Energies

17 pages, 13332 KB

Open AccessArticle

Weight-Adaptable Disturbance Observer for Continuous-Control-Set Model Predictive Control of NPC-3L-Fed PMSMs

by Zhenyan Liang, Jiang Wang, Yitong Wu and Zhen Zhang

Energies 2025, 18(21), 5864; https://doi.org/10.3390/en18215864 - 6 Nov 2025

Viewed by 391

This paper presents a cascaded control strategy for neutral-point-clamped three-level (NPC-3L) inverter-fed permanent magnet synchronous motors (PMSMs), integrating continuous-control-set model-predictive control (CCS-MPC) with mid-point voltage regulation and an online Lyapunov-stable neural-network (NN) disturbance observer. The outer CCS-MPC loop optimizes voltage vector application for [...] Read more.

This paper presents a cascaded control strategy for neutral-point-clamped three-level (NPC-3L) inverter-fed permanent magnet synchronous motors (PMSMs), integrating continuous-control-set model-predictive control (CCS-MPC) with mid-point voltage regulation and an online Lyapunov-stable neural-network (NN) disturbance observer. The outer CCS-MPC loop optimizes voltage vector application for accurate current tracking and harmonic suppression, while the inner loop balances mid-point voltage by adjusting the dwell times of P/N small-voltage vectors (VVs). The NN-based disturbance observer compensates parameter mismatches in real time, reducing steady-state dq-axis current errors. To validate the effectiveness of the proposed strategy, experiments are conducted using a three-phase PMSM fed by three-phase NPC-3L inverters. Experimental results demonstrate substantial improvements in mid-point voltage balance, current quality, and robustness against model uncertainties. Full article

(This article belongs to the Collection State-of-the-Art of Electrical Power and Energy System in China)

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33 pages, 2428 KB

Open AccessArticle

Methodology for Evaluating and Comparing Different Sustainable Energy Generation and Storage Systems for Residential Buildings—Application to the Case of Spain

by Oscar Castillo Campo and Roberto Álvarez Fernández

Energies 2025, 18(21), 5863; https://doi.org/10.3390/en18215863 - 6 Nov 2025

Viewed by 496

Abstract

This paper focuses on assessing different sustainable energy generation and storage systems for residential buildings in Spain, identifying the best-performing system according to the end-user requirements. As outlined by the consulted literature, the authors have selected two types of hybrid configurations—a Photovoltaic System [...] Read more.

This paper focuses on assessing different sustainable energy generation and storage systems for residential buildings in Spain, identifying the best-performing system according to the end-user requirements. As outlined by the consulted literature, the authors have selected two types of hybrid configurations—a Photovoltaic System with Battery Backup (PSBB) and a Photovoltaic System with Hydrogen Hybrid Storage Backup (PSHB)—and a Grid-Based System with Renewable Hydrogen Contribution (GSHC) is proposed. A Fuzzy Analytical Hierarchy Process methodology (FAHP) is employed for evaluating the hybrid power systems from a multi-criteria approach: acquisition, operational, and environmental. The main requirements for selecting the optimal system are organized under these criteria and evaluated using key performance indicators. This methodology allows the selection of the best option considering objective and subjective system performance indicators. Beyond establishing the ranking, a sensitivity analysis was conducted to provide insights into how individual criteria influence the ranking of the hybrid power systems alternatives. The results demonstrate that the selection of hybrid power systems for a residential building is highly dependent on consumer preferences, but the PSBB system scores highly in operation and acquisition criteria, while the GSHC has good performance in all the criteria. Full article

(This article belongs to the Special Issue Sustainable Energy Transition: Urban Planning and Climate Change)

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16 pages, 2469 KB

Open AccessArticle

Wide-Band Characteristic Analysis and Compensation Research of Electromagnetic Current Transformer

by Xingyan Wu, Zhenhua Li, Zhenxing Li, Lei Zhang and Chenyi Yang

Energies 2025, 18(21), 5862; https://doi.org/10.3390/en18215862 - 6 Nov 2025

Viewed by 263

Abstract

In order to realize the wide frequency applicability of the electromagnetic current transformer in a ‘double high’ power system, the equivalent circuit model of the electromagnetic current transformer under wide frequency is established. The complex permeability method is used to obtain the excitation [...] Read more.

In order to realize the wide frequency applicability of the electromagnetic current transformer in a ‘double high’ power system, the equivalent circuit model of the electromagnetic current transformer under wide frequency is established. The complex permeability method is used to obtain the excitation impedance value on the basis of the existing core parameters. Secondly, according to the equivalent circuit of the current transformer in the broadband domain, the error transfer function of the electromagnetic current transformer is derived. Through simulation calculation, the ratio difference and angle difference in the electromagnetic current transformer at 50 Hz–3000 Hz are obtained. The correctness of the theoretical analysis and simulation model is verified by comparing it with the existing model and measurement. The simulation and test results show that the electromagnetic current transformer has good linearity when the frequency is in the frequency range of 50 to 650 Hz. When the frequency exceeds this frequency, the ratio difference and angle difference in the current transformer will not reach the accuracy standard, which indicates that it is difficult to accurately measure the high frequency current. Aiming at the correlation of frequency characteristics, this paper proposes a method of optimizing parameters, which provides a certain reference for the error compensation and structural design of electromagnetic current transformers. Full article

(This article belongs to the Special Issue Advances in Diagnostic Analysis, Strategic Management, and Proactive Maintenance of Electrical Equipment)

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21 pages, 531 KB

Open AccessArticle

An Efficient Heuristic Algorithm for Stochastic Multi-Timescale Network Reconfiguration for Medium- and High-Voltage Distribution Networks with High Renewables

by Wanjun Huang, Mingrui Xu, Xinran Zhang and Le Zheng

Energies 2025, 18(21), 5861; https://doi.org/10.3390/en18215861 - 6 Nov 2025

Viewed by 454

Abstract

To handle the uncertainties brought by the increasing penetration of renewable energy sources and random loads, we design a stochastic multi-timescale distribution network reconfiguration (SMTDNR) framework to coordinate diverse scheduling resources across different timescales and develop an efficient heuristic algorithm to solve this [...] Read more.

To handle the uncertainties brought by the increasing penetration of renewable energy sources and random loads, we design a stochastic multi-timescale distribution network reconfiguration (SMTDNR) framework to coordinate diverse scheduling resources across different timescales and develop an efficient heuristic algorithm to solve this complex NP-hard combinatorial optimization problem with high efficiency for medium- and high-voltage distribution networks. First, the SMTDNR problem, incorporating distributed renewable generators, fuel generators, energy storage systems, and controllable loads, is simplified through circular constraint linearization, Jabr relaxation, and second-order cone (SOC) relaxation techniques. Then, a one-stage multi-timescale successive branch reduction (MTSBR) algorithm is developed for distribution networks with one redundant branch, which transforms the SMTDNR problem into a stochastic multi-timescale optimal power flow (SMTOPF) problem. This is extended to a two-stage MTSBR algorithm for general networks with multiple redundant branches, which iteratively runs the proposed one-stage MTSBR algorithm. Numerical results on modified IEEE 33-bus and 123-bus distribution networks validate the superior optimality, feasibility, and computational efficiency of the proposed algorithms, particularly in scenarios of high renewable penetration and increased uncertainty, offering robust and feasible solutions where traditional methods may fail. Full article

(This article belongs to the Special Issue Advances in Machine Learning Applications in Stability Analysis and Optimal Operation of Power Systems)

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23 pages, 3886 KB

Open AccessArticle

Multi-Step Sky Image Prediction Using Cluster-Specific Convolutional Neural Networks for Solar Forecasting Applications

by Stylianos P. Schizas, Markos A. Kousounadis-Knousen, Francky Catthoor and Pavlos S. Georgilakis

Energies 2025, 18(21), 5860; https://doi.org/10.3390/en18215860 - 6 Nov 2025

Viewed by 359

Abstract

Effective integration of photovoltaic (PV) systems into electric power grids presents significant challenges due to the inherent variability in solar energy. Therefore, accurate PV power forecasting in various timescales is critical for the reliable operation of modern electric power systems. For short-term horizons, [...] Read more.

Effective integration of photovoltaic (PV) systems into electric power grids presents significant challenges due to the inherent variability in solar energy. Therefore, accurate PV power forecasting in various timescales is critical for the reliable operation of modern electric power systems. For short-term horizons, the primary source of solar power stochasticity is cloud movement and deformation, which are typically captured at high spatiotemporal resolutions using ground-based sky images. In this paper, we propose a novel multi-step sky image prediction framework for improved cloud tracking, which can be deployed for short-term PV power forecasting. The proposed method is based on deep learning, but instead of being purely data-driven, we propose a hybrid approach where we combine Auto-Encoder-like Convolutional Neural Networks (AE-like CNNs) with physics-informed sky image clustering to enhance robustness towards fast-varying sky conditions and effectively model non-linearities without adding to the computational overhead. The proposed method is compared against several state-of-the-art approaches using a real-world case study comprising minutely sky images. The experimental results show improvements of up to 17.97% on structural similarity and 62.14% on mean squared error, compared to persistence. These findings demonstrate that by combining effective physics-informed preprocessing with deep learning, multi-step ahead sky image forecasting can be reliably achieved even at low temporal resolutions. Full article

(This article belongs to the Special Issue Challenges and Progresses of Electric Power Systems)

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20 pages, 3194 KB

Open AccessArticle

Assessing the Viability of Rooftop Solar PV in Energy-Intensive Industries: A Techno-Economic and Safety Framework for the Indonesian FMCG Sector

by Almaaidah Puri Galevien, Mohammad Kholid Ridwan and Awang Noor Indra Wardana

Energies 2025, 18(21), 5859; https://doi.org/10.3390/en18215859 - 6 Nov 2025

Viewed by 878

Abstract

Energy-intensive sectors in emerging nations have the simultaneous difficulties of trying to diminish greenhouse gas emissions while maintaining a stable and cost-effective energy supply. Rooftop solar photovoltaic (PV) systems offer a viable solution, especially in tropical areas like Indonesia that have elevated solar [...] Read more.

Energy-intensive sectors in emerging nations have the simultaneous difficulties of trying to diminish greenhouse gas emissions while maintaining a stable and cost-effective energy supply. Rooftop solar photovoltaic (PV) systems offer a viable solution, especially in tropical areas like Indonesia that have elevated solar irradiance. This study employs a comprehensive methodology to evaluate the structural, economic, and safety viability of rooftop photovoltaic adoption in the Fast-Moving Consumer Goods (FMCG) sector. Structural analysis utilizing the PMM Ratio verified that industrial rooftops can support a 599 kWp photovoltaic system with minimal reinforcements. The economic assessment revealed substantial feasibility, featuring a Levelized Cost of Energy (LCOE) of Rp 261.40/kWh (about USD 0.016/kWh), yearly savings of Rp 1.36 billion (approximately USD 89,000), a Return on Investment (ROI) of 570%, and a payback duration of 3.73 years. The safety evaluation utilizing the Hazard Identification and Risk evaluation (HIRA) technique found significant hazards—working at height, electrical faults, and fire risks—and recommended mitigation measures in accordance with IEC and Indonesian standards. The findings establish a replicable paradigm for assessing rooftop photovoltaic systems in energy-intensive sectors and furnish actionable recommendations for policymakers and industry executives to expedite the adoption of renewable energy in tropical emerging economies. Full article

(This article belongs to the Special Issue Solar Energy and Photovoltaic Systems: Prospect Development and Challenges)

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48 pages, 6323 KB

Open AccessReview

Digital Twins for Space Battery Management Systems: A Comprehensive Review of Different Approaches for Predictive Maintenance and Monitoring

by Roberto Giovanni Sbarra, Michele Pasquali, Giuliano Coppotelli, Paolo Gaudenzi, Davide di Ienno, Carlo Ciancarelli and Niccolò Picci

Energies 2025, 18(21), 5858; https://doi.org/10.3390/en18215858 - 6 Nov 2025

Viewed by 858

Abstract

The development of Digital Twin (DT) technology in Battery Management Systems (BMSs) presents a transformative approach for maintenance, monitoring, and predictive diagnostics, especially in the demanding field of space applications. DTs, through their three-layer structure, provide an accurate and dynamic virtual representation of [...] Read more.

The development of Digital Twin (DT) technology in Battery Management Systems (BMSs) presents a transformative approach for maintenance, monitoring, and predictive diagnostics, especially in the demanding field of space applications. DTs, through their three-layer structure, provide an accurate and dynamic virtual representation of the physical entity, continuously updated via bidirectional data exchange provided by the communication link. Given the promising capabilities of the DT approach in real-time applications, its integration into BMSs is straightforward, as it can enhance monitoring and prediction of nonlinear electrochemical systems, such as space-grade lithium-ion batteries, supporting the mitigation of ageing effects under the unique constraints of the space environment. Despite notable progress in BMS technologies, the choice of estimation techniques consistent with the DT paradigm remains insufficiently defined. This survey examines the state of the art with the aim of bridging the conceptual framework of DTs and existing battery management algorithms, identifying the methodologies most suitable in accordance with DT architectures and principles. The scope of this paper is to provide researchers and engineers with a comprehensive overview of the advancements, key enabling technologies, and implementation strategies for Digital Twins in space BMSs, ultimately contributing to more reliable and efficient space missions. Full article

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34 pages, 10116 KB

Open AccessArticle

Gas Evolution and Stability of Alkali-Activated MSWI Slag and Fly Ash: Implications for Safe Use and Energy Valorization

by Beata Łaźniewska-Piekarczyk, Grzegorz Dzido, Monika Czop and Małgorzata Kajda-Szcześniak

Energies 2025, 18(21), 5857; https://doi.org/10.3390/en18215857 - 6 Nov 2025

Viewed by 323

Abstract

This study investigates the valorization of municipal solid waste incineration (MSWI) residues—specifically bottom ash with slag (BA + S) and fly ash (FA)—through alkaline activation in geopolymer and cementitious systems. The research demonstrates that alkali activation significantly improves mechanical properties, with compressive strengths [...] Read more.

This study investigates the valorization of municipal solid waste incineration (MSWI) residues—specifically bottom ash with slag (BA + S) and fly ash (FA)—through alkaline activation in geopolymer and cementitious systems. The research demonstrates that alkali activation significantly improves mechanical properties, with compressive strengths up to 45.9 MPa for cement mortars and 33.2 MPa for geopolymers. A key innovation includes the quantification of hydrogen gas release during activation, with up to 72.5 dm³/kg H₂ from BA + S, offering insights into binder design and potential green hydrogen recovery. Environmental leachability assessments confirmed that activated BA + S immobilizes heavy metals effectively, although FA showed higher barium and lead leaching. Morphological analysis (SEM, granulometry) revealed microstructural changes enhancing reactivity. Additionally, a practical swelling test is proposed for early detection of expansion risk. The findings contribute to the development of sustainable, high-performance binders from waste, with implications for circular economy and energy valorization strategies. Full article

(This article belongs to the Special Issue Biomass and Municipal Solid Waste Thermal Conversion Technologies: 3rd Edition)

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Graphical abstract

12 pages, 2264 KB

Open AccessArticle

Real-Time Monitoring of Secondary Mineral Precipitation During CO₂–H₂O–Rock Interactions Under High Temperature and Pressure Using Fiber Optic Scale Sensors

by Sakurako Satake, Ai Hosoki, Hideki Kuramitz, Akira Ueda and Amane Terai

Energies 2025, 18(21), 5856; https://doi.org/10.3390/en18215856 - 6 Nov 2025

Viewed by 425

Abstract

This study successfully monitored the formation of secondary minerals resulting from CO₂–H₂O–rock reactions under high-temperature, high-pressure conditions (approximately 250 °C and 6 MPa, respectively) in real time using a sensor based on the attenuated total reflection (ATR) detection principle. [...] Read more.

This study successfully monitored the formation of secondary minerals resulting from CO₂–H₂O–rock reactions under high-temperature, high-pressure conditions (approximately 250 °C and 6 MPa, respectively) in real time using a sensor based on the attenuated total reflection (ATR) detection principle. First, a verification experiment was conducted using a saturated calcium carbonate solution. This experiment quantitatively confirmed an increase in precipitation and a decrease in transmittance as the temperature increased from 25 °C to 250 °C. Next, CO₂–H₂O–rock reaction tests were conducted within a batch-type apparatus. Under neutral conditions (pH 7.3), the transmittance rapidly decreased to approximately 20% within five days of initiating the reaction. Combined with our previous results from separate batch-based rock reaction tests conducted under identical conditions, it was revealed that the rapid precipitation of secondary minerals, primarily smectite, was the dominant process. Conventional methods estimate precipitation amounts by analyzing rock surface morphology after reaction tests, which leaves the reaction mechanism unclear. The primary innovation of this study lies in directly capturing precipitation dynamics during the initial reaction stage, which could not be achieved using conventional post reaction analysis methods. By employing this monitoring technique to measure the precipitation rates and quantities of secondary minerals under various test conditions, this study is expected to make significant contributions to the understanding and controlling of precipitation phenomena and changes in formation permeability in CO₂ geological storage and carbon-recycling geothermal power generation projects. Full article

(This article belongs to the Section H2: Geothermal)

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21 pages, 6738 KB

Open AccessArticle

Optimized Defense Resource Allocation for Coupled Power-Transportation Networks Considering Information Security

by Yuheng Liu, Wenteng Liang, Jie Li, Yufeng Xiong, Yan Li, Qinran Hu, Tao Qian and Jinyu Yue

Energies 2025, 18(21), 5855; https://doi.org/10.3390/en18215855 - 6 Nov 2025

Viewed by 324

Abstract

Electric vehicle charging stations (EVCSs) are critical interfaces between urban mobility and distribution grids and are increasingly exposed to false data that can mislead operations and degrade voltage quality. This study proposes a defense-planning framework that models how cyber manipulation propagates to physical [...] Read more.

Electric vehicle charging stations (EVCSs) are critical interfaces between urban mobility and distribution grids and are increasingly exposed to false data that can mislead operations and degrade voltage quality. This study proposes a defense-planning framework that models how cyber manipulation propagates to physical impacts in a coupled transport–power system. The interaction is modeled as a tri-level defender–attacker–operator problem in which a defender hardens a subset of charging stations, an attacker forges measurements and demand, and an operator redispatches resources to keep the system secure. We solve this problem with a method that embeds corrective operation into the evaluation and uses improved implicit enumeration (IIE) with pruning to identify a small set of high-value stations to protect with far fewer trials than an exhaustive search. On a benchmark feeder coupled to a road network, protecting a few traffic-critical stations restores compliance with voltage limits under tested attack levels while requiring roughly an order of magnitude fewer evaluations than complete enumeration. Sensitivity analysis shows that the loss of reactive power from PV inverters (PV VARs) harms voltage profiles more than an equivalent reduction in distributed storage, indicating that maintaining local reactive capability reduces the number of stations that must be hardened to meet a given voltage target. These results guide utilities and city planners to prioritize protection at traffic-critical EVCSs and co-plan local Volt/VAR capability, achieving code-compliant voltage quality under adversarial conditions with markedly lower planning effort. Full article

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36 pages, 14759 KB

Open AccessArticle

Effects of GAHE Application on Annual Changes in Microclimate Parameters in Equine Facilities

by Piotr Kęskiewicz, Maciej Besler and Wojciech Cepiński

Energies 2025, 18(21), 5854; https://doi.org/10.3390/en18215854 - 6 Nov 2025

Viewed by 393

Abstract

In this manuscript, an analysis of the prospect of using a direct-contact air, gravel, ground heat exchanger (GAHE)—patented and tested at the Wroclaw University of Science and Technology—as a simple and inexpensive way of improving microclimate parameters in horse stables using renewable energy [...] Read more.

In this manuscript, an analysis of the prospect of using a direct-contact air, gravel, ground heat exchanger (GAHE)—patented and tested at the Wroclaw University of Science and Technology—as a simple and inexpensive way of improving microclimate parameters in horse stables using renewable energy was presented. Different options for introducing a GAHE into the typical HVAC system have been proposed and examined. Using the GAHE calculation model developed based on the research, computer simulations of the GAHE’s interaction with the ventilation system were conducted. The effects of GAHE interaction were compared with a typical solution that does not utilise ground renewable energy. The analyses demonstrate year-round changes in microclimate parameters, particularly in the air temperature, relative humidity, and the THI comfort index. The benefits of using a GAHE as a component that improves comfort for animals and employees, while simultaneously saving energy, were demonstrated. The use of measurement data and computer energy simulations demonstrates the engineering feasibility of including GAHEs in a mechanical ventilation system for a horse stable. The obtained results indicate the potential for improving animal husbandry and employee working conditions without the need to consume additional energy to operate complex HVAC systems. Full article

(This article belongs to the Special Issue Smart and Energy Efficient HVAC Systems Towards Building Decarbonizations)

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30 pages, 6333 KB

Open AccessArticle

Phase-Specific Mixture of Experts Architecture for Real-Time NO_x Prediction in Diesel Vehicles: Advancing Euro 7 Compliance

by Maksymilian Mądziel

Energies 2025, 18(21), 5853; https://doi.org/10.3390/en18215853 - 6 Nov 2025

Cited by 1 | Viewed by 435

Abstract

The implementation of Euro 7 emission standards demands advanced real-time NO_x monitoring systems for diesel vehicles. Existing unified models inadequately capture phase-dependent emission mechanisms during cold-start, urban, and highway operation. This study develops a novel Mixture of Experts (MoE) architecture with data-driven [...] Read more.

The implementation of Euro 7 emission standards demands advanced real-time NO_x monitoring systems for diesel vehicles. Existing unified models inadequately capture phase-dependent emission mechanisms during cold-start, urban, and highway operation. This study develops a novel Mixture of Experts (MoE) architecture with data-driven phase classification based on aftertreatment thermal dynamics. Real-world data from a Euro 6d commercial vehicle (3247 PEMS samples) were classified into three phases, cold (<70 °C coolant temperature), hot low-speed (<90 km/h), and hot high-speed (≥90 km/h), validated through t-SNE analysis (silhouette coefficient = 0.73). The key innovation integrates thermal–kinematic domain knowledge with specialized XGBoost regressors, achieving R² = 0.918 and a 58% RMSE reduction versus unified models (RMSE = 1.825 mg/s). The framework operates within real-time constraints (1.5 ms inference latency), integrating autoencoder-based anomaly detection (95.2% sensitivity) and Model Predictive Control (11–13% NO_x reduction). This represents the first systematic phase-specific NO_x modeling framework with validated Euro 7 OBM compliance capability, providing both methodological advances in expert allocation strategies and practical solutions for next-generation emission control systems. Full article

(This article belongs to the Special Issue Challenges and Opportunities in the Global Clean Energy Transition)

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28 pages, 1089 KB

Open AccessReview

A Review of Geothermal–Solar Hybrid Power-Generation Systems

by Shuntao Hu, Jiali Liu, Xinli Lu and Wei Zhang

Energies 2025, 18(21), 5852; https://doi.org/10.3390/en18215852 - 6 Nov 2025

Viewed by 1023

Abstract

Hybrid geothermal–solar systems leverage complementary resources to enhance efficiency, dispatchability, and low-carbon supply. This review compares mainstream configurations (solar-preheating configurations, solar-superheating configuration, and other emerging concepts) and reports typical performance gains—thermal efficiency of 5–80% and exergy efficiency up to ~60%—observed across resource contexts. [...] Read more.

Hybrid geothermal–solar systems leverage complementary resources to enhance efficiency, dispatchability, and low-carbon supply. This review compares mainstream configurations (solar-preheating configurations, solar-superheating configuration, and other emerging concepts) and reports typical performance gains—thermal efficiency of 5–80% and exergy efficiency up to ~60%—observed across resource contexts. Findings indicate that preheating routes are generally preferable under medium direct normal irradiance (DNI) and operation-and-maintenance (O&M)-constrained conditions, while superheating routes become attractive at high DNI with thermal storage; integrated multigeneration systems can deliver system-level benefits for multi-energy parks and district applications. In addition, this paper identifies technical bottlenecks—source matching, storage dependence, and the absence of a unified evaluation—and summarizes control/optimization strategies, including emerging advanced artificial-intelligence algorithms. In addition, the review highlights a standardized comprehensive performance evaluation framework, which covers thermal and exergy efficiency, net power output, complexity, the levelized cost of electricity (LCOE), reliability, and storage. Finally, according to the research status and findings, future research directions are proposed, which pave the way for more effective exploitation of geothermal and solar energy. Full article

(This article belongs to the Topic Sustainable Energy Systems)

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27 pages, 889 KB

Open AccessArticle

BLDC Motor Models for Multi-Domain Modeling of Electric Power Tools

by Paweł Kocwa, Andrzej Tutaj, Tomasz Drabek and Paweł Piątek

Energies 2025, 18(21), 5851; https://doi.org/10.3390/en18215851 - 6 Nov 2025

Viewed by 587

Abstract

Accurate modeling of Brushless DC (BLDC) motors is crucial for the multi-domain simulation of complex electromechanical systems like electric torque tools, especially when high fidelity is required for Model-Based Design (MBD) and controller validation. Standard BLDC models often employ simplifications that may not [...] Read more.

Accurate modeling of Brushless DC (BLDC) motors is crucial for the multi-domain simulation of complex electromechanical systems like electric torque tools, especially when high fidelity is required for Model-Based Design (MBD) and controller validation. Standard BLDC models often employ simplifications that may not capture critical operational details. This paper presents a comparative analysis of four distinct BLDC motor simulation models: two based on ready-to-use MATLAB/Simulink/Simscape Electrical library blocks (Specialized Power Systems/Electrical Machines/Permanent Magnet Synchronous Machine and Electromechanical/Permanent Magnet/BLDC) and two custom models developed by the authors at AGH University. The models are evaluated based on their structure, underlying equations, and performance in simulating typical operational scenarios of an electric torque tool. Key assessment criteria include the ability to implement realistic (e.g., tabulated, non-ideal) back-EMF (electromotive force) profiles, incorporate cogging torque, model commutation effects, and flexibility for modification. Simulation results indicate that while all models can be suitable for basic control design, the custom-developed models offer greater flexibility and fidelity in representing detailed motor phenomena such as irregular back-EMF waveforms and cogging torque, making them better suited for advanced, high-precision applications. Conversely, standard library models, particularly the one underlying the PMSM block, exhibit limitations in custom back-EMF implementation. This study concludes by recommending models based on specific application requirements and outlines directions for future enhancements, including thermal modeling and iron loss representation. Full article

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

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14 pages, 6294 KB

Open AccessArticle

Numerical Simulations of Forced Ignition and Flame Dynamics in an Ammonia/Air Mixing Layer

by Zhuchuan Chang, Haiou Wang, Kun Luo and Jianren Fan

Energies 2025, 18(21), 5850; https://doi.org/10.3390/en18215850 - 6 Nov 2025

Viewed by 302

Abstract

This work explores NH₃/air non-premixed combustion in a mixing layer, with the objective of quantifying the influence of key parameters on ignition and flame dynamics. A series of two-dimensional simulations were conducted with forced ignition. The evolutions of the Damköhler number [...] Read more.

This work explores NH₃/air non-premixed combustion in a mixing layer, with the objective of quantifying the influence of key parameters on ignition and flame dynamics. A series of two-dimensional simulations were conducted with forced ignition. The evolutions of the Damköhler number (Da) and flame stretch at the peak heat release rate for cases with successful/unsuccessful ignition were examined. It was found that for the cases with successful ignition, the Damköhler number is always larger than unity, the flame stretch maintains a positive value, and the tangential diffusion consistently dominates the normal diffusion all the time. On the contrary, for the cases with unsuccessful ignition, the Damköhler number gradually becomes less than unity, and the value of the flame stretch changes from positive to negative as time advances. During flame quenching, the value of the normal diffusion term becomes larger than that of the tangential diffusion term. The effects of mixing layer thickness on the ignition kernel evolution were assessed. It was shown that a thicker mixing layer promotes ignition kernel development. The ignition process is also influenced by the location of the spark in the mixture fraction space. Finally, the flame dynamics were analyzed in terms of scalar dissipation rate (

χ

), displacement speed

S_{d}

, and flame stretch (

κ

) for various cases. The results showed that the

S_{d}

is negatively correlated with the

κ

and

χ

. The Markstein length was evaluated, and it does not differ between the cases with varying mixing layer thickness. Full article

(This article belongs to the Special Issue Recent Advances in Energy Combustion and Flame)

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24 pages, 5158 KB

Open AccessArticle

Estimation of Lithium Battery State of Health Using Hybrid Deep Learning with Multi-Step Feature Engineering and Optimization Algorithm Integration

by Zhiguo Zhao, Yibo Dai, Ke Li, Zhirong Zhang, Yibing Fang, Biao Chen and Qian Zhao

Energies 2025, 18(21), 5849; https://doi.org/10.3390/en18215849 - 6 Nov 2025

Viewed by 692

Abstract

Accurate State of Health (SOH) estimation is critical for the reliable and safe operation of lithium-ion batteries; this paper proposes an ORIME–Transformer–BILSTM model integrating multiple health factors and achieves high-precision SOH prediction. Traditional single-dimensional health factors (HFs) struggle to predict battery SOH accurately [...] Read more.

Accurate State of Health (SOH) estimation is critical for the reliable and safe operation of lithium-ion batteries; this paper proposes an ORIME–Transformer–BILSTM model integrating multiple health factors and achieves high-precision SOH prediction. Traditional single-dimensional health factors (HFs) struggle to predict battery SOH accurately and stably. Therefore, this study employs Spearman and Kendall correlation coefficients to analyze multi-dimensional HFs and determine the key characteristics for quantifying SOH. The self-attention mechanism of the Transformer encoder extracts and fuses the key features of long-term sequences. A BILSTM network receives these input vectors, whose primary function is to uncover the temporal evolution of the SOH. Finally, the optimal random-weight-initialization meta-heuristic estimation (ORIME) algorithm adaptively adjusts the hyperparameters to optimize the model efficiently. Cycle data from four batteries (B5, B6, B7 and B18) provided by NASA are used for testing. The mean absolute error (MAE), mean absolute percentage error (MAPE) and root-mean-square error (RMSE) of the proposed method are 0.2634%, 0.4337% and 0.3106% Compared to recent state-of-the-art methods, this approach significantly reduces prediction errors by 33% to 67%, unequivocally confirming its superiority and robustness. This work provides a highly accurate and generalized solution for SOH estimation in real-world battery management systems. Full article

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17 pages, 2707 KB

Open AccessArticle

Impact Analysis of Energy and Emissions in Lane-Closure-Free Road Inspections

by Junseo Lee, Junhwi Cho, Shanelle Aira Rodrigazo, Kyung-Sun Lee and Jaeheum Yeon

Energies 2025, 18(21), 5848; https://doi.org/10.3390/en18215848 - 6 Nov 2025

Viewed by 348

Abstract

Road damage threatens driving safety, making timely maintenance essential. However, conventional repairs require on-site personnel, necessitating traffic control and lane closures. These restrictions cause traffic congestion, leading to unnecessary idling and repeated acceleration and deceleration of vehicles, reducing fuel efficiency and increasing energy [...] Read more.

Road damage threatens driving safety, making timely maintenance essential. However, conventional repairs require on-site personnel, necessitating traffic control and lane closures. These restrictions cause traffic congestion, leading to unnecessary idling and repeated acceleration and deceleration of vehicles, reducing fuel efficiency and increasing energy consumption. To overcome these limitations, this study proposes a method for performing inspections without lane closures, utilizing machine vision and AI-based damage detection technology. Furthermore, to quantitatively verify the effectiveness of the proposed method, an energy consumption analysis is conducted using the traffic simulator simulation of urban mobility (SUMO) and the vehicle energy simulator future automotive systems technology simulator (FASTSim). Results show lane closures reduced average speed by 25% and increased driving time by over 40%, adding 5044.73 L of fuel for gasoline vehicles and 3208.63 L for diesel vehicles, with CO₂ emissions rising by 11.86 and 8.60 t, respectively. In contrast, the proposed method had minimal traffic impact, with less than 0.1% increases in fuel use and emissions. This approach enables simultaneous multi-lane inspection, improving maintenance efficiency and reducing social costs and energy waste caused by traffic control. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, 3rd Edition)

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24 pages, 8173 KB

Open AccessArticle

The Role of Double-Φ Floating Semi-Submersible Vertical Axis Wind Turbines in Suppressing the Gyroscopic Effect

by Jin Jiang, Zhengyang Wang, Weijie Zhang and Binbin Zhao

Energies 2025, 18(21), 5847; https://doi.org/10.3390/en18215847 - 6 Nov 2025

Viewed by 526

Abstract

The gyroscopic effect has significant impacts on the stability, dynamic behavior, and vibration characteristics of high-speed rotating systems. A floating offshore vertical axis wind turbine (FOVWT) exhibits gyroscope-like motions under combined wind–wave–current conditions; the attitude angles of the shaft connected to the platform [...] Read more.

The gyroscopic effect has significant impacts on the stability, dynamic behavior, and vibration characteristics of high-speed rotating systems. A floating offshore vertical axis wind turbine (FOVWT) exhibits gyroscope-like motions under combined wind–wave–current conditions; the attitude angles of the shaft connected to the platform change continuously in space, making the overall system’s gyroscopic effect more pronounced. From a geometric perspective, this study investigates a method to suppress the gyroscopic effect of floating offshore vertical axis wind turbines: replacing the conventional single-Φ rotor with a stagger-mounted double-layer double-Φ rotor. This configuration exploits the phase difference in circumferential (i.e., 360° around the rotor) aerodynamic loads experienced by the upper and lower rotors; the superposition of these loads ultimately reduces the platform’s pitch response. This study adopts computational fluid dynamics (CFD) for numerical simulations. First, using the NREL 5-MW OC4 floating horizontal axis wind turbine (FOHWT) platform as the research object, we computed the platform’s motion responses under different environmental conditions and verified the effectiveness of the numerical method through comparison with published literature data. Then, under the same marine environment, we compared the motion responses of the conventional single-Φ turbine and double-Φ turbines with different misalignment angles. The results show that modifying the Φ-type rotor configuration can effectively reduce the axial load on the rotor and enhance system stability. As the rotor misalignment angle increases from 15° to 90°, the pitch motion amplitude decreases from 20.6% to 11.8%, while the overall turbine power is only slightly reduced. Full article

(This article belongs to the Special Issue Advances in Offshore Renewable Energy Systems)

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20 pages, 2424 KB

Open AccessArticle

An Aerodynamic Optimization Approach for Wind Turbine Blades Using Proper Generalized Decomposition

by Nacer Eddine Boumezbeur and Arezki Smaili

Energies 2025, 18(21), 5846; https://doi.org/10.3390/en18215846 - 6 Nov 2025

Viewed by 594

Abstract

A new approach for optimizing the blade profile of a horizontal axis wind turbine is proposed in this paper, based on the combination of the Blade Element Momentum (BEM) method and Proper Generalized Decomposition (PGD). The resulting algorithm was implemented in MATLAB (R2010A). [...] Read more.

A new approach for optimizing the blade profile of a horizontal axis wind turbine is proposed in this paper, based on the combination of the Blade Element Momentum (BEM) method and Proper Generalized Decomposition (PGD). The resulting algorithm was implemented in MATLAB (R2010A). To investigate the applicability of the proposed BEM-PGD method, simulations were conducted using the NREL phase VI turbine. By focusing on the tangential force coefficient as a parametrized solution, the study demonstrated a 21.7% improvement in the power coefficient relative to the baseline blade corresponding to a 20 kW turbine, while the tip speed ratio (TSR) ranged from 1 to 12, as assessed through a quantitative metric comparing the optimized and reference curves. These advancements are attributed to the algorithm’s capability to parameterize the solution and to select the appropriate airfoil type, thickness, chord, and twist, allowing for an optimized and realistic blade design. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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41 pages, 11589 KB

Open AccessArticle

Low-Voltage Test Bench Experimental System for Current Harmonics Mitigation

by Marian Gaiceanu, Silviu Epure, Razvan Constantin Solea, Razvan Buhosu and Ciprian Vlad

Energies 2025, 18(21), 5845; https://doi.org/10.3390/en18215845 - 5 Nov 2025

Cited by 1 | Viewed by 525

Abstract

The authors of this paper highlight the creation of an experimental system for the implementation and testing of active low-voltage electronic power filters of the parallel type, with applicability in a wide range of electrical parameters. In this paper, the authors present the [...] Read more.

The authors of this paper highlight the creation of an experimental system for the implementation and testing of active low-voltage electronic power filters of the parallel type, with applicability in a wide range of electrical parameters. In this paper, the authors present the results obtained on an experimental test bench for power quality purposes. The experimental test bench is one of the results of a technology transfer project. One of the specific objectives of the project was to carry out industrial research and experimental development activities in order to develop a competitive, technical and economic solution for an intelligent power system, Active Power Filter (APF). Thus, this paper presents the experimental test bench for the design, implementation and testing of algorithms for current harmonics mitigation. The conceptual theoretical frame bases of both direct and indirect control have been presented by the authors. As a case study, both the simulation and experimental results of the indirect control strategy implemented on the test bench are provided. The indirect control method is chosen due to simplicity, no complex calculus requirements, and the use of a minimum number of transducers. By features comparison with modern control strategies, this study underlines the supremacy of the indirect control in active harmonics control. Full article

(This article belongs to the Special Issue Recent Advances in Power Quality Analysis and Robust Control of Renewable Energy Sources in Power Grids: 2nd Edition)

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36 pages, 2131 KB

Open AccessReview

Biogas Production in Agriculture: Technological, Environmental, and Socio-Economic Aspects

by Krzysztof Pilarski, Agnieszka A. Pilarska and Michał B. Pietrzak

Energies 2025, 18(21), 5844; https://doi.org/10.3390/en18215844 - 5 Nov 2025

Cited by 1 | Viewed by 962

Abstract

This review provides a comprehensive analysis of the technological, environmental, economic, regulatory, and social dimensions shaping the development and operation of agricultural biogas plants. The paper adopts a primarily European perspective, reflecting the comparatively high share of agricultural inputs in anaerobic digestion (AD) [...] Read more.

This review provides a comprehensive analysis of the technological, environmental, economic, regulatory, and social dimensions shaping the development and operation of agricultural biogas plants. The paper adopts a primarily European perspective, reflecting the comparatively high share of agricultural inputs in anaerobic digestion (AD) across EU Member States, while drawing selective comparisons with global contexts to indicate where socio-geographical conditions may lead to different outcomes. It outlines core principles of the AD process and recent innovations—such as enzyme supplementation, microbial carriers, and multistage digestion systems—that enhance process efficiency and cost-effectiveness. The study emphasises substrate optimisation involving both crop- and livestock-derived materials, together with the critical management of water resources and digestate within a circular-economy framework to promote sustainability and minimise environmental risks. Economic viability, regulatory frameworks, and social dynamics are examined as key factors underpinning successful biogas implementation. The paper synthesises evidence on cost–benefit performance, investment drivers, regulatory challenges, and support mechanisms, alongside the importance of community engagement and participatory governance to mitigate land-use conflicts and ensure equitable rural development. Finally, it addresses persistent technical, institutional, environmental, and social barriers that constrain biogas deployment, underscoring the need for integrated solutions that combine technological advances with policy support and stakeholder cooperation. This analysis offers practical insights for advancing sustainable biogas use in agriculture, balancing energy production with environmental stewardship, food security, and rural equity. The review is based on literature identified in Scopus and Web of Science for 2007 to 2025 using predefined keyword sets and supplemented by EU policy and guidance documents and backward- and forward-citation searches. Full article

(This article belongs to the Special Issue Renewable Energy Integration into Agricultural and Food Engineering)

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34 pages, 7065 KB

Open AccessArticle

Metaheuristic-Based Control Parameter Optimization of DFIG-Based Wind Energy Conversion Systems Using the Opposition-Based Search Optimization Algorithm

by Kavita Behara and Ramesh Kumar Behara

Energies 2025, 18(21), 5843; https://doi.org/10.3390/en18215843 - 5 Nov 2025

Viewed by 395

Abstract

Renewable wind energy systems widely employ doubly fed induction generators (DFIGs), where efficient converter control ensures grid-integrated power system stability and reliability. Conventional proportional–integral (PI) controller tuning methods often encounter challenges with nonlinear dynamics and parameter variations, resulting in reduced adaptability and efficiency. [...] Read more.

Renewable wind energy systems widely employ doubly fed induction generators (DFIGs), where efficient converter control ensures grid-integrated power system stability and reliability. Conventional proportional–integral (PI) controller tuning methods often encounter challenges with nonlinear dynamics and parameter variations, resulting in reduced adaptability and efficiency. To address this, we present an owl search optimization (OSO)-based tuning strategy for PI controllers in DFIG back-to-back converters. Inspired by the hunting behavior of owls, OSO provides robust global search capabilities and resilience against premature convergence. The proposed method is evaluated in MATLAB/Simulink and benchmarked against particle swarm optimization (PSO), genetic algorithm (GA), and simulated annealing (SA) under step wind variations, turbulence, and grid disturbances. Simulation results demonstrate that OSO achieves superior performance, with 96.4% efficiency, reduced power losses (~40 kW), faster convergence (<400 ms), shorter settling time (<345 ms), and minimal oscillations (0.002). These findings establish OSO as a robust and efficient optimization approach for DFIG-based wind energy systems, delivering enhanced dynamic response and improved grid stability. Full article

(This article belongs to the Special Issue Algorithmic Approaches and Control Techniques for Energy Optimization in Power Converters and Grid Transmission)

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18 pages, 2309 KB

Open AccessArticle

Kinetic Study on Pyrolysis of Tung Seed Shells and In Situ Characterization by Using TG–FTIR Analysis

by Yiju Liao and Kai Huang

Energies 2025, 18(21), 5842; https://doi.org/10.3390/en18215842 - 5 Nov 2025

Viewed by 317

Abstract

This study investigates the pyrolysis behavior of tung seed shells (TSSs), an underutilized lignocellulosic residue from Vernicia fordii, using thermogravimetric analysis (TGA) and in situ TG–FTIR spectroscopy. The thermal decomposition process was found to occur in multiple stages, corresponding to the sequential [...] Read more.

This study investigates the pyrolysis behavior of tung seed shells (TSSs), an underutilized lignocellulosic residue from Vernicia fordii, using thermogravimetric analysis (TGA) and in situ TG–FTIR spectroscopy. The thermal decomposition process was found to occur in multiple stages, corresponding to the sequential degradation of hemicellulose, cellulose, and lignin. Particle size and heating rate strongly influenced the decomposition profile, with finer particles exhibiting enhanced devolatilization due to improved heat and mass transfer. Kinetic analysis using the Coats–Redfern, Doyle, and Kissinger methods revealed apparent activation energies ranging from 30 to 122 kJ/mol, consistent with typical values for lignocellulosic biomass. The evolution of gaseous species, including CO, CO₂, and CH₄, throughout all pyrolysis stages confirms the potential of TSSs for bio-syngas and biochar production. These findings provide new insights into the kinetic and mechanistic characteristics of tung seed shell pyrolysis and support its application as a renewable feedstock for sustainable bioenergy generation. Full article

(This article belongs to the Special Issue Biomass to Liquid Fuels)

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20 pages, 2972 KB

Open AccessArticle

Multi-Stage Adaptive Robust Scheduling Framework for Nonlinear Solar-Integrated Transportation Networks

by Puyu He, Jie Jiao, Yuhong Zhang, Yangming Xiao, Zhuhan Long, Hanjing Liu, Zhongfu Tan and Linze Yang

Energies 2025, 18(21), 5841; https://doi.org/10.3390/en18215841 - 5 Nov 2025

Viewed by 323

Abstract

The operation of modern power networks is increasingly exposed to overlapping climate extremes and volatile system conditions, making it essential to adopt scheduling approaches that are resilient as well as economical. In this study, a two-stage stochastic formulation is advanced, where indicators of [...] Read more.

The operation of modern power networks is increasingly exposed to overlapping climate extremes and volatile system conditions, making it essential to adopt scheduling approaches that are resilient as well as economical. In this study, a two-stage stochastic formulation is advanced, where indicators of system adaptability are embedded directly into the optimization process. The objective integrates standard operating expenses—generation, reserve allocation, imports, responsive demand, and fuel resources—with a Conditional Value-at-Risk component that reflects exposure to rare but damaging contingencies, such as extreme heat, severe cold, drought-related hydro scarcity, solar output suppression from wildfire smoke, and supply chain interruptions. Key adaptability dimensions, including storage cycling depth, activation speed of demand response, and resource ramping behavior, are modeled through nonlinear operational constraints. A stylized test system of 30 interconnected areas with a 46 GW demand peak is employed, with more than 2000 climate-informed scenarios compressed to 240 using distribution-preserving reduction techniques. The results indicate that incorporating risk-sensitive policies reduces expected unserved demand by more than 80% during compound disruptions, while the increase in cost remains within 12–15% of baseline planning. Pronounced spatiotemporal differences emerge: evening reserve margins fall below 6% without adaptability provisions, yet risk-adjusted scheduling sustains 10–12% margins. Transmission utilization curves further show that CVaR-based dispatch prevents extreme flows, though modest renewable curtailment arises in outer zones. Moreover, adaptability provisions promote shallower storage cycles, maintain an emergency reserve of 2–3 GWh, and accelerate the mobilization of demand-side response by over 25 min in high-stress cases. These findings confirm that combining stochastic uncertainty modeling with explicit adaptability metrics yields measurable gains in reliability, providing a structured direction for resilient system design under escalating multi-hazard risks. Full article

(This article belongs to the Topic Intelligent, Flexible, and Effective Operation of Smart Grids with Novel Energy Technologies and Equipment)

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19 pages, 2675 KB

Open AccessArticle

Multi-Time-Scale Optimization and Control Method for High-Penetration Photovoltaic Electrolytic Aluminum Plants

by Lixin Wu, Qunhai Huo, Qiran Liu, Jingyuan Yin and Jie Yang

Energies 2025, 18(21), 5840; https://doi.org/10.3390/en18215840 - 5 Nov 2025

Viewed by 336

Abstract

In response to the high energy consumption and carbon emission issues in the electrolytic aluminum industry, this paper proposes a multi-time-scale optimization and control method for electrolytic aluminum plants with high photovoltaic penetration. First, a plant architecture is established, which includes traditional power [...] Read more.

In response to the high energy consumption and carbon emission issues in the electrolytic aluminum industry, this paper proposes a multi-time-scale optimization and control method for electrolytic aluminum plants with high photovoltaic penetration. First, a plant architecture is established, which includes traditional power systems, renewable energy systems, and electrolytic aluminum loads. A mathematical model for flexible resources such as thermal power units, on-load tap-changing transformers, thyristor-controlled voltage regulators, saturable reactors, and electrolytic cells is developed. Based on this, a two-level optimization control strategy is designed, consisting of a day-ahead and real-time control layer: the day-ahead layer targets economic and low-carbon operation, while the real-time layer aims to stabilize the DC bus voltage. Using actual data from an electrolytic aluminum plant in Southwest China, simulations are conducted on the MATLAB 2021a platform, and the effectiveness of the strategy is verified through hardware-in-the-loop experiments. The results demonstrate that the proposed method can effectively increase the photovoltaic utilization rate, reduce thermal power output and operational costs, and decrease carbon emissions, providing a feasible solution for the green and low-carbon transformation of the electrolytic aluminum industry. Full article

(This article belongs to the Special Issue Modeling, Control and Simulation of Power Electronic Converters for the Power Gird Application)

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23 pages, 2604 KB

Open AccessArticle

Multi-Criteria Model Predictive Controller for Hybrid Heating Systems in Buildings

by Ali Soleimani, Paul Davidsson, Reza Malekian and Romina Spalazzese

Energies 2025, 18(21), 5839; https://doi.org/10.3390/en18215839 - 5 Nov 2025

Viewed by 468

Abstract

With more hybrid heating systems available, there is a need to optimize energy use intelligently from the end-consumer perspective. This paper focuses on a multi-criteria heating system optimization to optimize cost, carbon emission, and comfort level of building occupants. A discrete Multi-Objective Model [...] Read more.

With more hybrid heating systems available, there is a need to optimize energy use intelligently from the end-consumer perspective. This paper focuses on a multi-criteria heating system optimization to optimize cost, carbon emission, and comfort level of building occupants. A discrete Multi-Objective Model Predictive Controller (MO-MPC) algorithm is proposed to optimally utilize two heating sources connected to a building, namely district heating (DH) and a building-integrated electrical heat pump (HP). The model is tested on a real-world building case simulated with a gray box building model. The results are compared to a conventional PID controller as well as the MPC scheme, each with a single heating input, and eight different cases are constructed to make this comparison more visible. The results indicate that, using MO-MPC, a cost saving of up to 10% and emission saving of up to 13% can be reached without additional thermal discomfort, while the potential savings on cost and emission with the hybrid system can be up to 25% and 77%, respectively. Further, a sensitivity analysis on price and emission parameters is conducted to investigate the changes in the provided solution. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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19 pages, 4154 KB

Open AccessArticle

Energy-Storage Performance of High-Entropy (NaBiBa)_0.205 (SrCa)_0.1925TiO₃-La(Mg_0.5Zr_0.5)O₃ Ceramic Under Moderate Electric Fields

by Peng Shi, Heng Li, Yu Zhou, Ziying Wang and Yiming Wang

Energies 2025, 18(21), 5838; https://doi.org/10.3390/en18215838 - 5 Nov 2025

Viewed by 367

Abstract

With the global low-voltage power market expanding rapidly, lead-free dielectric ceramics exhibit excellent stability and environmental friendliness, but their strong field-dependence limits low-field applications. There is an urgent need to develop lead-free ceramic systems with outstanding energy-storage performance under modest electric fields to [...] Read more.

With the global low-voltage power market expanding rapidly, lead-free dielectric ceramics exhibit excellent stability and environmental friendliness, but their strong field-dependence limits low-field applications. There is an urgent need to develop lead-free ceramic systems with outstanding energy-storage performance under modest electric fields to meet the rapidly expanding global low-voltage power market for bulk ceramics. In this study, high-entropy ceramics (1 − x%)(NaBiBa)_0.205(SrCa)_0.1925TiO₃-x%La(Zr_0.5Mg_0.5)O₃ (x = 0–8) were successfully prepared. The introduced La(Zr_0.5Mg_0.5)O₃ not only dissolves well in the high-entropy elementary lattice but also effectively improves its relaxation characteristics. High-entropy ceramics show optimal energy-storage characteristics, as indicated by an excellent energy-storage density of 4.46 J/cm³ and an energy-storage efficiency of 94.55% at 318 kV/cm. Moreover, its power density is as high as 92.20 MV/cm³, and the discharge time t_0.9 is only 145 ns. Full article

(This article belongs to the Section D1: Advanced Energy Materials)

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26 pages, 7703 KB

Open AccessArticle

Deployment of Modular Renewable Energy Sources and Energy Storage Schemes in a Renewable Energy Valley

by Alexandros Kafetzis, Giorgos Kardaras, Michael Bampaou, Kyriakos D. Panopoulos, Elissaios Sarmas, Vangelis Marinakis and Aristotelis Tsekouras

Energies 2025, 18(21), 5837; https://doi.org/10.3390/en18215837 - 5 Nov 2025

Viewed by 411

Abstract

While community energy initiatives and pilot projects have demonstrated technical feasibility and economic benefits, their site-specific nature limits transferability to systematic, scalable investment models. This study addresses this gap by proposing a modular framework for Renewable Energy Valleys (REVs), developed from real-world Community [...] Read more.

While community energy initiatives and pilot projects have demonstrated technical feasibility and economic benefits, their site-specific nature limits transferability to systematic, scalable investment models. This study addresses this gap by proposing a modular framework for Renewable Energy Valleys (REVs), developed from real-world Community Energy Lab (CEL) demonstrations in Crete, Greece, which is an island with pronounced seasonal demand fluctuation, strong renewable potential, and ongoing hydrogen valley initiatives. Four modular business schemes are defined, each representing different sectoral contexts by combining a baseline of 50 residential units with one representative large consumer (hotel, rural households with thermal loads, municipal swimming pool, or hydrogen bus). For each scheme, a mixed-integer linear programming model is applied to optimally size and operate integrated solar PV, wind, battery (BAT) energy storage, and hydrogen systems across three renewable energy penetration (REP) targets: 90%, 95%, and 99.9%. The framework incorporates stochastic demand modeling, sector coupling, and hierarchical dispatch schemes. Results highlight optimal technology configurations that minimize dependency on external sources and curtailment while enhancing reliability and sustainability under Mediterranean conditions. Results demonstrate significant variation in optimal configurations across sectors and targets, with PV capacity ranging from 217 kW to 2840 kW, battery storage from 624 kWh to 2822 kWh, and hydrogen systems scaling from 65.2 kg to 192 kg storage capacity. The modular design of the framework enables replication beyond the specific context of Crete, supporting the scalable development of Renewable Energy Valleys that can adapt to diverse sectoral mixes and regional conditions. Full article

(This article belongs to the Special Issue Energy Transition Targets in Future Energy Systems: The Role of Electric Vehicles, Storage Technologies, Smart Grids and Hydrogen Systems)

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12 pages, 436 KB

Open AccessPerspective

Economic and Environmental Outlook on Agrivoltaics: Review and Perspectives

by Alexandra Jean and Kurt A. Rosentrater

Energies 2025, 18(21), 5836; https://doi.org/10.3390/en18215836 - 5 Nov 2025

Viewed by 477

Abstract

The growing world population has continued to drive up the demand for food and energy resources, putting substantial strain on the finite land, water, and fossil resources of the earth. Given the current climate crisis, the necessity of implementing renewable energy-generation strategies has [...] Read more.

The growing world population has continued to drive up the demand for food and energy resources, putting substantial strain on the finite land, water, and fossil resources of the earth. Given the current climate crisis, the necessity of implementing renewable energy-generation strategies has become clear. Although solar energy is one of the most abundant and consistent forms of renewable energy available, conventional ground-mounted solar arrays require large amounts of land area, and solar energy generation may come into competition with agriculture with increasing installation capacity. Agrivoltaics has been presented as a solution to integrate agricultural activities with solar energy generation to enhance the land efficiency of both activities. Through this method, agriculture and solar energy become synergistic, generating multiple profit streams from the same land with additional potential environmental benefits. The review presented herein studies the literature pertaining to the triple bottom line for agrivoltaics systems: people, planet, and profit. Despite the early-stage nature of many available studies, researchers have reported that certain agrivoltaics systems could be up to 270% more profitable than standalone cropping systems and reduce the greenhouse gas potential of traditional agriculture and energy generation by up to 99%. By synthesizing the information from multiple techno-economic analyses, life-cycle assessments, and policy recommendations, we hope to provide some insight into the key parameters driving the long-term sustainability of agrivoltaics systems. Full article

(This article belongs to the Section B: Energy and Environment)

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23 pages, 3692 KB

Open AccessArticle

Energy-Autonomous Cooling of Open Spaces—The Impact of Thermal Comfort Temperature on the Cooperation of the Cooling System with the PV Installation

by Ewelina Barnat, Robert Sekret, Sławomir Rabczak and Justyna Darmochwał-Podoba

Energies 2025, 18(21), 5835; https://doi.org/10.3390/en18215835 - 5 Nov 2025

Viewed by 372

Abstract

Climate change and rising temperatures in cities due to the urban heat island (UHI) effect are causing increased heat stress and driving the development of efficient, sustainable outdoor cooling systems. The aim of this article was to analyze the integration of adiabatic air [...] Read more.

Climate change and rising temperatures in cities due to the urban heat island (UHI) effect are causing increased heat stress and driving the development of efficient, sustainable outdoor cooling systems. The aim of this article was to analyze the integration of adiabatic air cooling systems with photovoltaic (PV) installations in the context of improving thermal comfort and energy autonomy. The study was conducted on the example of a bus station in Rzeszow (Poland), considering two system variants: indirect evaporative cooling and direct evaporative cooling. To assess the impact of comfort parameters on the number of hours of system operation, energy consumption, and operating costs, four upper thermal comfort limits were considered: 22 °C, 22.9 °C, 24 °C, and 25 °C. The results indicate that increasing the upper limit of thermal comfort reduces the operating time of the system and significantly reduces the demand for cooling—for example, increasing the thermal comfort range from 22.9 °C to 24 °C reduces useful energy by 41%. Assuming a thermal comfort range of 25 °C, the direct evaporative cooling system achieves full energy autonomy and is fully powered by photovoltaics. Life cycle analysis (LCA) and life cycle cost (LCC) confirmed the environmental and economic benefits of using higher thermal comfort values. The study highlights the potential of adiabatic cooling systems, in conjunction with a local photovoltaic installation, as an adaptive solution that improves thermal comfort in urban spaces with minimal energy consumption from the grid. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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