Renewable Energy最新文献

{"title":"Advanced energy management strategy for enhancing battery lifespan in solar PV-powered EV charging stations with hybrid energy storage systems","authors":"Jayant Sharma ,&nbsp;Chinnayan Karuppaiyah Sundarabalan ,&nbsp;Chelladurai Balasundar","doi":"10.1016/j.renene.2025.123443","DOIUrl":"10.1016/j.renene.2025.123443","url":null,"abstract":"<div><div>Electric Vehicle Charging Stations (EVCS) with Solar Photovoltaic (PV) integration require efficient power management to ensure grid stability and battery longevity. This study proposes a hybrid energy storage system (HESS) utilizing Superconducting Magnetic Energy Storage (SMES) and Battery Energy Storage System (BESS) to mitigate transient power fluctuations and optimize energy distribution. The proposed current control strategy is validated through MATLAB/Simulink simulations under Variable Load Constant Generation (VLCG) and Constant Load Variable Generation (CLVG) scenarios. The results indicate that SMES integration reduces the peak battery current by 52.63 % and 32.72 % following the connections of EV-1 and EV-2, respectively, thereby enhancing battery lifespan. Additionally, real-time validation using the dSPACE DS1202 platform confirms that the proposed system effectively stabilizes grid voltage and optimizes power flow under varying load and power generation conditions. The findings demonstrate the efficacy of the HESS in reducing peak transient currents and improving the overall reliability of solar PV-supported EVCS.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123443"},"PeriodicalIF":9.0,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fault warning study of gearbox based on SOM-ASTGCN-BiLSTM and mutual diagnosis of same clustered wind turbines","authors":"Bo Gu ,&nbsp;Hongtao Zhang ,&nbsp;Shuai Yue ,&nbsp;Konstantin Suslov ,&nbsp;Jie Shi","doi":"10.1016/j.renene.2025.123442","DOIUrl":"10.1016/j.renene.2025.123442","url":null,"abstract":"<div><div>Accurate warning of the low-speed bearing temperature of a wind turbine gearbox is the basis for ensuring its healthy and stable operation. Therefore, a gearbox fault warning method based on self-organizing map (SOM)-attention-based spatiotemporal graph convolutional network (ASTGCN)- bidirectional long short-term memory network (BiLSTM) and mutual diagnosis of the same clustered wind turbines was proposed. This method utilizes the SOM clustering algorithm to cluster wind turbines with similar external environments and operation states into one cluster, which provides support for the mutual diagnosis of the operation states of the same clustered wind turbines. An ASTGCN was used to deeply mine the spatiotemporal correlation characteristics between the operating state data of the wind turbine and the temperature value of the gearbox low-speed bearing. A BiLSTM was used to bidirectionally mine the temporal correlation between the operating state data of the wind turbine and the temperature value of the gearbox low-speed bearing, and a forecasting model of the gearbox low-speed bearing temperature based on ASTGCN-BiLSTM was constructed. The temperature of the gearbox low-speed bearings of the same clustered wind turbines exhibited a similar dynamic change process. By comparing and analyzing the distribution characteristics of the forecasted temperature values of the gearbox low-speed bearings of the same clustered wind turbines, it is possible to accurately identify wind turbines with abnormal gearbox operating states. Taking a certain wind farm as the calculation object, the calculation results show that the forecasting accuracy of the proposed SOM-ASTGCN-BiLSTM model is higher than that of other models such as ASTGCN, Reformer, Transformer, Informer, Pyraformer, QR-LSTM, and PSO-ELM, proving the superiority of the algorithm proposed in this study. The mutual-diagnosis strategy for the same clustered wind turbines can accurately identify wind turbines with abnormal gearboxes.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123442"},"PeriodicalIF":9.0,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and performance evaluation of an innovative solar concentration polygeneration system","authors":"Gang Wang ,&nbsp;Dongyu Li ,&nbsp;Tianlin Zou ,&nbsp;Yanfeng Duan","doi":"10.1016/j.renene.2025.123441","DOIUrl":"10.1016/j.renene.2025.123441","url":null,"abstract":"<div><div>This paper presents an innovative solar concentration polygeneration system with super-critical carbon dioxide (S-CO₂) Brayton and organic Rankine cycles. It is developed for generating electric power, freshwater and hydrogen. Operation, exergetic and economic performances of the polygeneration system are evaluated. The evaluation results show that the electric power and S-CO₂ Brayton cycle efficiency of the polygeneration system are 50.0 MW and 44.0 %. The hydrogen and freshwater production rates of the polygeneration system are 6.24 kg/h and 393.55 t/h. The linear Fresnel reflector solar loop, S-CO₂ Brayton cycle, hydrogen production and freshwater production blocks can coordinatively achieve the effective operation for both short and long terms. The LFR solar field has the largest exergetic loss (97.3 MW) and its exergetic efficiency is 63.8 %. The levelized costs of electricity, freshwater and hydrogen of the polygeneration system are 0.106 $/kWh, 0.98 $/t and 3.51 $/kg, respectively. The net present value is about 478.0 million USD. These results reveal the technical and economic viability of the polygeneration system.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123441"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A built-in charging electret rotational energy harvester for kinetic energy at ultra-low frequency","authors":"Weihan Xu ,&nbsp;Shanghao Gu ,&nbsp;Anxin Luo ,&nbsp;Kai Tao ,&nbsp;Fei Wang","doi":"10.1016/j.renene.2025.123407","DOIUrl":"10.1016/j.renene.2025.123407","url":null,"abstract":"<div><div>In harsh environments, extreme temperature or humidity may lead to the decay in the surface potential of electrets in open structures. When electret materials in energy harvesters need to be charged to maintain polarization, disassembling harvesters or separating electret films from harvesters is generally an unavoidable procedure, which complicates the charging process and increases maintenance costs. At present, there is no ideal built-in charging method for electret materials in non-resonant structures that can balance low cost, safety, and simple operation. Herein, we propose a built-in charging electret rotational energy harvester (BIC-EREH), which can achieve the contact charging of the fluorinated ethylene propylene (FEP) film using a gap-adjustable platform and interdigital electrodes inside the harvester. After charging, the surface potential of the FEP film can reach over −1200 V. The interdigital electrodes in the BIC-EREH are not only used to recharge the FEP film but also serve as a component of an electret transducer to participate in electrical energy conversion. Based on a pawl-ratchet clutch driver, the harvester can output uninterruptedly even under ultra-low frequency excitation. Under one excitation with a velocity of 200 mm/s, the harvester can continuously output for about 23 s with a peak power of 98.2 μW, generating electric energy of about 0.4 mJ. Over a broad bandwidth (0.1–2 Hz), the harvester still has a stable output power. Furthermore, the BIC-EREH has high stability in a high humidity environment and the attenuated output performance can be perfectly restored with an average output power of 85.4 μW after built-in charging. Finally, the harvester is successfully applied as the power supply to drive a wireless sensor node. The study has considerable significance for sustainable power supply of electret energy harvesters in wireless sensor nodes.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123407"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing efficient market interventions through isoprofit modelling to accelerate the decarbonisation of power systems","authors":"Pablo Faúndez ,&nbsp;Enzo Sauma ,&nbsp;Miguel Pérez de Arce ,&nbsp;Sonia Vera ,&nbsp;Jazmine Calabrese ,&nbsp;Pablo Osses ,&nbsp;Francisco Manríquez ,&nbsp;Andrés Pereira","doi":"10.1016/j.renene.2025.123398","DOIUrl":"10.1016/j.renene.2025.123398","url":null,"abstract":"<div><div>We propose a framework to design cost-free market interventions aiming to accelerate the decarbonisation of power systems. The framework relies on isoprofit modeling and partial equilibrium analysis of supply curve shifts brought about by the interventions. As opposed to Levelised Cost of Energy (LCOE) based techniques, the isoprofit approach uses a fully-fledged profit function allowing for the study of tax collection effects of interventions. Because it uses geographical information system tools, results are sensitive to the territorial exclusion criteria employed. We specifically analyse the reduction of wind farms' corporate income tax rate as a market intervention subject to tax revenue neutrality. We apply the proposed framework in a territory of Chile, which is the source and destination of wind energy in the context of the decarbonisation of a simplified power system. Our results yield a shortening of the complete decarbonisation process by three years. Because the intervention has no additional cost for consumers and brings forward in time any producers’ surplus, it produces a welfare improvement. Using this framework to prescribe similar market interventions for other territories can help to the rapid and cost-efficient attainment of a low-carbon global economy.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123398"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144083946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-stage optimal scheduling strategy for community integrated energy system based on uncertainty and integrated demand response model","authors":"Shengcheng Wu ,&nbsp;Aiping Pang","doi":"10.1016/j.renene.2025.123373","DOIUrl":"10.1016/j.renene.2025.123373","url":null,"abstract":"<div><div>This study presents an optimization management framework for community integrated energy systems. First, the output scenarios of renewable energy are generated by the Monte Carlo method, and the K-means method is used to reduce the scenarios. According to the spatio-temporal characteristics of electric vehicles, this study proposes a charging/discharging decision-making method based on the fuzzy theory. Moreover, an integrated demand response model based on the real-time price mechanism and a two-stage optimization scheduling strategy is formulated. The results show that, compared with two traditional scenarios, the proposed strategy reduces comprehensive operating costs on typical days by 8.81% and 3.22% in summer and 6.55% and 3.33% in winter, respectively, while ensuring overall satisfaction. This study also analyzes the impact of the number of electric vehicles and the weight of the objective function on the optimization scheduling results.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123373"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EnergyGPT: Fine-tuning large language model for multi-energy load forecasting","authors":"Min Liang,&nbsp;Yongli Hu,&nbsp;Haoen Weng,&nbsp;Jiayang Xi,&nbsp;Baocai Yin","doi":"10.1016/j.renene.2025.123313","DOIUrl":"10.1016/j.renene.2025.123313","url":null,"abstract":"<div><div>Multi-energy load forecasting plays a pivotal role in strategy management and operational planning in integrated energy systems (IESs). However, the inherent complexity and high dynamicity of IESs bring significant challenges, including modeling the coupling relationships between relevant features and designing effective forecasting models. The traditional statistical methods for feature correlation analysis struggle to reveal the dynamic correlation of feature sequences, and the classic data-driven machine learning methods for multi-energy load forecasting suffer from a lack of generalization. To address these issues, inspired by the successful applications of pre-trained large models in specific tasks, this paper introduces a large language model (LLM) into the energy field and proposes a novel multi-energy load forecasting model based on GPT2, called EnergyGPT, which utilizes the knowledge and capabilities of LLMs trained on a massive text stream corpus to enhance generalization and performance in multi-energy load forecasting. Additionally, EnergyGPT adopts a dynamic self-attention module to adjust the importance of sequential features. The proposed EnergyGPT is evaluated on the real load data from the Tempe campus provided by Arizona State University’s online platform, compared with a set of the latest load forecasting methods. The experimental results show that EnergyGPT outperforms all the comparisons with the best performance in four seasons, which validates the effectiveness of EnergyGPT and shows the potential of large models for cross-domain applications.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123313"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical study on a novel backward bent duct buoy wave energy converter with ‘ducktail’ deflector","authors":"Huanbin Yang ,&nbsp;Yongliang Zhang","doi":"10.1016/j.renene.2025.123434","DOIUrl":"10.1016/j.renene.2025.123434","url":null,"abstract":"<div><div>On the basis of the backward bent duct buoy (BBDB) wave energy converter (WEC), this paper proposes a novel BBDB WEC with a ‘ducktail’ deflector, aiming to further improve capture width ratio (CWR), expand efficient working range, and increase annual power generation. For developing the new device, a 32.5 m-wide numerical wave channel is established and validated. The validated numerical model is used to explore the performance of the 6.5 m-wide full-scale new device, especially the influence of ‘ducktail’ deflector's geometric parameters on the CWR and frequency response bandwidth of the new device. The optimal deflector width, length, inclination angle, as well as the horizontal and vertical distances between the deflector and the BBDB are obtained. The results reveal that, compared with the original BBDB WEC without deflector, CWR of the optimized new device with a deflector increases by 18.5 % under the typical wave condition of the planned deployment site (wave period 4.25s, wave height 1 m), and the wave period range with CWR higher than 1.0 is expanded by 100 % (wave height 1 m). Also, the mechanisms underlying CWR improvement and efficient working range expansion by using the ‘ducktail’ deflector under various waves are revealed from different perspectives.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123434"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective optimization of hydraulic performance of an ultra-low head axial-flow turbine with improved blade camber line configuration","authors":"Huixiang Chen ,&nbsp;Xiaobo Li ,&nbsp;Feng Zhao ,&nbsp;Jinbo Chen ,&nbsp;Mossandre Aboule Léonce ,&nbsp;Kan Kan","doi":"10.1016/j.renene.2025.123432","DOIUrl":"10.1016/j.renene.2025.123432","url":null,"abstract":"<div><div>Against the backdrop of the progressive and comprehensive development of large-scale hydroelectric facilities, there remains a considerable number of untapped low-head river segments in rural, remote, and hilly areas. Low-head hydropower technology, renowned for its versatility and minimal environmental impact, is the optimal power generation solution for such areas. This technology's high potential and efficiency underscore its crucial role in developing small, low-head hydropower systems. This paper introduces a camber line configuration method that utilizes two segments of second-order Bézier curves based on a fish-friendly ultra-low head axial flow turbine model developed using standard modular hydropower technology. The method accurately describes and controls the maximum camber position of the airfoil during the optimization process, allowing for a decoupling of the blade camber line placement angle and the maximum camber in the airfoil design. Based on the enhanced bone-line design method, optimization is conducted with the specific goal of improving the hydraulic efficiency and output power of the hydraulic turbine. As a result, a remarkable efficiency improvement of 2.79 % and a substantial output power enhancement of 5.93 % were successfully attained, respectively. The analysis indicates that the enhanced bone-line design enables a closer alignment of the fluid flow within the turbine with the desired ideal flow pattern. Consequently, it effectively diminishes internal entropy production losses, improves the pressure distribution on the blades, and ultimately achieves a significant enhancement in turbine performance. These research findings provide valuable insights and references for the bone-line configuration in optimizing the hydraulic design of ultra-low head hydraulic turbines.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123432"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active load control applied to upscaled wind turbines: Design and cost impacts","authors":"Ipsita Mishra,&nbsp;Mayank Chetan,&nbsp;M. Sadman Sakib,&nbsp;D. Todd Griffith,&nbsp;Abhineet Gupta,&nbsp;Mario A. Rotea","doi":"10.1016/j.renene.2025.123411","DOIUrl":"10.1016/j.renene.2025.123411","url":null,"abstract":"<div><div>This study examines the combined effect of rotor upscaling and active load control (ALC), whereby ALC is used to offset the negative impacts of increased loads from an upscaled rotor that produces higher energy capture. Consequently, there is growing interest in innovative load control techniques to mitigate these excessive loads and their associated impacts on increased cost. In this study, ALC is implemented using controllable gurney flaps based on plasma actuators where we assess the impacts of upscaling and ALC on 1) loads of all major turbine components, 2) sizing of turbine components, 3) cost of energy including capital expenditures (CapEx), operating expenditures (OpEx), annual energy production (AEP), and ultimately the levelized cost of energy (LCOE). Additionally, ALC effects are examined for Region III-only operation and full-range, i.e., Region II and Region III. Upscaling is examined via two distinct scenarios: a power-uprated turbine design with a 6.3 % upscaled rotor and higher power rating (and higher structural loads), and a load-limited turbine design with the same increase in rotor size but maintaining the reference turbine power rating (to maintain or limit the load increase). Using a 3.4 MW reference wind turbine design, we maintain baseline performance limits with respect to the reference design for the tip deflection, mean stresses, and fatigue stresses in the upscaled design with ALC during the component resizing process. This resizing approach led to changes in CapEx, OpEx, AEP, and LCOE. Among the upscaled designs, the load-limited turbine with ALC achieved a slightly higher LCOE reduction of up to 4.9 % compared to 4.1 % for the power-uprated turbine, under full-range ALC operation. Overall, the load-limited upscaled design with ALC emerges as the marginally more favorable configuration, achieving greater LCOE reduction through a substantial AEP increase in Region II (due to upscaling), fatigue load reductions in critical components (via ALC), and relatively smaller capital cost increases compared to the power-uprated design, despite the latter yielding similar LCOE reductions. As a result, this work presents a comprehensive assessment of how ALC impacts component sizing and economics and compares upscaled designs (3.4B) with the 3.4A (retrofit) design, providing insights to designers and operators to most effectively use ALC in upscaled wind turbines.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"251 ","pages":"Article 123411"},"PeriodicalIF":9.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}