, this paper introduces an innovative approach that combines time-of-use electricity pricing with the flexible energy storage capabilities of electric vehicles. By dynamically adjusting the time-of-use electricity prices and implementing a tiered carbon pricing system, this paper presents a comprehensive strategy for formulating optimized charging and discharging plans that leverage the inherent flexibility of electric vehicles. This approach aims to mitigate the fluctuations in the microgrid load and enhance the overall grid stability. The proposed strategy was simulated and compared with the no-incentive and single-incentive strategies. The results indicate that the load peak-to-trough difference was reduced by 30.1% and 18.6%, respectively, verifying its effectiveness and superiority. Additionally, the increase in user income and the reduction in carbon emissions verify the need for the development of EVs in tandem with clean energy for environmental benefits. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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15 pages, 5045 KiB  
Article
Numerical Investigation of Wind Turbine Airfoil Icing and Its Influencing Factors under Mixed-Phase Conditions
by Xiang Wang, Yiyao Ru, Huanyu Zhao and Zhengzhi Wang
Energies 2024, 17(19), 4993; https://doi.org/10.3390/en17194993 - 7 Oct 2024
Viewed by 539
Abstract
Icing is a popular research area in wind energy, and the icing problem of the supercooled droplet–ice crystal mixed-phase condition is one of the new challenges. A numerical method for analyzing the icing characteristics of wind turbine airfoil under mixed-phase conditions is presented. [...] Read more.
Icing is a popular research area in wind energy, and the icing problem of the supercooled droplet–ice crystal mixed-phase condition is one of the new challenges. A numerical method for analyzing the icing characteristics of wind turbine airfoil under mixed-phase conditions is presented. The control equations for the dynamics of supercooled droplets and ice crystals are formulated using the Lagrangian method. Equations for the conservation of mass and energy during the icing process involving supercooled droplets and ice crystals are constructed. The impact of erosion phenomena on the mixed-phase icing process is examined, and methodologies for solving the control equations are introduced. The numerical method is utilized for modeling mixed-phase icing under a range of conditions. The results of these simulations are then compared with data obtained from icing wind tunnel tests to assess the validity of the method. The influence of various mixed-phase conditions on ice shapes is studied. It is found that higher icing temperatures correspond to a larger icing range and amount. The increase in supercooled droplet content, ice crystal content, and ice crystal diameter all contribute to enhanced ice accretion. However, the effects of ice crystal content and diameter are relatively minor. Full article
(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
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16 pages, 7326 KiB  
Article
A Lyapunov Theory-Based SEIG–STATCOM Voltage Regulation Control Strategy
by Zeyu Zhang, Pingping Gong and Ziguang Lu
Energies 2024, 17(19), 4992; https://doi.org/10.3390/en17194992 - 7 Oct 2024
Viewed by 520
Abstract
To improve the voltage regulation of asynchronous generators during load switching, a Lyapunov-based control strategy has been proposed to stabilize the generator’s voltage by connecting a static synchronous compensator. By constructing a Lyapunov function from the mathematical model, the error tracking problem is [...] Read more.
To improve the voltage regulation of asynchronous generators during load switching, a Lyapunov-based control strategy has been proposed to stabilize the generator’s voltage by connecting a static synchronous compensator. By constructing a Lyapunov function from the mathematical model, the error tracking problem is transformed into a global asymptotic stability problem of the Lyapunov function at the equilibrium point. The outer loop linearizes the direct current (DC) voltage control process, while the inner loop replaces integral terms with differential terms. The proposed Lyapunov method achieves linearized voltage control with a quadratic outer loop structure and the inner loop differential structure exhibits a shorter transient process, outperforming traditional methods. Simulation and experimental tests were then used, where the latter was a down-scale laboratory prototype experiment. Compared to traditional (voltage-oriented control) VOC, the outer loop (Lyapunov-function-based control) LBC reduces the DC voltage transient processes by approximately 9.4 milliseconds, while the inner loop LBC reduces both alternating current (AC) and DC voltage transient processes by approximately 2.6 ms and 8.7 ms, respectively. Full article
(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)
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15 pages, 4697 KiB  
Article
Energy Flux Method for Wave Energy Converters
by Gabriel Thomas Scarlett, James Cameron McNatt, Alan Henry and Abel Arredondo-Galeana
Energies 2024, 17(19), 4991; https://doi.org/10.3390/en17194991 - 6 Oct 2024
Viewed by 851
Abstract
Hydrodynamic tools reveal information as to the behaviour of a device in the presence of waves but provide little information on how to improve or optimise the device. With no recent work on the transfer of power (energy flux) from a wave field [...] Read more.
Hydrodynamic tools reveal information as to the behaviour of a device in the presence of waves but provide little information on how to improve or optimise the device. With no recent work on the transfer of power (energy flux) from a wave field through the body surface of a wave energy converter (WEC), we introduce the energy flux method to map the flow of power. The method is used to develop an open-source tool to visualise the energy flux density on a WEC body surface. This energy flux surface can also be used to compute the total power capture by integrating over the surface. We apply the tool to three WEC classes: a heaving cylinder, a twin-hulled hinged barge, and pitching surge devices. Using the flux surfaces, we investigate power efficiency in terms of power absorbed to power radiated. We visualise the hydrodynamic consequence of sub-optimal damping. Then, for two pitching surge devices with similar resonant peaks, we reveal why one device has a reduced power performance in a wave spectrum compared to the other. The results show the effectiveness of the energy flux method to predict power capture compared to motion-based methods and highlight the importance of assessing the flux of energy in WECs subjected to different damping strategies. Importantly, the tool can be adopted for a wide range of applications, from geometry optimisation and hydrodynamic efficiency assessment to structural design. Full article
(This article belongs to the Special Issue New Advances in Wave Energy Conversion)
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15 pages, 1964 KiB  
Article
On the Use of the Multi-Site Langmuir Model for Predicting Methane Adsorption on Shale
by Zhe Wu, Yuan Ji, Ke Zhang, Li Jing and Tianyi Zhao
Energies 2024, 17(19), 4990; https://doi.org/10.3390/en17194990 - 6 Oct 2024
Viewed by 541
Abstract
Shale gas, mainly consisting of adsorbed gas and free gas, has served a critical role of supplying the growing global natural gas demand in the past decades. Considering that the adsorbed methane has contributed up to 80% of the total gas in place [...] Read more.
Shale gas, mainly consisting of adsorbed gas and free gas, has served a critical role of supplying the growing global natural gas demand in the past decades. Considering that the adsorbed methane has contributed up to 80% of the total gas in place (GIP), understanding the methane adsorption behaviors is imperative to an accurate estimation of total GIP. Historically, the single-site Langmuir model, with the assumption of a homogeneous surface, is commonly applied to estimate the adsorbed gas amount. However, this assumption cannot depict the methane adsorption characteristics due to various compositions and pore sizes of shales. In this work, a multi-site model integrating the energetic heterogeneity in adsorption is derived to predict methane adsorption on shale. Our results show that the multi-site model is capable of addressing the heterogeneity of shales by a wide range of adsorption energy distributions (owing to the complex compositions and different pore sizes), which is different from the single-site model only characterized by single adsorption energy. Consequently, the multi-site model results have better accuracy against the experimental data. Therefore, applying the multi-site Langmuir model for estimating GIP in shales can achieve more accurate results compared with using the traditionally single-site model. Full article
(This article belongs to the Section H: Geo-Energy)
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21 pages, 9077 KiB  
Article
The Low-Carbon Path of Active Distribution Networks: A Two-Stage Model from Day-Ahead Reconfiguration to Real-Time Optimization
by Taorong Jia, Guoqing Yang and Lixiao Yao
Energies 2024, 17(19), 4989; https://doi.org/10.3390/en17194989 - 6 Oct 2024
Viewed by 487
Abstract
The integration of renewable energy sources and distributed energy storage systems increasingly complicates the operation of distribution networks, while stringent carbon reduction targets demand low-carbon operational strategies. To address these complexities, this paper introduces a two-stage model for reconfiguring distribution networks and ensuring [...] Read more.
The integration of renewable energy sources and distributed energy storage systems increasingly complicates the operation of distribution networks, while stringent carbon reduction targets demand low-carbon operational strategies. To address these complexities, this paper introduces a two-stage model for reconfiguring distribution networks and ensuring low-carbon dispatch. Initially, second-order cone programming is employed to minimize losses in the network. Subsequently, the outputs of renewable energy and energy storage systems are optimized using the mantis search algorithm (MSA) to achieve low-carbon dispatch, with the network’s carbon potential as the evaluation metric. The proposed model demonstrates a significant reduction in average active power loss by 34.85%, a decrease in daily carbon emissions by 509.97 kg, and a reduction in carbon emission costs by 17.24%, thereby markedly enhancing the economic and social benefits of grid operations. Full article
(This article belongs to the Section F3: Power Electronics)
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43 pages, 2718 KiB  
Review
Enhancing Energy Systems and Rural Communities through a System of Systems Approach: A Comprehensive Review
by Abdellatif Soussi, Enrico Zero, Alessandro Bozzi and Roberto Sacile
Energies 2024, 17(19), 4988; https://doi.org/10.3390/en17194988 - 6 Oct 2024
Viewed by 1329
Abstract
Today’s increasingly complex energy systems require innovative approaches to integrate and optimize different energy sources and technologies. In this paper, we explore the system of systems (SoS) approach, which provides a comprehensive framework for improving energy systems’ interoperability, efficiency, and resilience. By examining [...] Read more.
Today’s increasingly complex energy systems require innovative approaches to integrate and optimize different energy sources and technologies. In this paper, we explore the system of systems (SoS) approach, which provides a comprehensive framework for improving energy systems’ interoperability, efficiency, and resilience. By examining recent advances in various sectors, including photovoltaic systems, electric vehicles, energy storage, renewable energy, smart cities, and rural communities, this study highlights the essential role of SoSs in addressing the challenges of the energy transition. The principal areas of interest include the integration of advanced control algorithms and machine learning techniques and the development of robust communication networks to manage interactions between interconnected subsystems. This study also identifies significant challenges associated with large-scale SoS implementation, such as real-time data processing, decision-making complexity, and the need for harmonized regulatory frameworks. This study outlines future directions for improving the intelligence and autonomy of energy subsystems, which are essential for achieving a sustainable, resilient, and adaptive energy infrastructure. Full article
(This article belongs to the Special Issue Empowering Rural Communities: Control Strategies for a Sustainable and Resilient Energy Future)
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