Energies

21 pages, 2788 KB

Open AccessArticle

Effect of Standardized Driving-Cycle Characteristics on Control Performance and Energy Efficiency of a PID-Controlled Hybrid Electric Vehicle

by Tomasz Wołowiec, Dmytro Mironov, Oleg Lyashuk, Volodymyr Martyniuk, Marcin Gąsior, Artur Lutsyk, Ivan Gevko and Mariana Lyashuk

Energies 2026, 19(12), 2923; https://doi.org/10.3390/en19122923 (registering DOI) - 20 Jun 2026

Abstract

The influence of standardized driving-cycle characteristics on the dynamic and energy performance of a parallel hybrid electric vehicle controlled by a fixed-gain PID speed controller was investigated. A control-oriented MATLAB/Simulink model was developed, including an electric traction subsystem, an electric battery pack, a [...] Read more.

The influence of standardized driving-cycle characteristics on the dynamic and energy performance of a parallel hybrid electric vehicle controlled by a fixed-gain PID speed controller was investigated. A control-oriented MATLAB/Simulink model was developed, including an electric traction subsystem, an electric battery pack, a simplified internal combustion engine subsystem, a supervisory torque-split controller and longitudinal vehicle dynamics. The same controller configuration was evaluated under the FTP75, HWFET and US06 cycles, with the shorter cycles repeated to obtain comparable durations. Control quality was assessed using RMSE, MAE, IAE and ITAE, whereas energy performance was quantified using battery state-of-charge variation, fuel consumption, engine utilization and traction motor current loading. FTP75 yielded favorable performance, with RMSE = 0.265 m/s, fuel consumption of 4.824 L/100 km and an SoC decrease of 19.698%, whereas US06 proved severe, with RMSE = 4.567 m/s, fuel consumption of 10.328 L/100 km, an SoC decrease of 41.630% and a peak motor current of 580.9 A. Sensitivity analysis showed that ±20% PID-gain variations do not materially alter the principal conclusion, while supervisory energy-management parameters exert a stronger influence on the trade-off between tracking quality, fuel expenditure and charge maintenance. The results confirm that fixed-gain PID control is cycle-dependent and becomes inadequate under aggressive driving conditions. Full article

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27 pages, 2122 KB

Open AccessArticle

Scenario-Based Multi-Objective Optimisation for Rural Electrification Under Carbon, Economic, and Equity Constraints

by Desmond Eseoghene Ighravwe, Olubayo Babatunde, Oludolapo Akanni Olanrewaju and Emmanuel Adetiba

Energies 2026, 19(12), 2922; https://doi.org/10.3390/en19122922 (registering DOI) - 20 Jun 2026

Abstract

Rural electrification in Sub-Saharan Africa faces a trilemma: cutting carbon emissions, making it economically viable, and achieving fair access to energy for all. This paper develops a multi-objective framework that optimises carbon revenue, net present value (NPV), total energy supply, cooking fuel (firewood [...] Read more.

Rural electrification in Sub-Saharan Africa faces a trilemma: cutting carbon emissions, making it economically viable, and achieving fair access to energy for all. This paper develops a multi-objective framework that optimises carbon revenue, net present value (NPV), total energy supply, cooking fuel (firewood and LPG), health costs, and benefit to society. The model uses continuous decision variables: daily energy allocation among four sources (solar, generator, firewood, LPG) to three population groups (men, women, children). The case study is a rural community of 7000 people in Nigeria (Tier 1 energy consumers). Six policy scenarios are considered: baseline, high carbon price, low carbon price, microfinance, government subsidy and community cooperative. This study compared algorithms and identified a hybrid Non-dominated Sorting Genetic Algorithm and Particle Swarm Optimisation II as the most suitable algorithm for solving the formulated optimisation problem. It was found that NPV and unit cost of energy would increase to $175,500 and 26.4 ¢/kWh, respectively, by increasing the price of carbon from $8/ton to $12/ton. Firewood generates health savings and carbon revenue in the range of $4100–$12,270/year. Prices below $8/ton do not induce optimal reconfigurations in the system. The best energy supply (2825 kWh/day) and the lowest unsatisfied demand occur in the government subsidy scenario with the greatest disparity index, displaying an equity-efficiency trade-off. The framework shows that sustainable access to energy can be unlocked using strategic integration of carbon finance, valuation of health benefits and equity constraints. Full article

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38 pages, 39943 KB

Open AccessArticle

Measurement-Driven Phase-Resolved Modeling of Unbalanced Nonlinear Loads for Harmonic Assessment and Mitigation in Building Distribution Systems

by Nestor F. Guerrero-Rodríguez, Rafael Omar Batista-Jorge, Vrindarani Nuñez-Ramírez, Abraham Manilla-García, Francisco A. Ramírez-Rivera, Robert Mercado-Ravelo, Julio A. Ferreira and Juan G. Faxas-Guzmán

Energies 2026, 19(12), 2921; https://doi.org/10.3390/en19122921 (registering DOI) - 20 Jun 2026

Abstract

Nonlinear loads in modern buildings are often represented using balanced or frequency-domain approximations that do not fully capture phase asymmetry and time-domain distortion observed under field operating conditions. This study aims to develop and validate a measurement-driven phase-resolved modeling framework for unbalanced three-phase [...] Read more.

Nonlinear loads in modern buildings are often represented using balanced or frequency-domain approximations that do not fully capture phase asymmetry and time-domain distortion observed under field operating conditions. This study aims to develop and validate a measurement-driven phase-resolved modeling framework for unbalanced three-phase nonlinear loads and to evaluate its usefulness for harmonic-mitigation assessment using shunt active power filters (SAPFs). In situ voltage and current waveforms were acquired in a university building using a Class S power-quality analyzer and embedded in MATLAB/Simulink as time-domain signals to preserve harmonic content, waveform shape, and phase-dependent behavior. Model accuracy was assessed using RMSE and range-normalized RMSE, yielding a mean RN_RMSE of 1.36% across representative loads, with simulated THD_I deviations of approximately 1–3 percentage points relative to the measurements. The measured load signatures were then used to evaluate three SAPF configurations under representative load-specific operating conditions. The results show that mean THD_I was reduced from 39.25% before compensation to 2.28% after compensation, with all the post-filter phase values remaining below 5%, consistent with IEEE Std 519-2022. The findings show that phase-resolved measurement-based load models provide a practical basis for harmonic assessment and SAPF-oriented mitigation studies in low-voltage building distribution systems with heterogeneous and unbalanced nonlinear loads. Full article

(This article belongs to the Section F: Electrical Engineering)

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22 pages, 1470 KB

Open AccessArticle

Predicting District Heating Networks Fault Location with Graph Neural Networks

by Ivan Plokhikh, Dmitriy Pushkarev, Oleg Gobyzov, Sergey Filimonov, Alexander Dekterev, Rustam Mullyadzhanov and Sergey Alekseenko

Energies 2026, 19(12), 2920; https://doi.org/10.3390/en19122920 (registering DOI) - 20 Jun 2026

Abstract

District heating networks (DHNs) are critical infrastructure prone to physical failures such as leakage-related faults, which cause significant energy and financial losses. Traditional physics-based monitoring methods are computationally expensive and require the continual recalibration of complex mathematical models, while standard data-driven approaches often [...] Read more.

District heating networks (DHNs) are critical infrastructure prone to physical failures such as leakage-related faults, which cause significant energy and financial losses. Traditional physics-based monitoring methods are computationally expensive and require the continual recalibration of complex mathematical models, while standard data-driven approaches often fail due to the scarcity of real-world sensor data. This study addresses these challenges by proposing a topology-aware graph neural network (GNN) architecture for fault localization. The methodology follows a two-stage process: first, a graph attention-based architecture is designed and optimized using a synthetic dataset to effectively capture multi-step neighborhood dependencies. Second, the model is adapted and evaluated on a physically simulated dataset of a real urban DHN, comprising 187 nodes and 42,570 operational states. The problem is formulated as a multi-class classification task across supply and return subnets. The results demonstrate high predictive performance, achieving an accuracy of 96% on the supply subnet and 91% on the return subnet. Analysis of prediction errors reveals a strong bias towards local topological mistakes, indicating the model’s ability to capture the physical propagation of disturbances. These findings highlight the efficacy of GNNs in handling sparse data and exploiting network topology for robust DHN monitoring. Full article

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28 pages, 1529 KB

Open AccessArticle

Strategy to Reduce Production Cost of Carbon-Free Hydrogen Using Positive Imbalances of Renewable Power Plants

by Masashi Matsubara, Masahiro Mae, Tsuyoshi Yoshioka, Ryuji Matsuhashi, Toshiyuki Ito and Daisuke Sawaki

Energies 2026, 19(12), 2919; https://doi.org/10.3390/en19122919 (registering DOI) - 20 Jun 2026

Abstract

Towards achieving carbon neutrality, it is important to produce carbon-free hydrogen from renewables at an acceptable cost. At the same time, power retailers that own renewables must manage their imbalances between planned and actual generation. This paper proposes an economically viable carbon-free hydrogen [...] Read more.

Towards achieving carbon neutrality, it is important to produce carbon-free hydrogen from renewables at an acceptable cost. At the same time, power retailers that own renewables must manage their imbalances between planned and actual generation. This paper proposes an economically viable carbon-free hydrogen method for such retailers, utilizing both positive imbalances of renewables and electricity from the market with non-fossil certificates. The proposed method enables geographically flexible hydrogen production through the power grid while utilizing renewable imbalances within actual power business operations. This paper develops solutions to an optimization problem that minimizes the hydrogen variable cost and offsets the imbalances using an electrolyzer and a battery while accounting for imbalance uncertainty. The case study in Tokyo, Japan demonstrates that imbalance compensation reduces the hydrogen variable cost by 30%. The minimum levelized cost of hydrogen (LCOH) is approximately 60 JPY/Nm

^{3}

when the electrolyzer operates at a 40% capacity factor. Furthermore, sensitivity analysis of market prices indicates that the LCOH can decline to 50 JPY/Nm

^{3}

under lower price conditions. The results suggest that market-independent cost components, such as wheeling and renewable energy charges and non-fossil certificates, remain major obstacles to further reducing hydrogen costs. Full article

(This article belongs to the Special Issue Advances in Green Hydrogen Energy Production)

16 pages, 1777 KB

Open AccessArticle

Study on Analytical Model of Heat Transfer and Long-Term Operation Characteristics of Energy Tunnels

by Zhigang Shi, Zheng Xu, Chaozheng Wang, Yu Wang, Shiwei Xia, Lin Zhang, Jin Tu and Peng He

Energies 2026, 19(12), 2918; https://doi.org/10.3390/en19122918 (registering DOI) - 20 Jun 2026

Abstract

Existing studies on energy tunnels mainly focus on short-term heat transfer and neglect long-term thermal accumulation. This paper establishes a one-dimensional unsteady heat transfer model using Robin boundary conditions, considering air–lining coupled heat transfer and seasonal tunnel air temperature variations. The model is [...] Read more.

Existing studies on energy tunnels mainly focus on short-term heat transfer and neglect long-term thermal accumulation. This paper establishes a one-dimensional unsteady heat transfer model using Robin boundary conditions, considering air–lining coupled heat transfer and seasonal tunnel air temperature variations. The model is verified with experimental and numerical results, and the relative error is less than 1%. Simulations of 20-year continuous operation show that the host rock temperature presents obvious periodic fluctuations. The thermal influence zone expands rapidly at the initial operation stage and gradually stabilizes. Sensitivity analysis indicates that thermal conductivity, air flow velocity and circulating fluid velocity significantly affect the long-term thermal performance. Higher thermal conductivity speeds up heat diffusion, higher air velocity strengthens convective heat transfer, and higher fluid velocity improves heat exchange efficiency but increases pumping consumption. The model can accurately predict long-term temperature evolution, providing theoretical support for the design and operation optimization of energy tunnels. Full article

32 pages, 9166 KB

Open AccessArticle

Vibration Assessment Due to Stator and Rotor Interturn Faults in a Doubly Fed Induction Generator for Wind Turbine Application

by Aakriti Gupta and Thanga Raj Chelliah

Energies 2026, 19(12), 2917; https://doi.org/10.3390/en19122917 (registering DOI) - 20 Jun 2026

Abstract

All rotating electrical machines are susceptible to vibrations arising from electromagnetic (EM) forces, electrical faults, mechanical defects, imbalance, and structural resonance. In Doubly Fed Induction Generators (DFIGs), such electromechanical vibrations are especially important because they can degrade reliability, increase noise, and lead to [...] Read more.

All rotating electrical machines are susceptible to vibrations arising from electromagnetic (EM) forces, electrical faults, mechanical defects, imbalance, and structural resonance. In Doubly Fed Induction Generators (DFIGs), such electromechanical vibrations are especially important because they can degrade reliability, increase noise, and lead to severe damage if resonance-prone operating conditions are not identified in time. Although fault diagnosis in DFIGs has been widely investigated using current, voltage, and flux signatures, comparatively fewer studies have examined fault-specific vibration behaviour under stator and rotor interturn faults (ITTFs), particularly through a coupled EM structural framework. In addition, prior vibration-based studies have not examined the influence of end winding ITTFs, its location, severity, and modal interaction investigating resonance risk. This paper considers vibration characteristics of a variable-speed 2.8 MW DFIG used in a grid-connected Type-3 wind turbine unit (WTU) at no-load operating condition. The DFIG is modelled in ANSYS Academic Research v 2022 R2 Maxwell for EM behaviour assessment for ITTFs in both stator and rotor windings along with modal analysis (MA) in ANSYS Workbench to examine the undamped stator and rotor modes over a range of frequencies. This coupled approach enables identification of vibration signatures associated with different ITTF types. The results show the magnetic flux density near faulty end-winding region increases with fault severity and ranges from 4.19 T to 4.39 T in proximity to faulty windings. A dominant modal frequency band of 60–65 Hz is identified, where stator and rotor modes coincide, creating probable resonance conditions. A severe vibration response is observed for single-phase stator ITTF, showing an amplitude of 2116 mm/s at 480 Hz for a larger number of shorted turns, indicating that asymmetric faults can produce stronger EM excitation than multi-phase faults. The main contribution of this paper is demonstration of a fault-specific, MA and vibration-based Condition monitoring system (CMS) implementation workflow for a DFIG. Unlike prior vibration-based studies that primarily focus on general machine vibration, mechanical faults, bearings, etc., this paper links stator and rotor ITTF induced EM excitation to modal characteristics, resonance behaviour, and measurable vibration signatures, establishing vibration analysis (VA) as a practical complementary technique for CMS of ITTFs in DFIGs. Full article

(This article belongs to the Special Issue Reliability and Condition Monitoring of Electric Motors and Drives: 2nd Edition)

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24 pages, 20052 KB

Open AccessArticle

An Analysis of Market Subsidy Costs for Utility-Scale Renewable Energy Generation in the UK

by Donald R. Noble, Simon Olsson, Kristofer Grattan and Henry Jeffrey

Energies 2026, 19(12), 2916; https://doi.org/10.3390/en19122916 (registering DOI) - 20 Jun 2026

Abstract

Renewable energy technologies have historically been offered market support to facilitate their deployment and aid the transition away from fossil fuels. This work shows the costs of subsidising utility-scale renewable electricity generation in the UK, focusing on wind, solar and tidal stream technologies [...] Read more.

Renewable energy technologies have historically been offered market support to facilitate their deployment and aid the transition away from fossil fuels. This work shows the costs of subsidising utility-scale renewable electricity generation in the UK, focusing on wind, solar and tidal stream technologies in the Renewables Obligation (RO) and Contracts for Difference (CfD) schemes. The subsidy of each technology is calculated using published data, including an estimate of committed costs over the full project lifetime, which is not always assessed. For the technologies considered, the RO supported 24.8 GW of installed capacity at a lifetime cost of about £103 bn. To date, CfD have been awarded for 45.3 GW of wind, solar and tidal stream, with total lifetime cost of £40 bn, although this is sensitive to future gas generation costs, with a range of £8–71 bn. The CfD scheme offers better value for money to consumers than the previous RO schemes, and this is true for all technologies assessed. By design, the CfD also helps to insulate billpayers from spikes in the wholesale market caused by high fossil fuel prices, decoupling the costs of electricity from gas. Credible scenarios for future deployment out to 2050 are also presented, along with discussion of potential socioeconomic benefits and the mechanisms to achieve these. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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20 pages, 4768 KB

Open AccessArticle

Design and Cooling Performance Analysis of a Coupled Solar Ventilation Evaporative Cooling System for Hot and Arid Climates

by Faris Alqurashi, Rached Nciri, Chaouki Ali and Faouzi Nasri

Energies 2026, 19(12), 2915; https://doi.org/10.3390/en19122915 (registering DOI) - 20 Jun 2026

Abstract

This study investigates numerically a Coupled Solar Ventilation Evaporative Cooling system for hot and arid climates. The system uses a solar wall chimney to produce natural ventilation and generate hot and dry airflow, which is then directed through a roof-mounted humid hay packed [...] Read more.

This study investigates numerically a Coupled Solar Ventilation Evaporative Cooling system for hot and arid climates. The system uses a solar wall chimney to produce natural ventilation and generate hot and dry airflow, which is then directed through a roof-mounted humid hay packed bed to enhance evaporative air conditioning. The resulting cold is transferred via a thermally conductive inner roof plate while a membrane condenser recovers moisture for reusing. A mathematical model was developed to describe heat and mass transfer in the hay packed bed, including solar chimney airflow, pressure drop and the evaporation energy balance. Parametric simulations were carried out for inlet air temperature of 40–60 °C, airflow rates of 0.25–0.45 m³/s, hay moisture contents of 0.006–0.014 kg/kg dry basis and air humidity ratio of 0.002–0.006 kg/kg dry air. Results show that evaporative cooling becomes effective only above certain inlet temperature. Increasing airflow from 0.25 to 0.45 m³/s reduced hay temperature from 30 to 26.8 °C when inlet air temperature exceeded 43.5 °C. Higher hay moisture content enhanced cooling performance, reaching about 26 °C, while higher inlet air humidity reduced evaporation and limited cooling. The operating maps obtained from the numerical simulations provide practical guidance for preliminary system sizing and for optimal operating parameters selection in solar-driven evaporative cooling systems. The mathematical model treats the solar chimney, the evaporative packed bed, the conditioned room and the membrane condenser within the same steady state calculation. The solar energy balance and the pressure balance are used to relate the inlet air temperature and the airflow rate to solar irradiance, ambient temperature and chimney geometry. The model also includes the heat transferred from the room through the roof plate, the sensible heat of the supplied water and the mass transfer and pressure drop effects of the membrane condenser. Full article

(This article belongs to the Special Issue Design, Modeling, and Testing of Heating, Ventilation, and Air Conditioning (HVAC) and Building Energy Systems for Energy Efficiency)

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31 pages, 3447 KB

Open AccessArticle

Variable Time Scale Dispatch Strategy for Multi-Microgrid Active Distribution Systems Based on a Hybrid Game

by Yudong Wang, Fan Tang, Hancong Guo, Chao Yang, Yingli Wei and Qibao Kang

Energies 2026, 19(12), 2914; https://doi.org/10.3390/en19122914 (registering DOI) - 20 Jun 2026

Abstract

With the increasing penetration of renewable energy generation (REG) in novel distribution systems, active distribution networks (ADNs) integrated with microgrids (MGs) play a crucial role in enhancing the flexibility of regulation resources and promoting the accommodation of REG. To meet the operational requirements [...] Read more.

With the increasing penetration of renewable energy generation (REG) in novel distribution systems, active distribution networks (ADNs) integrated with microgrids (MGs) play a crucial role in enhancing the flexibility of regulation resources and promoting the accommodation of REG. To meet the operational requirements for efficient collaboration between ADNs and MGs under different dispatch time scales, this paper proposes a collaborative optimal dispatch strategy for multi-microgrid active distribution systems based on a hybrid game and variable time scales. Firstly, a transaction operation framework is constructed for the distribution network operator (DNO) and a multi-microgrid alliance (MMA), considering the peer-to-peer (P2P) transaction mode. On this basis, a day-ahead hybrid game model with a two-layer structure is constructed, the upper layer is a master–slave game with the DNO as the leader and the MMA as the follower, while the lower layer is a cooperative game for MGs within the MMA. An asymmetric Nash bargaining strategy based on contribution degree in P2P transactions is introduced to ensure equitable benefit allocation among cooperative MGs. Secondly, an intra-day rolling optimization model for reactive power and voltage based on variable time scales is proposed, which enhances the system’s responsiveness to real-time source–load power fluctuations by dynamically adjusting the dispatch time scale. Finally, the alternating direction method of multipliers (ADMM), integrated with a strategy separation mechanism, is adopted to efficiently solve the hybrid game model involving numerous 0–1 variables. The case study results indicate that, under the proposed strategy, the MMA’s power purchase cost from the DNO and ESS operational cost are decreased by 9.7% and 11.6%, respectively, while the system’s average deviation rate of node voltage decreases by 0.82%. Therefore, the proposed collaborative dispatch strategy can not only effectively reduce the system’s operational cost and ensure voltage stability but also significantly promote the accommodation of REG. Full article

(This article belongs to the Special Issue Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids: 2nd Edition)

21 pages, 5751 KB

Open AccessArticle

Proposal of a Decentralized Consensus-Based P2P Electricity Trading Methodology That Takes into Account Consumer Equipment Operations

by Hyuya Koshikawa and Shintaro Negishi

Energies 2026, 19(12), 2913; https://doi.org/10.3390/en19122913 (registering DOI) - 20 Jun 2026

Abstract

With increasing penetration of distributed energy resources, peer-to-peer (P2P) electricity trading has attracted attention for locally utilizing surplus renewable energy. This paper proposes a distributed consensus-based P2P electricity trading method that explicitly considers prosumer equipment operation constraints. Each prosumer autonomously solves a daily [...] Read more.

With increasing penetration of distributed energy resources, peer-to-peer (P2P) electricity trading has attracted attention for locally utilizing surplus renewable energy. This paper proposes a distributed consensus-based P2P electricity trading method that explicitly considers prosumer equipment operation constraints. Each prosumer autonomously solves a daily scheduling problem considering electricity demand, PV generation, battery operation, grid purchase and sale, and P2P trades with neighboring prosumers. P2P prices and desired trading quantities are iteratively adjusted through local information exchange. After convergence, bidirectional trades are converted into net one-way trades, and the final feasible daily schedule is obtained by re-optimizing with fixed trading quantities. Numerical simulations were conducted for six low-voltage prosumers using annual residential demand data and a representative daily PV generation profile. In the base case, the proposed method reduced annual electricity cost by 13.7% compared with the no-P2P case, while its total cost was only 2.3% higher than that of the centralized benchmark. Unlike the centralized benchmark, which increased costs for some prosumers, the proposed method reduced costs for all prosumers. Wheeling-charge sensitivity analysis showed that the charge affects P2P trading volume and benefit allocation. Future work will address tariff design, PV uncertainty, scalability, and distribution-network constraints. Full article

(This article belongs to the Section F2: Distributed Energy System)

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33 pages, 10688 KB

Open AccessArticle

Lithium-Ion Battery Thermal Runaway Propagation Simulation Using Joint Model of Lumped-Parameter Method for Shell and 3D Modeling for Jelly Roll

by Xinying Liu, Zeyu Li and Zhantang Lin

Energies 2026, 19(12), 2912; https://doi.org/10.3390/en19122912 (registering DOI) - 20 Jun 2026

Abstract

Models of thermal runaway propagation in lithium-ion batteries are widely used for thermal safety analysis. Current methods, primarily lumped-parameter and 3D models, face challenges in balancing accuracy with computational efficiency. Three-dimensional models offer high accuracy at high computational cost, while lumped-parameter models are [...] Read more.

Models of thermal runaway propagation in lithium-ion batteries are widely used for thermal safety analysis. Current methods, primarily lumped-parameter and 3D models, face challenges in balancing accuracy with computational efficiency. Three-dimensional models offer high accuracy at high computational cost, while lumped-parameter models are faster but less accurate. For instance, the battery shell is included in lumped-parameter models but often omitted in 3D models. This study focuses on a 37 Ah ternary lithium-ion battery, with Li(NiCoMn)_1/3O₂ as the cathode material and graphite as the anode material. The propagation of thermal runaway in the battery array is triggered by nail penetration. A lithium-ion battery thermal runaway propagation model is proposed, combining the lumped-parameter method with 3D modeling. The model primarily describes the heat transfer characteristics of the shell using a series connection of thermal capacitance and several thermal resistances. The shell temperature is then calculated by weighting the temperatures associated with the thermal capacitance and thermal resistances using specific weight coefficients. The joint model is detailed and applied to study thermal runaway propagation in one- and two-dimensional battery arrays. For the one-dimensional array, based on the three-dimensional simulation data and calculation time, the joint model shows only a 1.32% average deviation in propagation time compared to full 3D simulation, while maintaining good temperature agreement. It also reduces solution time by 70.22%. These findings confirm that the proposed model effectively enhances both the efficiency and accuracy of thermal runaway simulations, supporting improved safety analysis for lithium-ion battery systems. Full article

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19 pages, 2957 KB

Open AccessReview

Renewable and Citizen Energy Communities in the European Union: A Structured Review of Legal Frameworks, Implementation Barriers and Anchor-Prosumer Pathways in Romania

by Andrei Glămeanu, Iuliana Niță, Mircea Scripcariu and Cristian Gheorghiu

Energies 2026, 19(12), 2911; https://doi.org/10.3390/en19122911 (registering DOI) - 20 Jun 2026

Abstract

Energy communities (ECs) are becoming a key institutional instrument for decentralizing the European energy transition, yet their implementation remains constrained by fragmented legal interpretation, uneven national transposition, and unresolved socio-technical coordination problems. This review synthesizes the peer-reviewed literature, EU primary legal texts, and [...] Read more.

Energy communities (ECs) are becoming a key institutional instrument for decentralizing the European energy transition, yet their implementation remains constrained by fragmented legal interpretation, uneven national transposition, and unresolved socio-technical coordination problems. This review synthesizes the peer-reviewed literature, EU primary legal texts, and national legislation to clarify the distinction between Renewable Energy Communities (RECs) and Citizen Energy Communities (CECs), alongside the amendment relationship between the RED II and RED III directives. The analysis demonstrates that the scalability of these initiatives depends less on theoretical legal recognition and more on aligning operational frameworks, including metering, settlement, cybersecurity, and equitable allocation rules. The Romanian case illustrates this challenge clearly: rapid prosumer growth creates valuable distributed generation but also exposes physical grid constraints, asymmetric socio-economic participation capacity, and weak experience with cooperative energy governance. To address these vulnerabilities, this paper contributes a focused analytical framework linking energy justice, peer-to-peer game-theoretic modeling, and the strategic integration of “anchor-prosumers.” The study argues that larger renewable self-consumers can act as stabilizing community anchors when internal energy prices are designed between wholesale export values and retail import prices, thereby improving both producer incentives and consumer affordability. Future research developments, including targeted surveys and longitudinal empirical validations, will sustain this claim and optimize the socio-economic resilience of decentralized energy markets. Full article

(This article belongs to the Special Issue Research Studies on Combined Heat and Power Systems)

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17 pages, 4934 KB

Open AccessArticle

Research on the Peak of Terminal Energy Consumption and Carbon Emissions of Civil Buildings in Anhui Province

by Guotao Zhu, Haowei Hu, Zihao Wang, Donghong Wang, Yimiao Wu and Huidi Huang

Energies 2026, 19(12), 2910; https://doi.org/10.3390/en19122910 (registering DOI) - 19 Jun 2026

Abstract

Buildings account for nearly 30% of global energy-related carbon emissions. In rapidly developing economies, the operational phase of buildings represents a major and growing source of emissions. However, emission pathways in hot-summer-cold-winter (HSCW) regions remain understudied. This study analyzes carbon emission peaks and [...] Read more.

Buildings account for nearly 30% of global energy-related carbon emissions. In rapidly developing economies, the operational phase of buildings represents a major and growing source of emissions. However, emission pathways in hot-summer-cold-winter (HSCW) regions remain understudied. This study analyzes carbon emission peaks and influencing factors in the operational phase of existing civilian buildings in Anhui Province. It integrates energy balance tables, the LEAP model, carbon emission factors, and the STIRPAT model. The energy balance table method disaggregates building energy consumption into urban, rural residential and public sectors. It adjusts for transportation energy by deducting specific proportions of gasoline and diesel from industrial, commercial, and residential sectors. Heating energy calculations are simplified because the region has a HSCW climate with limited centralized heating. The LEAP model projects emissions under four scenarios from 2020 to 2060. The STIRPAT model with ridge regression reveals that the permanent population and energy structure negatively influence residential emissions with elasticities of −2.646 and −1.465, respectively. This finding is consistent with the province’s energy transition, where coal use dropped from 28.48% in 2005 to 0.45% in 2020 and electricity use rose from 39.86% to 59.01%. In contrast, per capita GDP, building area, and energy intensity show positive effects. For public buildings, tertiary industry added value and energy structure are key determinants. Scenario analysis identifies the blueprint scenario as optimal, with residential emissions peaking at 34.29 million tons in 2025 and declining to 9.19 million tons by 2060 through measures such as 10% building retrofits by 2025, 75% energy-saving standards for new constructions, 50% retrofits by 2060, and renewable energy integration with building electrification, outperforming the baseline scenario that peaks in 2036 at 49.46 million tons and other intermediate scenarios. The study underscores that energy structure optimization significantly decouples energy consumption from emissions, offering actionable pathways for dual carbon goals through policy synergies in building efficiency, population management, and clean energy adoption to foster sustainable development and the construction industry’s low-carbon transition. Full article

(This article belongs to the Section B3: Carbon Emission and Utilization)

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17 pages, 10141 KB

Open AccessArticle

An Experimental Investigation of Power Quality Effects on Torque Pulsations in an Induction Motor

by Marcin Pepliński and Dariusz Świsulski

Energies 2026, 19(12), 2909; https://doi.org/10.3390/en19122909 (registering DOI) - 19 Jun 2026

Abstract

Voltage disturbances occur frequently in power systems. The most important voltage disturbances are voltage unbalance, voltage deviation, and voltage waveform distortions. Voltage waveform distortions are usually considered harmonics, but subharmonics and interharmonics may also occur. Voltage subharmonics are components with frequencies lower than [...] Read more.

Voltage disturbances occur frequently in power systems. The most important voltage disturbances are voltage unbalance, voltage deviation, and voltage waveform distortions. Voltage waveform distortions are usually considered harmonics, but subharmonics and interharmonics may also occur. Voltage subharmonics are components with frequencies lower than the fundamental frequency. In contrast, voltage interharmonics are components of the frequency spectrum that are higher than the fundamental frequency and are not integer multiples of it. Voltage fluctuations are the superposition of the first voltage harmonic and subharmonic components. This work analysed the shaft torque pulses of an induction motor under single-subharmonic action or under periodic voltage fluctuations combined with voltage unbalance. The experimental results were compared with results from previous work. We also analysed the influence of voltage disturbances on the selection of the coupling connecting the induction motor to the working machine. Full article

(This article belongs to the Special Issue Modern Aspects of the Design and Operation of Electric Machines)

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17 pages, 573 KB

Open AccessArticle

Integrated Transfer Learning and Reinforcement Learning for Reactive Current Injection During Voltage Sags

by Mohana Fathollahi, Antonio Camacho Santiago and Cecilio Angulo

Energies 2026, 19(12), 2908; https://doi.org/10.3390/en19122908 (registering DOI) - 19 Jun 2026

Abstract

Modern power grids with high renewable energy penetration are vulnerable to fast voltage disturbances caused by grid faults. Among these, voltage sags are critical because they develop within milliseconds and require rapid reactive current support to maintain grid stability and power reliability. Reinforcement [...] Read more.

Modern power grids with high renewable energy penetration are vulnerable to fast voltage disturbances caused by grid faults. Among these, voltage sags are critical because they develop within milliseconds and require rapid reactive current support to maintain grid stability and power reliability. Reinforcement learning has previously shown potential for reactive current injection control during voltage sag events due to its fast response and adaptability to changing system conditions. However, existing approaches rely on separate policies for specific subsets of the operating space, which limits their ability to provide optimal actions when the system operates across broader or combined state regions. To address this limitation, this paper proposes a unified Soft Actor–Critic (SAC) target policy trained over the full state and action space by integrating multi-source transfer learning with potential-based reward shaping approach. Results show that the proposed multi-source transfer approach enables the target agent to converge faster and reach a higher reward solution than the baseline SAC and single-source transfer approach. The trained policy also improved prediction accuracy, achieving reactive-current errors below 0.2 A with respect to the ground-truth reference generated through extensive simulations over the full observation and action space. The reference follows the grid-code requirement for minimum reactive current injection during faults and provides a benchmark for evaluating prediction accuracy. This can help distributed generation sources respond more effectively during severe perturbations such as voltage sags, support voltage recovery, and reduce the risk of cascaded disconnections that could lead to unwanted blackouts. Additionally, the inference execution time is also sufficiently fast to satisfy the response-time requirement of voltage sag events, confirming the real-time feasibility of the proposed controller. Full article

(This article belongs to the Section F5: Artificial Intelligence and Smart Energy)

27 pages, 45969 KB

Open AccessArticle

A Synergistic Hybrid CPCM–Liquid Thermal Management System for High-Power Battery Modules

by Temesgen Abera Takiso, Jianwu Yu and Girum Girma Bizuneh

Energies 2026, 19(12), 2907; https://doi.org/10.3390/en19122907 (registering DOI) - 19 Jun 2026

Abstract

Rising demand for high-performance battery thermal management systems (BTMSs) has rendered single-mode cooling insufficient for advanced lithium-ion batteries (LIBs) in new energy vehicles (NEVs), particularly under high discharge rates. This study proposes a synergistic hybrid BTMS integrating composite phase-change material (CPCM)–aluminum foam with [...] Read more.

Rising demand for high-performance battery thermal management systems (BTMSs) has rendered single-mode cooling insufficient for advanced lithium-ion batteries (LIBs) in new energy vehicles (NEVs), particularly under high discharge rates. This study proposes a synergistic hybrid BTMS integrating composite phase-change material (CPCM)–aluminum foam with liquid cooling to enhance thermal regulation of cylindrical battery modules under 5 C discharge conditions. Multiple liquid-cooled plate (LCP) configurations, including serpentine, straight, and leaf-shaped designs, together with different flow channel topologies (FCTs), were systematically investigated and optimized. The effects of coolant flow speed (CFS) and ambient temperature were also analyzed. Results indicate that the optimized leaf-shaped LCP with FCT #2 delivers superior performance, limiting the maximum temperature to 309.98 K, reducing temperature difference by 7.6%, and decreasing pressure drop by 88.79% compared to the serpentine configuration. Increasing CFS improves heat dissipation and delays PCM melting, although it raises pressure losses. Furthermore, the proposed system maintains a cell-to-cell temperature difference below 0.51 K, indicating excellent thermal uniformity. Compared to a CPCM-only system, the hybrid BTMS reduces peak temperature by 8.81 K under elevated ambient conditions (309.15 K), demonstrating strong potential for reliable and efficient thermal management in demanding operating environments. Full article

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40 pages, 8365 KB

Open AccessArticle

Knowledge Discovery-Driven Intelligent Decision-Making System to Establish Public Building Envelope Prioritizing Strategies: Case Study on Romanian Building Stock

by Gheorghe Grigoras, Romeo-Cristian Ciobanu, Bogdan-Constantin Neagu, Mihaela Aradoaei, Razvan-Petru Livadariu and Alina Ruxandra Caramitu

Energies 2026, 19(12), 2906; https://doi.org/10.3390/en19122906 (registering DOI) - 19 Jun 2026

Abstract

The energy performance of a building reflects its typical energy use and is influenced by factors such as the building envelope (insulation and windows), system efficiency (particularly for heating, cooling, and domestic hot water), and the integration of renewable energy sources. Improving energy [...] Read more.

The energy performance of a building reflects its typical energy use and is influenced by factors such as the building envelope (insulation and windows), system efficiency (particularly for heating, cooling, and domestic hot water), and the integration of renewable energy sources. Improving energy performance helps save energy, boost energy independence and security, lower energy costs, and reduce the need for grid investments. Standardizing energy performance assessments enables benchmarking and comparison of building efficiency, encouraging informed decision-making. In this context, the paper presents a knowledge discovery-driven intelligent decision-making system, designed, developed, and tested to identify the best strategies for prioritizing buildings in the envelope process. The system combines data mining techniques with statistical analysis to precisely rank and thoroughly evaluate low-energy-performance buildings and to develop scenario-based strategies for enveloping the buildings to achieve high energy efficiency (associated with nearly zero-energy buildings) under real-world conditions. Testing of the proposed intelligent decision-making system was conducted using a real building database of approximately 3900 records, uploaded from the Romanian central administration website. Under the highest-performance scenario of the envelope-priority strategy, which includes nearly zero-energy building standards, energy savings exceeded 50% across all categories: 51.70% for healthcare, 53.40% for residential, 60.11% for administrative and office buildings, and 69.92% for educational institutions. Overall, the average savings across all building types were 59.81% (644.86 GWh/year). Full article

(This article belongs to the Special Issue Green Buildings and Community Energy Management)

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16 pages, 1868 KB

Open AccessArticle

Estimating Leakage Inductance in High-Frequency Transformers Using an Artificial Neural Network and a Gray Wolf Optimizer-Based Hybrid Algorithm

by Seda Kul, Hamza Yapıcı, Selami Balci and Farhad Shahnia

Energies 2026, 19(12), 2905; https://doi.org/10.3390/en19122905 (registering DOI) - 19 Jun 2026

Abstract

The trend in the power electronics industry toward higher power density and efficiency has brought high-frequency transformers (HFTs) to the forefront of critical applications, including isolated DC–DC converters, electric vehicle chargers, and solid-state transformers. This paper focuses on the leakage inductance of HFTs [...] Read more.

The trend in the power electronics industry toward higher power density and efficiency has brought high-frequency transformers (HFTs) to the forefront of critical applications, including isolated DC–DC converters, electric vehicle chargers, and solid-state transformers. This paper focuses on the leakage inductance of HFTs and presents a systematic comparative framework that evaluates five surrogate modeling and hybrid optimization approaches for the rapid and accurate estimation of leakage inductance. A comprehensive parametric dataset was constructed, comprising 1210 finite element analysis simulations conducted via finite element analysis in the ANSYS Maxwell 2024 R1 environment, varying the number of winding turns, primary winding thickness, and secondary winding thickness of the HFT. All five methods were trained and evaluated on the same dataset under identical conditions. The comparative evaluation demonstrates that the proposed hybrid Gray Wolf optimizer–artificial neural network (GWO-ANN) framework achieved the highest prediction accuracy (R² = 0.9832, MSE = 0.01780, MAE = 0.0935 µH) and the fastest convergence among all tested approaches. The generalization capability of the proposed model was confirmed through blind validation tests across six geometric configurations spanning the full range of the design space, yielding a maximum prediction error of 8.15% and an average error of 2.14%. The functional validity of the proposed parameters was further tested in a third validation layer using MATLAB/Simulink R2024b transformer circuit studies, demonstrating a theoretical efficiency of 96.06%. This three-layer validation approach proves both the parametric and functional reliability of the proposed framework for HFT designs. Full article

(This article belongs to the Section F: Electrical Engineering)

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