Energy Reports最新文献

{"title":"Enhanced wireless power transfer for electric vehicles: A 7.2 kW ANN-based MPPT approach with LCC-LCC compensation topology","authors":"Bachhati Latha ,&nbsp;Mohammad Mujahid Irfan ,&nbsp;Butukuri Koti Reddy","doi":"10.1016/j.egyr.2025.08.039","DOIUrl":"10.1016/j.egyr.2025.08.039","url":null,"abstract":"<div><div>Optimizing electric vehicle charging via wireless power transfer is achievable through various control strategies. One effective method involves integrating an Artificial Neural Network based Maximum Power Point Tracking controller with a double-sided LCC compensation topology. This system, designed for a 7.2 kW inductive power transfer operating at 80 kHz<strong>,</strong> harnesses solar energy as its primary input. The ANN-based MPPT controller is trained to establish the optimal duty cycle for the DC-DC converter. It accomplishes this by learning the intricate relationship between photovoltaic voltage<strong>,</strong> current, and the maximum power point. This approach ensures robust MPP tracking performance even in diverse environmental conditions, including partial shading and noise. Furthermore, the double-sided LCC compensation network significantly boosts the system's power transfer capability and overall efficiency. The proposed system was meticulously modeled and simulated using MATLAB/Simulink<strong>.</strong> Simulation outcomes confirm that the combined ANN-based MPPT controller and double-sided LCC compensation deliver superior power transfer efficiency and enhanced output performance when compared to conventional WPT systems used for EV charging.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 2157-2169"},"PeriodicalIF":5.1,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144996864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Driving sustainable hydroelectric investments: Leveraging two-step logarithmic normalization for sustainable investment prioritization","authors":"Serhat Yüksel ,&nbsp;Serkan Eti ,&nbsp;Hasan Dinçer ,&nbsp;Dragan Pamucar ,&nbsp;Mustafa Hakan Saldı ,&nbsp;Edanur Ergün ,&nbsp;Vladimir Simic","doi":"10.1016/j.egyr.2025.08.047","DOIUrl":"10.1016/j.egyr.2025.08.047","url":null,"abstract":"<div><div>Hydroelectric energy investments involve substantial techno-economic risks that can increase costs and undermine economic sustainability if not properly managed. However, the literature lacks comprehensive studies addressing these risks. This study proposes a novel decision-making model to identify and prioritize strategies for effective risk management in hydroelectric projects. The model integrates z-scoring for expert selection, the Criteria Importance Assessment (CIMAS) method for weighting criteria, and the Alternative Ranking using Two-Step Logarithmic Normalization (ARLON) method for ranking EU-15 countries according to their strategies. Pythagorean fuzzy numbers are incorporated to better handle uncertainty and improve evaluation accuracy. Results indicate that challenges in adopting new technologies and grid integration issues are the most influential risk factors. The findings provide actionable insights for policymakers and investors to enhance the sustainability and efficiency of hydroelectric energy investments. Policymakers should implement targeted incentives and regulatory frameworks to accelerate technology adoption and address grid integration challenges in hydroelectric projects. Strategic planning should prioritize infrastructure modernization, cross-border energy cooperation, and capacity-building programs to enhance sector resilience and investment security.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 2110-2122"},"PeriodicalIF":5.1,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144988316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximum power tracking of a wind turbine using an adaptive barrier function global fast terminal sliding mode control approach","authors":"Zhong-wu Ma ,&nbsp;Le Shan ,&nbsp;Fei Wang ,&nbsp;Long He","doi":"10.1016/j.egyr.2025.08.040","DOIUrl":"10.1016/j.egyr.2025.08.040","url":null,"abstract":"<div><div>When a wind turbine operates in a region below the rated wind speed, it must track the desired rotor speed to maximize energy capture. However, uncertainties and unknown disturbances affect the speed and accuracy of the wind turbine in tracking this desired value. To address this issue, this paper proposes an adaptive barrier function global fast terminal sliding mode control method, recognized for its robustness and rapid convergence. The global fast terminal sliding mode combines the characteristics of traditional sliding mode and terminal sliding mode in the dynamic design of sliding mode, ensuring that the system state converges within a finite time and the tracking speed of the desired parameters of the wind turbine. The method introduces a barrier function whose intrinsic properties reduce the system's dependence on the uncertainty upper-bound setting, alleviate the chattering phenomenon, and guarantee the control accuracy. Furthermore, the control performance of the proposed method is compared with the two other methods in this paper under three wind speed conditions: step, random, and turbulent. In conclusion, the average settling time for the desired rotor speed of the proposed method is 6.94 % of other methods. The average maximum error and fluctuation range of the proposed method in tracking wind turbine parameters are 7.89 % and 10 % of other methods, respectively. The proposed method effectively improves the dynamic performance and accuracy of the wind turbine.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 2063-2074"},"PeriodicalIF":5.1,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144924721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing hybrid thermal energy storage in building management systems using data-driven model predictive control","authors":"Mustapha Habib ,&nbsp;Valeria Palomba ,&nbsp;Andrea Frazzica ,&nbsp;Qian Wang","doi":"10.1016/j.egyr.2025.08.033","DOIUrl":"10.1016/j.egyr.2025.08.033","url":null,"abstract":"<div><div>In most typical situations, thermal energy storage (TES) systems, which incorporate sensible and latent storage capacities, are not effectively utilized within the overall functions of building energy management systems (BEMSs), which usually rely on classical rule-based control (RBC). This study addresses the challenge of overcoming this by featuring model predictive control (MPC). The proposed method is based on modeling a water tank-integrated phase change material (PCM) using data-driven linear approximation generated with sparse regression. Based on the control objective, the proposed MPC can address two control targets, either providing robust and fast-tracking to the TES charging/discharging setpoints or reducing the energy cost related to the building heating needs. The digital simulation of a two-day scenario, using real operation conditions, demonstrates the effectiveness of the proposed MPC framework, showing up to 57 % heating cost reduction compared to the RBC scenario. As the real-time control requirement is critical, the MPC computing time was evaluated to assess its potential for integration into real-world applications within BEMS.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 2092-2109"},"PeriodicalIF":5.1,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IOT-enabled thermal and surface management system for PV modules coupled with a Cylindro-Parabolic Collector","authors":"Fares Touaref ,&nbsp;Istvan Seres ,&nbsp;Istvan Farkas","doi":"10.1016/j.egyr.2025.08.037","DOIUrl":"10.1016/j.egyr.2025.08.037","url":null,"abstract":"<div><div>This study presents the development and validation of a hybrid solar-powered desalination system that integrates photovoltaic (PV) panels, battery storage, a water pump, and a thermal distillation unit, enhanced by a compound parabolic concentrator (CPC) for improved solar energy capture. The novelty of the work lies in an Internet of Things (IoT)-enabled, fully automated three-dimensional (3D) cleaning and cooling mechanism, designed in SOLIDWORKS and controlled by an ESP32 microcontroller, which enables real-time operation based on environmental conditions. Unlike conventional systems, the proposed design combines dust detection, thermal regulation, and predictive analytics into a unified, low-maintenance platform suitable for off-grid applications. Field experiments in Gödöllő, Hungary, demonstrated an 8–15 % increase in irradiance capture, with summer peaks of 950 W/m² compared to 850 W/m² for unmaintained modules, and a 12 % improvement in daily energy yield, while efficiency was maintained within ±5 % across seasons. Statistical validation confirmed predictive accuracy with coefficients of determination (R²) between 97.5 % and 98.8 %, supported by other performance metrics. These findings highlight the potential of integrating IoT-based automation with hybrid photovoltaic-cylindroparabolic collector PV-CPC systems to ensure reliable year-round operation. By combining automated cleaning, thermal management, and real-time monitoring, this study establishes a scalable benchmark for sustainable solar desalination technologies that reduce maintenance requirements and support continuous energy and water production in remote and off-grid environments.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 2075-2091"},"PeriodicalIF":5.1,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144924722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Government subsidies, rent-seeking and investment efficiency in China's renewable energy industry: The suppressing role of R&D investment","authors":"Jiahui Xu ,&nbsp;Yanzi Li ,&nbsp;Walton Wider ,&nbsp;Shuhan Zhang","doi":"10.1016/j.egyr.2025.08.036","DOIUrl":"10.1016/j.egyr.2025.08.036","url":null,"abstract":"<div><div>Under China’s low-carbon transition strategy, renewable energy investment efficiency is essential to drive green transformation and meet carbon neutrality goals. This study investigates the impact of government subsidies on investment efficiency in China’s renewable energy sector, emphasizing the roles of Research and Development (R&amp;D) investment and rent-seeking behavior. Investment efficiency, measured inversely based on inefficient investment following the Richardson model, is negatively affected by subsidies (β = 0.0059, p &lt; 0.05), with rent-seeking further exacerbating this impact (β = 0.12, p &lt; 0.05 for the interaction term). R&amp;D investment suppresses the adverse influence of subsidies on investment efficiency, as subsidies positively affect R&amp;D investment (β = 0.0061, p &lt; 0.01) and R&amp;D investment positively influences investment efficiency (β = −0.104, p &lt; 0.05). The interaction between rent seeking and government subsidies reduces the effectiveness of subsidies in boosting R&amp;D investment (β = −0.109, p &lt; 0.05). Subsample analysis reveals that subsidies reduce investment efficiency in State-Owned Enterprises (SOEs) (β = 0.0085, p &lt; 0.1) but improve it in non-state-owned enterprises (non-SOEs) (β = −0.0143, p &lt; 0.05), with rent-seeking exacerbating inefficiency in SOEs (β = 0.146, p &lt; 0.05 for the interaction term). The study suggests that targeting subsidies based on firm characteristics and promoting innovation while avoiding rent-seeking could enhance their effectiveness and inform more sustainable and targeted energy policy interventions in the renewable energy sector.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 2047-2062"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144924720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the dynamics of artificial intelligence, renewable energy investment, and policy uncertainty in promoting green growth in China","authors":"Syed Tauseef Hassan ,&nbsp;Mehboob Ul Hassan","doi":"10.1016/j.egyr.2025.08.020","DOIUrl":"10.1016/j.egyr.2025.08.020","url":null,"abstract":"<div><div>As the world grapples with the challenge of balancing economic growth with environmental sustainability, the need for green growth has never been more pressing. This study examines the roles of artificial intelligence (AI), renewable energy investments (REI), and economic policy uncertainty (EPU) in shaping green growth in China, a country that is both a global leader in economic development and a major player in the green transition. Using a blend of innovative methods, including Dynamic Autoregressive Distributed Lag (DARDL) modeling, Kernel Regularized Least Squares (KRLS) machine learning, and Breitung-Candelon Spectral Granger-Causality analysis, we examine how these factors influence China’s sustainable development in both the short and long term. Our findings show that while AI and REI are key drivers of green growth, their full potential is hindered by the uncertainty surrounding economic policies. The results highlight that, without clear and stable policy frameworks, investments in green technologies are unlikely to reach their full potential. This study offers valuable insights into how AI and REI can be leveraged to foster sustainability, providing practical recommendations for policymakers to create the conditions necessary for green growth. Ultimately, it emphasizes the importance of stable, forward-thinking policies in enabling technological innovations to contribute meaningfully to a sustainable future for China and beyond.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 2015-2030"},"PeriodicalIF":5.1,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144920157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of BESS last-minutes reactions on short-term system imbalance forecasting accuracy in European energy markets","authors":"Samuel O. Ezennaya ,&nbsp;Godwin C. Okwuibe ,&nbsp;Julia Kowal","doi":"10.1016/j.egyr.2025.07.041","DOIUrl":"10.1016/j.egyr.2025.07.041","url":null,"abstract":"&lt;div&gt;&lt;div&gt;The increasing deployment of Battery Energy Storage Systems (BESS) in modern electricity markets has introduced new complexities in system imbalance (SI) forecasting, particularly due to last-minute balancing actions by Balance Responsible Parties (BRPs). Conventional forecasting models, which primarily rely on historical imbalance patterns and exogenous market features, often fail to capture the dynamic corrective responses of BESS, leading to substantial prediction inaccuracies. This study systematically evaluates the impact of key battery parameters, including maximum power capacity (&lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;max&lt;/mo&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;), depth of discharge &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;D&lt;/mi&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;D&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, and energy-to-power &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; ratio, on forecasting accuracy. A battery-aware autoregressive (AR) model is developed to explicitly integrate these factors, with predictive performance benchmarked against conventional models under both static and dynamic battery dispatch conditions. The analysis establishes well-defined operational stability constraints, demonstrating that forecast errors remain within considerably limits (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mtext&gt;MAE&lt;/mtext&gt;&lt;mo&gt;≤&lt;/mo&gt;&lt;mn&gt;100&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; MW) when &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;max&lt;/mo&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;≈&lt;/mo&gt;&lt;mn&gt;416&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; MW, &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mtext&gt;DOD&lt;/mtext&gt;&lt;mo&gt;≤&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;92&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, and the &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; ratio is maintained either at &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;mo&gt;≤&lt;/mo&gt;&lt;mn&gt;4&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;64&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; or &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;mn&gt;6&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;94&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. However, within the intermediate range &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mn&gt;4&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;64&lt;/mn&gt;&lt;mo&gt;&lt;&lt;/mo&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;mo&gt;&lt;&lt;/mo&gt;&lt;mn&gt;6&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;94&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, forecast errors exceed 100 MW, introducing instability and reducing predictive reliability. Notably, when &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;max&lt;/mo&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; is below 416 MW, variations in &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;D&lt;/mi&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;D&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; exhibit minimal influence on forecast accuracy concerning the 100 MW MAE threshold. These findings underscore the intricate interdependencies among BESS parameters, highlighting the destabilizing effects of high-power dispatch, extended storage durations, and deep discharge cycles beyond these defined thresholds. Comparisons against the Elia forecast and a Naïve benchmark confirm that the battery-aware model enhances forecasting accuracy, improving MAE by up to 13.39%,","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1964-1979"},"PeriodicalIF":5.1,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal and hydraulic performance of microencapsulated phase change material slurries in a microchannel heat sink","authors":"Rabia Shaukat ,&nbsp;Adnan Qamar ,&nbsp;Muhammad Adeel Munir ,&nbsp;Muhammad Amjad ,&nbsp;Shafiq Ahmad ,&nbsp;Fahid Riaz ,&nbsp;S.A. Sherif ,&nbsp;Shahid Imran","doi":"10.1016/j.egyr.2025.08.008","DOIUrl":"10.1016/j.egyr.2025.08.008","url":null,"abstract":"<div><div>The distinctive capability of Phase Change Materials (PCMs) to store and release thermal energy during the phase change process makes them important materials for tackling the energy efficiency-related challenges faced by modern compact energy systems. In this context, the present study explores the thermal and hydraulic performance of microencapsulated phase change materials (mPCMs) with a specific melting point of 37°C within a microchannel heat sink (MCHS) operating under convective heat transfer conditions. Various performance parameters, including the thermal boundary layer (TBL), bulk fluid mean temperature, wall temperature, the local and average Nusselt numbers (<em>Nu</em>), the pressure drop (ΔP) across the MCHS, and the performance evaluation factor (PEF), were investigated under varying mass concentrations (5–15 %) and inlet velocities (0.55–1.20 m/s) of the mPCMs. The increase in the <em>Nu</em> and ΔP was found to be 21 % and 16.7 %, respectively, at an inlet velocity of 1.2 m/s and a mass concentration of 15 %. The PEF was found to reach a maximum value of 1.29 for a mass concentration of 10 % and an inlet velocity of 1.2 m/s. The PEF is a quantity that balances the gains achieved in heat transfer with the associated penalties due to the increase in pressure drop. These pressure drop penalties typically occur due to an increase in the viscosity of the slurry due to the rise of the mass concentration of the mPCMs. Parametric sensitivity analysis for key thermophysical properties, confirmed the robustness of the CFD model under ±10 % variations. The significant improvement in the thermal performance of the mPCM slurry underscores its potential for heat transfer and thermal energy storage in modern energy systems. Integrating mPCMs with microchannel heat exchange systems will enhance the energy efficiency of modern thermal energy storage and heat transfer systems and reduce operational and maintenance costs.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1949-1963"},"PeriodicalIF":5.1,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal sizing of smart hybrid renewable energy system using Lotus Effect Optimization Algorithm","authors":"Mohammed Al-Shalabi ,&nbsp;Mohammad Shehab ,&nbsp;Mohammad T. Alshammari ,&nbsp;Meshari Alazmi ,&nbsp;Rami O. Alrawashdeh ,&nbsp;Laith Abualigah ,&nbsp;Mohammed A. Mahdi","doi":"10.1016/j.egyr.2025.08.007","DOIUrl":"10.1016/j.egyr.2025.08.007","url":null,"abstract":"<div><div>The increasing demand for sustainable and cost-effective energy solutions has prompted the integration of Hybrid Renewable Energy Systems (HRES), which combine solar, wind, and storage technologies. This study proposes an optimized HRES sizing framework utilizing the Lotus Effect Optimization Algorithm (LEOA), a novel nature-inspired metaheuristic approach known for its robust performance in solving multiobjective nonlinear problems. Research focuses on minimizing the Levelized Cost of Energy (LCOE), enhancing system reliability, and reducing environmental impact. A real-world case study from Qassim, Saudi Arabia, is presented to validate the proposed method. The results show that LEOA outperforms conventional algorithms, including PSO, GA, SA, and MOPSO, in terms of convergence speed, solution accuracy, and computational efficiency. The proposed algorithm achieved the lowest LCOE ($0.275/kWh), the highest penetration of renewable energy (85%) and the maximum reduction of <span><math><mrow><mi>C</mi><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></math></span> emissions (40%). These findings highlight the effectiveness of the proposed algorithm in the design of cost-effective, reliable, and environmentally sustainable HRES configurations, making it a promising tool for future smart grid applications.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1936-1948"},"PeriodicalIF":5.1,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}