Global Energy Interconnection最新文献_第7页

Enhanced physics-inspired algorithm for optimal power flow with renewable energy integration using Coulomb’s and Franklin’s law under climate considerations 在气候条件下，基于库仑和富兰克林定律的可再生能源整合优化潮流的增强物理启发算法

IF 2.6

Global Energy Interconnection Pub Date : 2025-12-01 Epub Date: 2025-07-25 DOI: 10.1016/j.gloei.2025.05.006

Saeid Jowkar , Amin Besharatiyan , Ali Esmaeel Nezhad , Ehsan Rahimi , Fariba Esmaeilnezhad , Toktam Tavakkoli Sabour , Mohammadamin Mobtahej , Afshin Canani

{"title":"Enhanced physics-inspired algorithm for optimal power flow with renewable energy integration using Coulomb’s and Franklin’s law under climate considerations","authors":"Saeid Jowkar , Amin Besharatiyan , Ali Esmaeel Nezhad , Ehsan Rahimi , Fariba Esmaeilnezhad , Toktam Tavakkoli Sabour , Mohammadamin Mobtahej , Afshin Canani","doi":"10.1016/j.gloei.2025.05.006","DOIUrl":"10.1016/j.gloei.2025.05.006","url":null,"abstract":"<div><div>Due to the climate-dependent nature of renewable energy sources (RESs), solving the optimal power flow (OPF) problem in power systems that integrate RESs, such as photovoltaic (PV) units and wind turbines (WTs), remains a significant challenge. To address this problem, this study presents an effective framework that incorporates solar and wind power generation. To manage the nonconvex and nonlinear characteristics of the OPF problem, a modified physics-inspired algorithm termed the Enhanced Coulomb’s and Franklin’s laws Algorithm (ECFA), is deployed. In the proposed OPF model, the power generated from RESs is considered a dependent variable, while voltages at buses equipped with RESs serve as decision variables. Real-time data on solar irradiation and wind speed are used to model the power outputs of PV units and WTs, respectively. Although the Coulomb’s and Franklin’s law algorithm (CFA) offers some advantages, it underperforms on complex optimization tasks compared to SSA, BA, SCA, ABC, and CFA. The enhanced version of the CFA improves the search process across the feasible space by incorporating diverse interaction methods and enhancing exploitation capabilities. The performance of the proposed ECFA is assessed through comprehensive comparisons with state-of-the-art methods for solving the OPF problem.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 982-996"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time dispatch strategy for microgrid considering source‒load uncertainty: a tailored TD3 reinforcement learning approach 考虑源负荷不确定性的微电网实时调度策略：一种定制TD3强化学习方法

IF 2.6

Global Energy Interconnection Pub Date : 2025-12-01 Epub Date: 2025-11-07 DOI: 10.1016/j.gloei.2025.10.003

Shenpeng Xiang , Mohan Lin , Zhe Chen , Pingliang Zeng , Xiangjin Wang , Diyang Gong

{"title":"Real-time dispatch strategy for microgrid considering source‒load uncertainty: a tailored TD3 reinforcement learning approach","authors":"Shenpeng Xiang , Mohan Lin , Zhe Chen , Pingliang Zeng , Xiangjin Wang , Diyang Gong","doi":"10.1016/j.gloei.2025.10.003","DOIUrl":"10.1016/j.gloei.2025.10.003","url":null,"abstract":"<div><div>The integration of large-scale-distributed new energy resources has led to heightened source‒load uncertainty. As energy prosumers, microgrids urgently require enhanced real-time regulation capabilities over controllable resources amid uncertain environments, rendering real-time and rapid decision-making a critical issue. This paper proposes a tailored twin delayed deep deterministic policy gradient (TD3) reinforcement learning algorithm that explicitly accounts for source‒load uncertainty. First, following an expert experience-based methodology, Gaussian process regression was implemented using the radial basis function covariance with historical source and load data. The parameters were adaptively adjusted by maximum likelihood estimation to generate the expected curves of demand and wind‒solar power generation, along with their 95% confidence regions, which were treated as representative uncertainty scenarios. Second, the traditional scheduling model was transformed into a deep reinforcement learning (DRL) environment through a Markov process. To minimize the total operational cost of the microgrid, the tailored TD3 algorithm was applied to formulate rapid intraday scheduling decisions. Finally, simulations were conducted using real historical data from an actual region in Zhejiang province, China, to verify the efficacy of the proposed method. The results demonstrate the potential of the algorithm for achieving economic scheduling for microgrids.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 905-917"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital twin topology modelling method of new-type distribution network based on CIM specifications and spectral clustering 基于CIM规范和谱聚类的新型配电网数字孪生拓扑建模方法

IF 2.6

Global Energy Interconnection Pub Date : 2025-12-01 Epub Date: 2025-11-07 DOI: 10.1016/j.gloei.2025.05.012

Zhimin He , Hai Yu , Lin Peng , Aihua Zhou , He Wang , Jin Xu

{"title":"Digital twin topology modelling method of new-type distribution network based on CIM specifications and spectral clustering","authors":"Zhimin He , Hai Yu , Lin Peng , Aihua Zhou , He Wang , Jin Xu","doi":"10.1016/j.gloei.2025.05.012","DOIUrl":"10.1016/j.gloei.2025.05.012","url":null,"abstract":"<div><div>Regard to the real-time dynamic digital twin modelling problem of a new-type distribution network that includes distributed resources such as distributed photovoltaic, energy storage, charging pile, and electric vehicle, a new-type distribution network digital twin topology modeling method based on Common Information Model (CIM) specifications and spectral clustering is proposed. Firstly, according to the specifications of the CIM standard, the digital twin topology models of distributed resources are extended and established. Secondly, based on the digital twin topology models of distributed resources, a digital twin aggregation modelling method for new-type distribution network is proposed based on spectral clustering. Furthermore, an online linked update strategy for the digital twin model of new-type distribution network that integrates real-time topology states is proposed. Finally, a case study is conducted on a distribution network in a certain demonstration area in China, and the results verify the practicability and effectiveness of the method proposed in this paper. This lays the foundation for the application of electrical network twin analysis, such as power flow calculation, optimal power flow, economic dispatch, and safety check, in a new-type distribution network that includes diversified distributed resources.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 947-958"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi-model management approach for power system transient stability assessment based on multi-moment feature clustering 基于多矩特征聚类的电力系统暂态稳定评估多模型管理方法

IF 2.6

Global Energy Interconnection Pub Date : 2025-10-01 Epub Date: 2025-06-25 DOI: 10.1016/j.gloei.2025.01.009

Xiaoyu Han , Tao Liu , Defu Cai , Rusi Chen , Erxi Wang , Jinfu Chen

{"title":"A multi-model management approach for power system transient stability assessment based on multi-moment feature clustering","authors":"Xiaoyu Han , Tao Liu , Defu Cai , Rusi Chen , Erxi Wang , Jinfu Chen","doi":"10.1016/j.gloei.2025.01.009","DOIUrl":"10.1016/j.gloei.2025.01.009","url":null,"abstract":"<div><div>Transient stability assessment (TSA) based on artificial intelligence typically has two distinct model management approaches: a unified management approach for all faulted lines and a separate management approach for each faulted line. To address the shortcomings of the aforementioned approaches, namely accuracy, training time, and model management complexity, a multi-model management approach for power system TSA based on multi-moment feature clustering has been proposed. First, the steady-state and transient features present under fault conditions were obtained through a transient simulation of line faults. The input sample set was then constructed using the aforementioned multi-moment electrical features and the embedded faulty line numbers. Subsequently, K-means clustering was conducted on each line based on the similarity of their electrical features, employing t-SNE dimensionality reduction. The PSO-CNN model was trained separately for each cluster to generate several independent TSA models. Finally, a model effectiveness evaluation system consisting of five metrics was established, and the effect of the sample imbalance ratio on the model effectiveness was investigated. The model effectiveness was evaluated using the IEEE 39-bus system algorithm. The results showed that the multi-model management strategy based on multi-moment feature clustering can effectively combine the two advantages of superior evaluation performance and streamlined model management by fully extracting system features. Moreover, this approach allows for more flexible adjustments to line topology changes.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 5","pages":"Pages 847-857"},"PeriodicalIF":2.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing off-grid energy solutions: a hybrid approach leveraging solar, wind, and biomass for sustainable development 优化离网能源解决方案：利用太阳能、风能和生物质能促进可持续发展的混合方法

IF 2.6

Global Energy Interconnection Pub Date : 2025-10-01 Epub Date: 2025-08-27 DOI: 10.1016/j.gloei.2025.05.008

Anouar Makhoukh, Abdelbari Redouane, Norddine Oubouch, Abdennebi El Hasnaoui

引用次数: 0

Forecasting electricity prices in the spot market utilizing wavelet packet decomposition integrated with a hybrid deep neural network 基于小波包分解和混合深度神经网络的现货市场电价预测

IF 2.6

Global Energy Interconnection Pub Date : 2025-10-01 Epub Date: 2025-06-11 DOI: 10.1016/j.gloei.2025.03.003

Heping Jia , Yuchen Guo , Xiaobin Zhang , Qianxin Ma , Zhenglin Yang , Yaxian Zheng , Dan Zeng , Dunnan Liu

{"title":"Forecasting electricity prices in the spot market utilizing wavelet packet decomposition integrated with a hybrid deep neural network","authors":"Heping Jia , Yuchen Guo , Xiaobin Zhang , Qianxin Ma , Zhenglin Yang , Yaxian Zheng , Dan Zeng , Dunnan Liu","doi":"10.1016/j.gloei.2025.03.003","DOIUrl":"10.1016/j.gloei.2025.03.003","url":null,"abstract":"<div><div>Accurate forecasting of electricity spot prices is crucial for market participants in formulating bidding strategies. However, the extreme volatility of electricity spot prices, influenced by various factors, poses significant challenges for forecasting. To address the data uncertainty of electricity prices and effectively mitigate gradient issues, overfitting, and computational challenges associated with using a single model during forecasting, this paper proposes a framework for forecasting spot market electricity prices by integrating wavelet packet decomposition (WPD) with a hybrid deep neural network. By ensuring accurate data decomposition, the WPD algorithm aids in detecting fluctuating patterns and isolating random noise. The hybrid model integrates temporal convolutional networks (TCN) and long short-term memory (LSTM) networks to enhance feature extraction and improve forecasting performance. Compared to other techniques, it significantly reduces average errors, decreasing mean absolute error (MAE) by 27.3%, root mean square error (RMSE) by 66.9%, and mean absolute percentage error (MAPE) by 22.8%. This framework effectively captures the intricate fluctuations present in the time series, resulting in more accurate and reliable predictions.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 5","pages":"Pages 874-890"},"PeriodicalIF":2.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mechanical performance of key components in floating photovoltaic systems: technological advances and application prospects 浮式光伏系统关键部件力学性能：技术进展与应用前景

IF 2.6

Global Energy Interconnection Pub Date : 2025-10-01 Epub Date: 2025-07-14 DOI: 10.1016/j.gloei.2025.07.001

Kai Feng , Shuaiqi Li , Lin Fu , Yingjiu Zhao , Bin Zhang , Sombel Diaham , Chatchai Putson , Fouad Belhora , Abdelowahed Hajjaji , Yahia Boughaleb , Jiawei Zhang

{"title":"Mechanical performance of key components in floating photovoltaic systems: technological advances and application prospects","authors":"Kai Feng , Shuaiqi Li , Lin Fu , Yingjiu Zhao , Bin Zhang , Sombel Diaham , Chatchai Putson , Fouad Belhora , Abdelowahed Hajjaji , Yahia Boughaleb , Jiawei Zhang","doi":"10.1016/j.gloei.2025.07.001","DOIUrl":"10.1016/j.gloei.2025.07.001","url":null,"abstract":"<div><div>Floating photovoltaic (FPV) technology is emerging as a highly promising approach to accelerate decarbonization of the global economy, due to its higher power generation efficiency and lower land occupation. With the rapid development of FPV technology, the mechanical performance degradation of key components caused by the harsh marine environment has become a pressing issue, as it significantly contributes to failure behavior observed in FPV systems. A comprehensive compilation of the mechanical performance of key components in FPV systems is also currently unavailable. Here, the mechanical behavior of each structural component in FPV systems under harsh marine environments is systematically reviewed. It further emphasizes the synergistic effects of mechanical performance degradation among different components on the overall system. The drop-off rate (<em>v</em>) of normalized elongation at break (EAB) of polymer under the synergistic effect of various environmental factors increases from 7.5 × 10<sup>−4</sup> h<sup>−1</sup> to 21.8 × 10<sup>−4</sup> h<sup>−1</sup> compared with the single environmental stress. Moreover, the development of novel materials and innovative mechanical structures applied in FPV systems to enhance mechanical performance is discussed. The novel flexible PV modules applied in FPV systems minimize the loads acting on the mooring lines by 80% and increase power generation by 5%. Notably, this paper provides a theoretical foundation for developing standards of FPV systems, especially the establishment of standards related to the synergistic effects of the mechanical performance degradation of different key components on FPV systems.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 5","pages":"Pages 719-731"},"PeriodicalIF":2.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A review on high-frequency electromagnetic interference induced by power electronics in new electric power systems 新型电力系统中电力电子设备引起的高频电磁干扰研究进展

IF 2.6

Global Energy Interconnection Pub Date : 2025-10-01 Epub Date: 2025-09-22 DOI: 10.1016/j.gloei.2025.05.011

Yundong Hu , Xing Lei , Xizhou Du , Ting Ye , Hongning Song , Hao Li

{"title":"A review on high-frequency electromagnetic interference induced by power electronics in new electric power systems","authors":"Yundong Hu , Xing Lei , Xizhou Du , Ting Ye , Hongning Song , Hao Li","doi":"10.1016/j.gloei.2025.05.011","DOIUrl":"10.1016/j.gloei.2025.05.011","url":null,"abstract":"<div><div>New electric power systems characterized by a high proportion of renewable energy and power electronics equipment face significant challenges due to high-frequency (HF) electromagnetic interference from the high-speed switching of power converters. To address this situation, this paper offers an in-depth review of HF interference problems and challenges originating from power electronic devices. First, the root cause of HF electromagnetic interference, i.e., the resonant response of the parasitic parameters of the system to high-speed switching transients, is analyzed, and various scenarios of HF interference in power systems are highlighted. Next, the types of HF interference are summarized, with a focus on common-mode interference in grounding systems. This paper thoroughly reviews and compares various suppression methods for conducted HF interference. Finally, the challenges involved and suggestions for addressing emerging HF interference problems from the perspective of both power electronics equipment and power systems are discussed. This review aims to offer a structured understanding of HF interference problems and their suppression techniques for researchers and practitioners.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 5","pages":"Pages 804-820"},"PeriodicalIF":2.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian optimized support vector regression with a Gaussian kernel for accurate prediction of the state of health of lithium-ion batteries used for electric vehicle applications 基于高斯核的贝叶斯优化支持向量回归用于电动汽车锂离子电池健康状态的准确预测

IF 2.6

Global Energy Interconnection Pub Date : 2025-10-01 Epub Date: 2025-06-10 DOI: 10.1016/j.gloei.2025.02.003

Selvaraj Vedhanayaki , Vairavasundaram Indragandhi

{"title":"Bayesian optimized support vector regression with a Gaussian kernel for accurate prediction of the state of health of lithium-ion batteries used for electric vehicle applications","authors":"Selvaraj Vedhanayaki , Vairavasundaram Indragandhi","doi":"10.1016/j.gloei.2025.02.003","DOIUrl":"10.1016/j.gloei.2025.02.003","url":null,"abstract":"<div><div>The state of health SoH of lithium ion batteries plays a predominant role in ensuring the safe and reliable operation of electric vehicles. In this, a novel SoH estimation approach using support vector regression with a Gaussian kernel optimized using the Bayesian optimization technique (BO-SVR with a Gaussian kernel) was proposed. Unlike, traditional approaches that use the internal resistance, and battery capacity as input parameters, this study utilized the equivalent discharging voltage difference interval and equivalent charging voltage difference interval, as they capture the dynamic voltage characteristics associated with the battery degradation. The model was simulated using MATLAB 2023a. The mean absolute error, R<sup>2</sup>, root mean squared error, and mean squared error were considered as performance indicators. The simulation results indicated that the proposed BO-SVR with a Gaussian kernel model had superior performance to other kernel SVR and Gaussian Process Regression models, with a reduced RMSE of 0.0082, thus demonstrating its potential to predict the SoH more accurately.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 5","pages":"Pages 891-904"},"PeriodicalIF":2.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coordinated control strategy for multi-DG DC microgrid based on two-layer fuzzy neural network 基于双层模糊神经网络的多dg直流微电网协调控制策略

IF 2.6

Global Energy Interconnection Pub Date : 2025-10-01 Epub Date: 2025-09-03 DOI: 10.1016/j.gloei.2025.04.006

Hao Pan , Limin Jia

{"title":"Coordinated control strategy for multi-DG DC microgrid based on two-layer fuzzy neural network","authors":"Hao Pan , Limin Jia","doi":"10.1016/j.gloei.2025.04.006","DOIUrl":"10.1016/j.gloei.2025.04.006","url":null,"abstract":"<div><div>Conventional coordinated control strategies for DC bus voltage signal (DBS) in islanded DC microgrids (IDCMGs) struggle with coordinating multiple distributed generators (DGs) and cannot effectively incorporate state of charge (SOC) information of the energy storage system, thereby reducing the system flexibility. In this study, we propose an adaptive coordinated control strategy that employs a two-layer fuzzy neural network controller (FNNC) to adapt to varying operating conditions in an IDCMG with multiple PV and battery energy storage system (BESS) units. The first-layer FNNC generates optimal operating mode commands for each DG, thereby avoiding the requirement for complex operating modes based on SOC segmentation. An optimal switching sequence logic prioritizes the most appropriate units during mode transitions. The second-layer FNNC dynamically adjusts the droop power to overcome power distribution challenges among DG groups. This helps in preventing the PV power from exceeding the limits and mitigating the risk of BESS overcharging or over-discharging. The simulation results indicate that the proposed strategy enhances the coordinated operation of multi-DG IDCMGs, thereby ensuring the efficient and safe utilization of PV and BESS.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 5","pages":"Pages 732-746"},"PeriodicalIF":2.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0