Energies

18 pages, 4507 KiB

Open AccessArticle

Online Efficiency Optimization of a Six-Phase Induction Generator Using Loss Model Control for Micro-Hydropower Systems

by Marius Ouédraogo, Amine Yazidi and Franck Betin

Energies 2025, 18(14), 3754; https://doi.org/10.3390/en18143754 (registering DOI) - 15 Jul 2025

This paper presents an online efficiency optimization strategy for a six-phase induction generator (6PIG) operating in both healthy and faulty modes for micro-hydropower applications. The proposed method is based on an extended Loss Model Control (LMC) approach, in which the direct axis stator [...] Read more.

This paper presents an online efficiency optimization strategy for a six-phase induction generator (6PIG) operating in both healthy and faulty modes for micro-hydropower applications. The proposed method is based on an extended Loss Model Control (LMC) approach, in which the direct axis stator current Id is dynamically optimized in real time to minimize the total electrical losses. Unlike conventional LMC strategies, this method explicitly incorporates switching losses into the loss model, along with stator and rotor copper losses and iron losses. The optimization problem is solved using a numerical minimization routine, allowing the control system to adapt continuously to variations in torque requests. The proposed approach is validated under both healthy and faulty configurations of the 6PIG. It is implemented and tested through simulation in MATLAB/Simulink^® and experimentally validated on a 24 kW squirrel cage six-phase induction generator (SC6PIG). The results are compared in terms of power losses, energy saving, and efficiency. Full article

(This article belongs to the Special Issue Design and Production Process Optimization for High Performance and Energy Efficiency in Electrical Machines)

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35 pages, 4736 KiB

Open AccessArticle

Computational and Experimental Investigation of Additively Manufactured Lattice Heat Sinks for Liquid-Cooling Railway Power Electronics

by Ahmad Batikh, Jean-Pierre Fradin and Antonio Castro Moreno

Energies 2025, 18(14), 3753; https://doi.org/10.3390/en18143753 (registering DOI) - 15 Jul 2025

Abstract

This study investigates the performance of lattice-structured heat sinks based on BCCz unit cells in comparison to conventional straight-fin and pin-fin designs. Various lattice configurations were explored. Numerical simulations and experimental evaluations were carried out to analyze thermal resistance, pressure drop, and temperature [...] Read more.

This study investigates the performance of lattice-structured heat sinks based on BCCz unit cells in comparison to conventional straight-fin and pin-fin designs. Various lattice configurations were explored. Numerical simulations and experimental evaluations were carried out to analyze thermal resistance, pressure drop, and temperature distribution under different operating conditions. Among the designs, the BCCz configuration with a circular cross-section was identified as the most promising candidate for integration into the final heat sink demonstrator, offering reliable and consistent performance. A prototype using the BCCz lattice structure was additively manufactured, alongside a conventional design for comparison. The results highlight the superior heat dissipation capabilities of lattice structures, achieving up to a 100% improvement in thermal performance at high flow rates and up to 300% at low flow rates compared to a conventional straight-fin heat sink. However, the pressure drop generated by the lattice structures remains a challenge that must be addressed. This work underscores the potential of optimized lattice-based heat exchangers to meet the severe thermal management requirements of railway power electronics. Full article

(This article belongs to the Special Issue Thermal and Reliability Investigations in Electronics Components and Systems)

14 pages, 3561 KiB

Open AccessArticle

Preparation and Electrochemical Performance of Zinc-Doped Copper Fluoride

by Peng Dou, Pengcheng Liu and Zhiyong Yu

Energies 2025, 18(14), 3752; https://doi.org/10.3390/en18143752 (registering DOI) - 15 Jul 2025

Abstract

To enhance the specific energy and rate performance of lithium primary batteries, the development of advanced cathode materials with superior electrochemical properties is essential. Fluorides, composed of light fluorine elements and multivalent cations, exhibit multi-electron reaction characteristics, possess a high theoretical voltage, and [...] Read more.

To enhance the specific energy and rate performance of lithium primary batteries, the development of advanced cathode materials with superior electrochemical properties is essential. Fluorides, composed of light fluorine elements and multivalent cations, exhibit multi-electron reaction characteristics, possess a high theoretical voltage, and demonstrate high discharge-specific energy. However, owing to fluorine’s high electronegativity, which leads to the formation of strong ionic bonds with other elements, most fluorides exhibit poor electronic conductivity, thereby constraining their electrochemical performance when used as cathode materials. Copper fluoride (CuF₂) exhibits a high theoretical specific capacity and discharge voltage but is constrained by its large bandgap, poor electronic conductivity, and difficulties in synthesizing anhydrous CuF₂ materials, which significantly limit its electrochemical activity. In this study, zinc (Zn) was chosen as a dopant for copper fluoride. By combining theoretical calculations with experimental validation, the impacts of Zn doping on the structural stability and electrochemical performance of copper fluoride were comprehensively analyzed. The resultant highly active Zn-doped copper fluoride achieved a discharge specific capacity of 528.6 mAh/g at 0.1 C and 489.1 mAh/g at 1 C, showcasing superior discharge-specific energy and good rate performance. This material holds great potential as a promising cathode candidate for lithium batteries, providing both high specific energy and power density. Full article

(This article belongs to the Special Issue High Performance Lithium Batteries: Prospects, Theories and Key Technologies)

18 pages, 1533 KiB

Open AccessArticle

A Data-Driven Observer for Wind Farm Power Gain Potential: A Sparse Koopman Operator Approach

by Yue Chen, Bingchen Wang, Kaiyue Zeng, Lifu Ding, Yingming Lin, Ying Chen and Qiuyu Lu

Energies 2025, 18(14), 3751; https://doi.org/10.3390/en18143751 (registering DOI) - 15 Jul 2025

Abstract

Maximizing the power output of wind farms is critical for improving the economic viability and grid integration of renewable energy. Active wake control (AWC) strategies, such as yaw-based wake steering, offer significant potential for power generation increase but require predictive models that are [...] Read more.

Maximizing the power output of wind farms is critical for improving the economic viability and grid integration of renewable energy. Active wake control (AWC) strategies, such as yaw-based wake steering, offer significant potential for power generation increase but require predictive models that are both accurate and computationally efficient for real-time implementation. This paper proposes a data-driven observer to rapidly estimate the potential power gain achievable through AWC as a function of the ambient wind direction. The approach is rooted in Koopman operator theory, which allows a linear representation of nonlinear dynamics. Specifically, a model is developed using an Input–Output Extended Dynamic Mode Decomposition framework combined with Sparse Identification (IOEDMDSINDy). This method lifts the low-dimensional wind direction input into a high-dimensional space of observable functions and then employs iterative sparse regression to identify a minimal, interpretable linear model in this lifted space. By training on offline simulation data, the resulting observer serves as an ultra-fast surrogate model, capable of providing instantaneous predictions to inform online control decisions. The methodology is demonstrated and its performance is validated using two case studies: a 9-turbine and a 20-turbine wind farm. The results show that the observer accurately captures the complex, nonlinear relationship between wind direction and power gain, significantly outperforming simpler models. This work provides a key enabling technology for advanced, real-time wind farm control systems. Full article

(This article belongs to the Special Issue Modeling, Control and Optimization of Wind Power Systems)

16 pages, 527 KiB

Open AccessReview

A Concise Review of Power Batteries and Battery Management Systems for Electric and Hybrid Vehicles

by Qi Zhang, Yunlong Shang, Yan Li and Rui Zhu

Energies 2025, 18(14), 3750; https://doi.org/10.3390/en18143750 (registering DOI) - 15 Jul 2025

Abstract

The core powertrain components of electric vehicles (EVs) and hybrid electric vehicles (HEVs) are the power batteries and battery management system (BMS), jointly determining the performance, safety, and economy of the vehicle. This review offers a comprehensive overview of the evolution and current [...] Read more.

The core powertrain components of electric vehicles (EVs) and hybrid electric vehicles (HEVs) are the power batteries and battery management system (BMS), jointly determining the performance, safety, and economy of the vehicle. This review offers a comprehensive overview of the evolution and current advancements in power battery and BMS technology for electric vehicles (EVs). It emphasizes product upgrades and replacements while also analyzing future research hotspots and development trends driven by the increasing demand for EVs and hybrid electric vehicles (HEVs). This review aims to give recommendations and support for the future development of power batteries and BMSs that are widely used in EVs, HEVs, and energy storage systems, which will lead to industry and research progress. Full article

(This article belongs to the Special Issue Challenges, Trends and Achievements in Electric Vehicle Research and Development in the Era of Vehicle Electrification)

29 pages, 4835 KiB

Open AccessArticle

The Impact of Wind Speed on Electricity Prices in the Polish Day-Ahead Market Since 2016, and Its Applicability to Machine-Learning-Powered Price Prediction

by Rafał Sowiński and Aleksandra Komorowska

Energies 2025, 18(14), 3749; https://doi.org/10.3390/en18143749 (registering DOI) - 15 Jul 2025

Abstract

The rising share of wind generation in power systems, driven by the need to decarbonise the energy sector, is changing the relationship between wind speed and electricity prices. In the case of Poland, this relationship has not been thoroughly investigated, particularly in the [...] Read more.

The rising share of wind generation in power systems, driven by the need to decarbonise the energy sector, is changing the relationship between wind speed and electricity prices. In the case of Poland, this relationship has not been thoroughly investigated, particularly in the aftermath of the restrictive legal changes introduced in 2016, which halted numerous onshore wind investments. Studying this relationship remains necessary to understand the broader market effects of wind speed on electricity prices, especially considering evolving policies and growing interest in renewable energy integration. In this context, this paper analyses wind speed, wind generation, and other relevant datasets in relation to electricity prices using multiple statistical methods, including correlation analysis, regression modelling, and artificial neural networks. The results show that wind speed is a significant factor in setting electricity prices (with a correlation coefficient reaching up to −0.7). The findings indicate that not only is it important to include wind speed as an electricity price indicator, but it is also worth investing in wind generation, since higher wind output can be translated into lower electricity prices. This study contributes to a better understanding of how natural variability in renewable resources translates into electricity market outcomes under policy-constrained conditions. Its innovative aspect lies in combining statistical and machine learning techniques to quantify the influence of wind speed on electricity prices, using updated data from a period of regulatory stagnation. Full article

(This article belongs to the Special Issue New Advances in Renewable Energy and Sustainable Energy Storage Systems)

19 pages, 1477 KiB

Open AccessArticle

Analysis and Design of a Multiple-Driver Power Supply Based on a High-Frequency AC Bus

by Qingqing He, Zhaoyang Tang, Wenzhe Zhao and Keliang Zhou

Energies 2025, 18(14), 3748; https://doi.org/10.3390/en18143748 (registering DOI) - 15 Jul 2025

Abstract

Multi-channel LED drivers are crucial for high-power lighting applications. Maintaining a constant average forward current is essential for stable LED luminous intensity, necessitating drivers capable of consistent current delivery across wide operating ranges. Meanwhile, achieving precise current sharing among channels without incurring high [...] Read more.

Multi-channel LED drivers are crucial for high-power lighting applications. Maintaining a constant average forward current is essential for stable LED luminous intensity, necessitating drivers capable of consistent current delivery across wide operating ranges. Meanwhile, achieving precise current sharing among channels without incurring high costs and system complexity is a significant challenge. Leveraging the constant-current characteristics of the LCL-T network, this paper presents a multi-channel DC/DC LED driver comprising a full-bridge inverter, a transformer, and a passive resonant rectifier. The driver generates a high-frequency AC bus with series-connected diode rectifiers, a structure that guarantees excellent current sharing among all output channels using only a single control loop. Fully considering the impact of higher harmonics, this paper derives an exact solution for the output current. A step-by-step parameter design methodology ensures soft switching and enhanced switch utilization. Finally, experimental verification was conducted using a prototype with five channels and 200 W, confirming the correctness and accuracy of the theoretical analysis. The experimental results showed that within a wide input voltage range of 380 V to 420 V, the driver was able to provide a stable current of 700 mA to each channel, and the system could achieve a peak efficiency of up to 94.4%. Full article

(This article belongs to the Special Issue Reliability of Power Electronics Devices and Converter Systems)

52 pages, 782 KiB

Open AccessSystematic Review

Novel Artificial Intelligence Applications in Energy: A Systematic Review

by Tai Zhang and Goran Strbac

Energies 2025, 18(14), 3747; https://doi.org/10.3390/en18143747 (registering DOI) - 15 Jul 2025

Abstract

This systematic review examines state-of-the-art artificial intelligence applications in energy systems, assessing their performance, real-world deployments and transformative potential. Guided by PRISMA 2020, we searched Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, and Google Scholar for English-language studies published between January 2015 and [...] Read more.

This systematic review examines state-of-the-art artificial intelligence applications in energy systems, assessing their performance, real-world deployments and transformative potential. Guided by PRISMA 2020, we searched Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, and Google Scholar for English-language studies published between January 2015 and January 2025 that reported novel AI uses in energy, empirical results, or significant theoretical advances and passed peer review. After title–abstract screening and full-text assessment, it was determined that 129 of 3000 records met the inclusion criteria. The methodological quality, reproducibility and real-world validation were appraised, and the findings were synthesised narratively around four critical themes: reinforcement learning (35 studies), multi-agent systems (28), planning under uncertainty (25), and AI for resilience (22), with a further 19 studies covering other areas. Notable outcomes include DeepMind-based reinforcement learning cutting data centre cooling energy by 40%, multi-agent control boosting virtual power plant revenue by 28%, AI-enhanced planning slashing the computation time by 87% without sacrificing solution quality, battery management AI raising efficiency by 30%, and machine learning accelerating hydrogen catalyst discovery 200,000-fold. Across domains, AI consistently outperformed traditional techniques. The review is limited by its English-only scope, potential under-representation of proprietary industrial work, and the inevitable lag between rapid AI advances and peer-reviewed publication. Overall, the evidence positions AI as a pivotal enabler of cleaner, more reliable, and efficient energy systems, though progress will depend on data quality, computational resources, legacy system integration, equity considerations, and interdisciplinary collaboration. No formal review protocol was registered because this study is a comprehensive state-of-the-art assessment rather than a clinical intervention analysis. Full article

(This article belongs to the Special Issue Optimization and Machine Learning Approaches for Power Systems)

34 pages, 1204 KiB

Open AccessReview

Bio-Coal Briquetting as a Potential Sustainable Valorization Strategy for Fine Coal: A South African Perspective in a Global Context

by Veshara Ramdas, Sesethu Gift Njokweni, Parsons Letsoalo, Solly Motaung and Santosh Omrajah Ramchuran

Energies 2025, 18(14), 3746; https://doi.org/10.3390/en18143746 (registering DOI) - 15 Jul 2025

Abstract

The generation of fine coal particles during mining and processing presents significant environmental and logistical challenges, particularly in coal-dependent, developing countries like South Africa (SA). This review critically evaluates the technical viability of fine coal briquetting as a sustainable waste-to-energy solution within a [...] Read more.

The generation of fine coal particles during mining and processing presents significant environmental and logistical challenges, particularly in coal-dependent, developing countries like South Africa (SA). This review critically evaluates the technical viability of fine coal briquetting as a sustainable waste-to-energy solution within a SA context, while drawing from global best practices and comparative benchmarks. It examines abundant feedstocks that can be used for valorization strategies, including fine coal and agricultural biomass residues. Furthermore, binder types, manufacturing parameters, and quality optimization strategies that influence briquette performance are assessed. The co-densification of fine coal with biomass offers a means to enhance combustion efficiency, reduce dust emissions, and convert low-value waste into a high-calorific, manageable fuel. Attention is also given to briquette testing standards (i.e., South African Bureau of Standards, ASTM International, and International Organization of Standardization) and end-use applications across domestic, industrial, and off-grid settings. Moreover, the review explores socio-economic implications, including rural job creation, energy poverty alleviation, and the potential role of briquetting in SA’s ‘Just Energy Transition’ (JET). This paper uniquely integrates technical analysis with policy relevance, rural energy needs, and practical challenges specific to South Africa, while offering a structured framework for bio-coal briquetting adoption in developing countries. While technical and economic barriers remain, such as binder costs and feedstock variability, the integration of briquetting into circular economy frameworks represents a promising path toward cleaner, decentralized energy and coal waste valorization. Full article

(This article belongs to the Section A: Sustainable Energy)

17 pages, 2066 KiB

Open AccessArticle

A Mid-Term Scheduling Method for Cascade Hydropower Stations to Safeguard Against Continuous Extreme New Energy Fluctuations

by Huaying Su, Yupeng Li, Yan Zhang, Yujian Wang, Gang Li and Chuntian Cheng

Energies 2025, 18(14), 3745; https://doi.org/10.3390/en18143745 (registering DOI) - 15 Jul 2025

Abstract

Continuous multi-day extremely low or high new energy outputs have posed significant challenges in relation to power supply and new energy accommodations. Conventional reservoir hydropower, with the advantage of controllability and the storage ability of reservoirs, can represent a reliable and low-carbon flexibility [...] Read more.

Continuous multi-day extremely low or high new energy outputs have posed significant challenges in relation to power supply and new energy accommodations. Conventional reservoir hydropower, with the advantage of controllability and the storage ability of reservoirs, can represent a reliable and low-carbon flexibility resource to safeguard against continuous extreme new energy fluctuations. This paper proposes a mid-term scheduling method for reservoir hydropower to enhance our ability to regulate continuous extreme new energy fluctuations. First, a data-driven scenario generation method is proposed to characterize the continuous extreme new energy output by combining kernel density estimation, Monte Carlo sampling, and the synchronized backward reduction method. Second, a two-stage stochastic hydropower–new energy complementary optimization scheduling model is constructed with the reservoir water level as the decision variable, ensuring that reservoirs have a sufficient water buffering capacity to free up transmission channels for continuous extremely high new energy outputs and sufficient water energy storage to compensate for continuous extremely low new energy outputs. Third, the mathematical model is transformed into a tractable mixed-integer linear programming (MILP) problem by using piecewise linear and triangular interpolation techniques on the solution, reducing the solution complexity. Finally, a case study of a hydropower–PV station in a river basin is conducted to demonstrate that the proposed model can effectively enhance hydropower’s regulation ability, to mitigate continuous extreme PV outputs, thereby improving power supply reliability in this hybrid renewable energy system. Full article

(This article belongs to the Special Issue Optimal Schedule of Hydropower and New Energy Power Systems)

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24 pages, 1795 KiB

Open AccessArticle

An Empirically Validated Framework for Automated and Personalized Residential Energy-Management Integrating Large Language Models and the Internet of Energy

by Vinícius Pereira Gonçalves, Andre Luiz Marques Serrano, Gabriel Arquelau Pimenta Rodrigues, Matheus Noschang de Oliveira, Rodolfo Ipolito Meneguette, Guilherme Dantas Bispo, Maria Gabriela Mendonça Peixoto and Geraldo Pereira Rocha Filho

Energies 2025, 18(14), 3744; https://doi.org/10.3390/en18143744 (registering DOI) - 15 Jul 2025

Abstract

The growing global demand for energy has resulted in a demand for innovative strategies for residential energy management. This study explores a novel framework—MELISSA (Modern Energy LLM-IoE Smart Solution for Automation)—that integrates Internet of Things (IoT) sensor networks with Large Language Models (LLMs) [...] Read more.

The growing global demand for energy has resulted in a demand for innovative strategies for residential energy management. This study explores a novel framework—MELISSA (Modern Energy LLM-IoE Smart Solution for Automation)—that integrates Internet of Things (IoT) sensor networks with Large Language Models (LLMs) to optimize household energy consumption through intelligent automation and personalized interactions. The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. A 12-month randomized controlled trial was conducted with 100 households, which were stratified across four socioeconomic quintiles in metropolitan areas. The experimental design included the continuous collection of IoT data. Baseline energy consumption was measured and compared with post-intervention usage to assess system impact. Statistical analyses included k-means clustering, multiple linear regression, and paired t-tests. The system achieved its intended goal, with a statistically significant reduction of 5.66% in energy consumption (95% CI: 5.21–6.11%,

p < 0.001

) relative to baseline, alongside high user satisfaction (mean = 7.81, SD = 1.24). Clustering analysis (

k = 4

, silhouette = 0.68) revealed four distinct energy-consumption profiles. Multiple regression analysis (

R^{2} = 0.68

,

p < 0.001

) identified household size, ambient temperature, and frequency of user engagement as the principal determinants of consumption. This research advances the theoretical understanding of human–AI interaction in energy management and provides robust empirical evidence of the effectiveness of LLM-mediated behavioral interventions. The findings underscore the potential of conversational AI applications in smart homes and have practical implications for optimization of residential energy use. Full article

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27 pages, 578 KiB

Open AccessReview

Market Applications and Uncertainty Handling for Virtual Power Plants

by Yujie Jin and Ciwei Gao

Energies 2025, 18(14), 3743; https://doi.org/10.3390/en18143743 (registering DOI) - 15 Jul 2025

Abstract

Virtual power plants achieve the flexible scheduling and management of power systems by integrating distributed energy resources such as renewable energy sources, energy storage systems, and controllable loads. However, due to the instability of renewable energy generation, load demand fluctuations, and market price [...] Read more.

Virtual power plants achieve the flexible scheduling and management of power systems by integrating distributed energy resources such as renewable energy sources, energy storage systems, and controllable loads. However, due to the instability of renewable energy generation, load demand fluctuations, and market price uncertainty, virtual power plants face a gigantic challenge operating and participating in electricity markets. First, this paper outlines the functions and uncertainties of virtual power plants; then, it describes the uncertainties of virtual power plants in terms of aggregation, participation in market bidding, and optimal dispatch; finally, it summarizes the review. Full article

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22 pages, 3678 KiB

Open AccessArticle

Technical and Economic Analysis of a Newly Designed PV System Powering a University Building

by Miroslaw Zukowski and Robert Adam Sobolewski

Energies 2025, 18(14), 3742; https://doi.org/10.3390/en18143742 (registering DOI) - 15 Jul 2025

Abstract

The use of renewable energy sources on university campuses is crucial for sustainable development, environmental protection by reducing greenhouse gas emissions, improving energy security, and public education. This study addresses technical and economic aspects of the newly designed photovoltaic system on the campus [...] Read more.

The use of renewable energy sources on university campuses is crucial for sustainable development, environmental protection by reducing greenhouse gas emissions, improving energy security, and public education. This study addresses technical and economic aspects of the newly designed photovoltaic system on the campus of the Bialystok University of Technology. The first part of the article presents the results of 9 years of research on an experimental photovoltaic system that is part of a hybrid wind and PV small system. The article proposes five variants of the arrangement of photovoltaic panels on the pergola. A new method was used to determine the energy efficiency of individual options selected for analysis. This method combines energy simulations using DesignBuilder software and regression analysis. The basic economic indicators NPV and IRR were applied to select the most appropriate arrangement of PV panels. In the recommended solution, the panels are arranged in three rows, oriented vertically, and tilted at 37°. The photovoltaic system, consisting of 438 modules, has a peak power of 210 kWp and is able to produce 166,392 kWh of electricity annually. The NPV is 679,506 EUR, and the IRR is over 38% within 30 years of operation. Full article

(This article belongs to the Section J: Thermal Management)

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19 pages, 2017 KiB

Open AccessArticle

Analysis of Grid Scale Storage Effectiveness for a West African Interconnected Transmission System

by Julius Abayateye and Daniel Zimmerle

Energies 2025, 18(14), 3741; https://doi.org/10.3390/en18143741 (registering DOI) - 15 Jul 2025

Abstract

The West Africa Power Pool (WAPP) Interconnected Transmission System (WAPPITS) has faced challenges with frequency control due to limited primary frequency control reserves (PFRs). Battery Energy Storage Systems (BESSs) have been identified as a possible solution to address frequency control challenges and to [...] Read more.

The West Africa Power Pool (WAPP) Interconnected Transmission System (WAPPITS) has faced challenges with frequency control due to limited primary frequency control reserves (PFRs). Battery Energy Storage Systems (BESSs) have been identified as a possible solution to address frequency control challenges and to support growing levels of variable renewable energy in the WAPPITS. This paper uses a dynamic PSS/E grid simulation to evaluate the effectiveness of BESSs and conventional power plants for the maximum N-1 contingency scenario in WAPPITS—the loss of 400 MW of generation. BESSs outperform conventional power plants in fast frequency response; a BESS-only PFR mix produces the best technical performance for the metrics analyzed. However, this approach does not have the best marginal cost; a balanced mix of BESSs and conventional reserves achieves adequate performance on all metrics to meet grid requirements. This hybrid approach combines BESSs’ rapid power injection with the lower cost of conventional units, resulting in improved nadir frequencies (e.g., 49.70–49.76 Hz), faster settling times (1.00–2.20 s), and cost efficiency. The study indicates that an optimal approach to frequency control should include a combination of regulatory reforms and coordinated reserve procurement that includes BESS assets. Regulatory reforms should require or incentivize conventional plant to provide PFRs, possibly through creation of a (new to WAPPITS) market for ancillary services. While not a comprehensive analysis of all variables, these findings provide critical insights for policymakers and system operators. Full article

(This article belongs to the Special Issue Development and Modeling of Energy Storage Systems for Future Power Grids)

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16 pages, 4297 KiB

Open AccessArticle

The Influence of Absorber Properties on Operating Parameters and Electricity Generation in the Solar Chimney with a Vertical Collector

by Sylwia Berdowska

Energies 2025, 18(14), 3740; https://doi.org/10.3390/en18143740 (registering DOI) - 15 Jul 2025

Abstract

The paper presents an analysis of the operating parameters of a solar chimney with a non-selective and selective absorbers. The analyzed system consisted of a rectangular vertical collector integrated with a chimney. The collector surface was 30 m², while the installation [...] Read more.

The paper presents an analysis of the operating parameters of a solar chimney with a non-selective and selective absorbers. The analyzed system consisted of a rectangular vertical collector integrated with a chimney. The collector surface was 30 m², while the installation was 80 m high. The calculations were performed for the climatic conditions in Katowice, Poland. The work included an analysis of parameters such as air temperature increase and its velocity and mass flow in the solar chimney system. The cumulative amounts of electricity that can be obtained in each month of the year were shown. A comparison of electricity generation in the installation with an absorber covered with a non-selective coating and selective coatings was made. The installation with an absorber with an absorption coefficient of 0.95 and an emission coefficient of 0.05 allowed for the generation of the largest amount of electricity during the year. Full article

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

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26 pages, 2219 KiB

Open AccessArticle

High-Frequency Impedance of Rotationally Symmetric Two-Terminal Linear Passive Devices: Application to Parallel Plate Capacitors with a Lossy Dielectric Core and Lossy Thick Plates

by José Brandão Faria

Energies 2025, 18(14), 3739; https://doi.org/10.3390/en18143739 (registering DOI) - 15 Jul 2025

Abstract

Linear passive electrical devices/components are usually characterized in the frequency domain by their impedance, i.e., the ratio of the voltage and current phasors. The use of the impedance concept does not raise particular concerns in low-frequency regimes; however, things become more complicated when [...] Read more.

Linear passive electrical devices/components are usually characterized in the frequency domain by their impedance, i.e., the ratio of the voltage and current phasors. The use of the impedance concept does not raise particular concerns in low-frequency regimes; however, things become more complicated when it comes to rapid time-varying phenomena, mainly because the voltage depends not only on the position of the points between which it is defined but also on the choice of the integration path that connects them. In this article, based on first principles (Maxwell equations and Poynting vector flow considerations), we discuss the concept of impedance and define it unequivocally for a class of electrical devices/components with rotational symmetry. Two application examples are presented and discussed. One simple example concerns the per-unit-length impedance of a homogeneous cylindrical wire subject to the skin effect. The other, which is more elaborate, concerns a heterogeneous structure that consists of a dielectric disk sandwiched between two metal plates. For the lossless situation, the high-frequency impedance of this device (circular parallel plate capacitor) reaches zero when the frequency reaches a certain critical frequency f_c; then, it becomes inductive and increases enormously when the frequency reaches another critical frequency at 1.6 f_c. The influence of losses on the impedance of the device is thoroughly investigated and evaluated. Impedance corrections due to dielectric losses are analyzed using a frequency-dependent Debye permittivity model. The impedance corrections due to plate losses are analyzed by considering radial current distributions on the outer and inner surfaces of the plates, the latter exhibiting significant variations near the critical frequencies of the device. Full article

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20 pages, 3464 KiB

Open AccessArticle

Methodology of Determining the Intensity of Heat Exchange in a Polytunnel: A Case Study of Synergy Between the Polytunnel and a Stone Heat Accumulator

by Sławomir Kurpaska, Paweł Kiełbasa, Jarosław Knaga, Stanisław Lis and Maciej Gliniak

Energies 2025, 18(14), 3738; https://doi.org/10.3390/en18143738 (registering DOI) - 15 Jul 2025

Abstract

This paper presents the results of laboratory tests on the intensity of mass and heat exchange in a polytunnel, with a focus on the synergy between the polytunnel and a stone accumulator. The subject of study was a standard polytunnel made of double [...] Read more.

This paper presents the results of laboratory tests on the intensity of mass and heat exchange in a polytunnel, with a focus on the synergy between the polytunnel and a stone accumulator. The subject of study was a standard polytunnel made of double polythene sheathing. In the process of selecting the appropriate working conditions for such a polytunnel, the characteristic operating parameters were modeled and verified. They were related to the process of mass and energy exchange, which takes place in regular controlled-environment agriculture (CEA). Then, experimental tests of a heat accumulator on a fixed stone bed were carried out. The experiments were carried out for various accumulator surfaces ranging from 18.7 m² to 74.8 m², which was measured perpendicularly to the heat medium. To standardize the results obtained, the analysis included the unit area of the accumulator and the unit time of the experiment. In this way, 835 heat and mass exchange events were analyzed, including 437 accumulator charging processes and 398 discharging processes from April to October, which is a standard period of polytunnel use in the Polish climate. During the tests, internal and external parameters of the process were recorded, such as temperature, relative humidity, solar radiation, wind speed and air flow speed in the accumulator system. Based on the parameters, a set of empirical relationships was developed using mathematical modeling. This provided the foundation for calculating heat gains as a result of its storage in a stone accumulator and its discharging process. The research results, including the developed dependencies, not only fill the scientific gap in the field of heat storage, but can also be used in engineering design of polytunnels supported by a heat storage system on a stone bed. In addition, the proposed methodology can be used in the study of other heat accumulators, not only in plant production facilities. Full article

(This article belongs to the Section D: Energy Storage and Application)

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31 pages, 2741 KiB

Open AccessArticle

Power Flow Simulation and Thermal Performance Analysis of Electric Vehicles Under Standard Driving Cycles

by Jafar Masri, Mohammad Ismail and Abdulrahman Obaid

Energies 2025, 18(14), 3737; https://doi.org/10.3390/en18143737 (registering DOI) - 15 Jul 2025

Abstract

This paper presents a simulation framework for evaluating power flow, energy efficiency, thermal behavior, and energy consumption in electric vehicles (EVs) under standardized driving conditions. A detailed Simulink model is developed, integrating a lithium-ion battery, inverter, permanent magnet synchronous motor (PMSM), gearbox, and [...] Read more.

This paper presents a simulation framework for evaluating power flow, energy efficiency, thermal behavior, and energy consumption in electric vehicles (EVs) under standardized driving conditions. A detailed Simulink model is developed, integrating a lithium-ion battery, inverter, permanent magnet synchronous motor (PMSM), gearbox, and a field-oriented control strategy with PI-based speed and current regulation. The framework is applied to four standard driving cycles—UDDS, HWFET, WLTP, and NEDC—to assess system performance under varied load conditions. The UDDS cycle imposes the highest thermal loads, with temperature rises of 76.5 °C (motor) and 52.0 °C (inverter). The HWFET cycle yields the highest energy efficiency, with PMSM efficiency reaching 92% and minimal SOC depletion (15%) due to its steady-speed profile. The WLTP cycle shows wide power fluctuations (−30–19.3 kW), and a motor temperature rise of 73.6 °C. The NEDC results indicate a thermal increase of 75.1 °C. Model results show good agreement with published benchmarks, with deviations generally below 5%, validating the framework’s accuracy. These findings underscore the importance of cycle-sensitive analysis in optimizing energy use and thermal management in EV powertrain design. Full article

(This article belongs to the Special Issue Analysis of Energy Consumption and Energy Efficiency of Electric Vehicles)

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25 pages, 3162 KiB

Open AccessArticle

Advancing Energy-Efficient Renovation Through Dynamic Life Cycle Assessment and Costing: Insights and Experiences from VERIFY Tool Deployment

by Komninos Angelakoglou, Ioannis Lampropoulos, Eleni Chatzigeorgiou, Paraskevi Giourka, Georgios Martinopoulos, Angelos-Saverios Skembris, Andreas Seitaridis, Georgia Kousovista and Nikos Nikolopoulos

Energies 2025, 18(14), 3736; https://doi.org/10.3390/en18143736 (registering DOI) - 15 Jul 2025

Abstract

This study investigates the deployment of VERIFY, a dynamic life cycle assessment (LCA) and life cycle costing (LCC) tool, tailored to evaluate the energy and environmental performance of building renovation strategies. The tool was applied to three diverse building renovation projects across Europe, [...] Read more.

This study investigates the deployment of VERIFY, a dynamic life cycle assessment (LCA) and life cycle costing (LCC) tool, tailored to evaluate the energy and environmental performance of building renovation strategies. The tool was applied to three diverse building renovation projects across Europe, offering insights into how life cycle-based tools can enhance decision-making by integrating operational data and modeling of energy systems. The paper highlights how VERIFY captures both embodied and operational impacts—addressing limitations of conventional energy assessments—and aligns with EU frameworks such as Level(s). Key findings from the case studies in Italy, Spain, and the Netherlands demonstrate how LCA/LCC-based approaches can support energy efficiency objectives and guide sustainability-aligned renovation investments. Across the three case studies, the tool demonstrated up to 51% reduction in primary energy demand, 66% decrease in life cycle greenhouse gas emissions, and 51% reduction in life cycle costs. These outcomes provide researchers with a validated dynamic LCA/LCC framework and offer practitioners a replicable methodology for planning and evaluating sustainability-driven renovations. Despite their advantages, the effective use of LCA tools in energy renovation faces challenges, including limited data availability, regulatory fragmentation, and methodological complexity. The paper concludes that advanced tools such as VERIFY, when harmonized with evolving EU energy performance and sustainability standards, can strengthen the evidence base for deep energy renovation and carbon reduction in the building sector. Full article

(This article belongs to the Special Issue Sustainable Built Environment: Energy Efficiency Technologies, Performance Evaluation and Indoor Environment Quality)

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