Global Energy Interconnection最新文献

{"title":"A coordinated operation method of wind-PV-hydrogen- storage multi-agent energy system","authors":"Tengfei Ma ,&nbsp;Wei Pei ,&nbsp;Yanhong Yang ,&nbsp;Hao Xiao ,&nbsp;Chenghong Tang ,&nbsp;Weiqi Hua","doi":"10.1016/j.gloei.2024.08.001","DOIUrl":"10.1016/j.gloei.2024.08.001","url":null,"abstract":"<div><p>Wind-photovoltaic (PV)-hydrogen-storage multi-agent energy systems are expected to play an important role in promoting renewable power utilization and decarbonization. In this study, a coordinated operation method was proposed for a wind-PV- hydrogen-storage multi-agent energy system. First, a coordinated operation model was formulated for each agent considering peer-to-peer power trading. Second, a coordinated operation interactive framework for a multi-agent energy system was proposed based on the theory of the alternating direction method of multipliers. Third, a distributed interactive algorithm was proposed to protect the privacy of each agent and solve coordinated operation strategies. Finally, the effectiveness of the proposed coordinated operation method was tested on multi-agent energy systems with different structures, and the operational revenues of the wind power, PV, hydrogen, and energy storage agents of the proposed coordinated operation model were improved by approximately 59.19%, 233.28%, 16.75%, and 145.56%, respectively, compared with the independent operation model.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 4","pages":"Pages 446-461"},"PeriodicalIF":1.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000616/pdf?md5=be0b794cfe0219254fefd67e4d340f6c&pid=1-s2.0-S2096511724000616-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generation of input spectrum for electrolysis stack degradation test applied to wind power PEM hydrogen production","authors":"Yanhui Xu ,&nbsp;Guanlin Li ,&nbsp;Yuyuan Gui ,&nbsp;Zhengmao Li","doi":"10.1016/j.gloei.2024.08.006","DOIUrl":"10.1016/j.gloei.2024.08.006","url":null,"abstract":"<div><p>Hydrogen production by proton exchange membrane electrolysis has good fluctuation adaptability, making it suitable for hydrogen production by electrolysis in fluctuating power sources such as wind power. However, current research on the durability of proton exchange membrane electrolyzers is insufficient. Studying the typical operating conditions of wind power electrolysis for hydrogen production can provide boundary conditions for performance and degradation tests of electrolysis stacks. In this study, the operating condition spectrum of an electrolysis stack degradation test cycle was proposed. Based on the rate of change of the wind farm output power and the time-averaged peak-valley difference, a fluctuation output power sample set was formed. The characteristic quantities that played an important role in the degradation of the electrolysis stack were selected. Dimensionality reduction of the operating data was performed using principal component analysis. Clustering analysis of the data segments was completed using an improved Gaussian mixture clustering algorithm. Taking the annual output power data of wind farms in Northwest China with a sampling rate of 1 min as an example, the cyclic operating condition spectrum of the proton-exchange membrane electrolysis stack degradation test was constructed. After preliminary simulation analysis, the typical operating condition proposed in this paper effectively reflects the impact of the original curve on the performance degradation of the electrolysis stack. This study provides a method for evaluating the degradation characteristics and system efficiency of an electrolysis stack due to fluctuations in renewable energy.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 4","pages":"Pages 462-474"},"PeriodicalIF":1.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000665/pdf?md5=51b59c89b74af8f5169221718325b4db&pid=1-s2.0-S2096511724000665-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel cascaded H-bridge photovoltaic inverter with flexible arc suppression function","authors":"Junyi Tang,&nbsp;Wei Gao","doi":"10.1016/j.gloei.2024.08.002","DOIUrl":"10.1016/j.gloei.2024.08.002","url":null,"abstract":"<div><p>This paper presents a novel approach that simultaneously enables photovoltaic (PV) inversion and flexible arc suppression during single-phase grounding faults. Inverters compensate for ground currents through an arc-elimination function, while outputting a PV direct current (DC) power supply. This method effectively reduces the residual grounding current. To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models, an adaptive fuzzy neural network imitating a sliding mode controller was designed. An online adaptive adjustment law for network parameters was developed, based on the Lyapunov stability theorem, to improve the robustness of the inverter to fault and connection locations. Furthermore, a new arc-suppression control exit strategy is proposed to allow a zero- sequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time. Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults. Compared to other methods, the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 4","pages":"Pages 513-527"},"PeriodicalIF":1.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000628/pdf?md5=016f43233e70698519f8ef08713a0188&pid=1-s2.0-S2096511724000628-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Consideration of the influence of supports in modeling the electromagnetic fields of 25 kV traction networks under emergency conditions","authors":"Konstantin Suslov ,&nbsp;Andrey Kryukov ,&nbsp;Ekaterina Voronina ,&nbsp;Pavel Ilyushin","doi":"10.1016/j.gloei.2024.08.004","DOIUrl":"10.1016/j.gloei.2024.08.004","url":null,"abstract":"<div><p>Single-phase 25 kV traction networks of electrified alternating current (AC) railways create electromagnetic fields (EMFs) with significant levels of intensity. The most intense magnetic fields occur when short circuits exist between the contact wire and rails or ground. Despite the short duration of exposure, they can adversely affect electronic devices and induce significant voltages in adjacent power lines, which is dangerous for operating personnel. Although numerous investigations have focused on modeling the EMF of traction networks and power lines, the challenge of determining the three-dimensional electromagnetic fields near metal supports during the flow of a short-circuit current through them is yet to be resolved. In this case, the field has a complex spatial structure that significantly complicates the calculations of intensities. This study proposes a methodology, algorithms, software, and digital models for determining the EMF in the described emergency scenarios. During the modeling process, the objects being studied were represented by segments of thin wires to analyze the distribution of the electric charge and calculate the intensities of the electric and magnetic fields. This approach was implemented in the Fazonord software, and the modeling results show a substantial increase in EMF levels close to the support, with a noticeable decrease in the levels as the distance from it increases. The procedure implemented in the commercial software Fazonord is universal and can be used to determine electromagnetic fields at any electrical power facility that includes live parts of limited length. Based on the proposed procedure, the EMF near the supports of overhead power lines and traction networks of various designs could be determined, the EMF levels at substations can be calculated, and the influence of metal structures located near traction networks, such as pedestrian crossings at railway stations, can be considered.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 4","pages":"Pages 528-540"},"PeriodicalIF":1.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000641/pdf?md5=aec14698b5c2c5d56839d91da7ef39b9&pid=1-s2.0-S2096511724000641-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling load distribution for rural photovoltaic grid areas using image recognition","authors":"Ning Zhou,&nbsp;Bowen Shang,&nbsp;Jinshuai Zhang,&nbsp;Mingming Xu","doi":"10.1016/j.gloei.2024.06.002","DOIUrl":"https://doi.org/10.1016/j.gloei.2024.06.002","url":null,"abstract":"<div><p>Expanding photovoltaic (PV) resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape, aligning with the “carbon peaking and carbon neutrality” objectives. However, rural power grids often lack digitalization; thus, the load distribution within these areas is not fully known. This hinders the calculation of the available PV capacity and deduction of node voltages. This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas. First, houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model. The distribution of the houses is then used to estimate the load distribution in the grid area. Next, equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines. Finally, by calculating the connectivity matrix of the nodes, a minimum spanning tree is extracted, the topology of the network is constructed, and the node parameters of the load-distribution model are calculated. The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas. The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters, thereby offering vital support for determining PV access capability.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 3","pages":"Pages 270-283"},"PeriodicalIF":1.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000410/pdf?md5=1e9a34705fc1550ee22ec7209638ba18&pid=1-s2.0-S2096511724000410-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics","authors":"Siwei Li ,&nbsp;Liang Yue ,&nbsp;Xiangyu Kong ,&nbsp;Chengshan Wang","doi":"10.1016/j.gloei.2024.06.004","DOIUrl":"https://doi.org/10.1016/j.gloei.2024.06.004","url":null,"abstract":"<div><p>This article introduces the concept of load aggregation, which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems. The online identification method is a computer-involved approach for data collection, processing, and system identification, commonly used for adaptive control and prediction. This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration, aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods. The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics, economic efficiency, and comfort. The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes, the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57, indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term. Overall, the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 3","pages":"Pages 313-323"},"PeriodicalIF":1.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000434/pdf?md5=f879b90415d9ddcb452fdaa01f1894f9&pid=1-s2.0-S2096511724000434-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A method for cleaning wind power anomaly data by combining image processing with community detection algorithms","authors":"Qiaoling Yang,&nbsp;Kai Chen,&nbsp;Jianzhang Man,&nbsp;Jiaheng Duan,&nbsp;Zuoqi Jin","doi":"10.1016/j.gloei.2024.06.001","DOIUrl":"https://doi.org/10.1016/j.gloei.2024.06.001","url":null,"abstract":"<div><p>Current methodologies for cleaning wind power anomaly data exhibit limited capabilities in identifying abnormal data within extensive datasets and struggle to accommodate the considerable variability and intricacy of wind farm data. Consequently, a method for cleaning wind power anomaly data by combining image processing with community detection algorithms (CWPAD-IPCDA) is proposed. To precisely identify and initially clean anomalous data, wind power curve (WPC) images are converted into graph structures, which employ the Louvain community recognition algorithm and graph- theoretic methods for community detection and segmentation. Furthermore, the mathematical morphology operation (MMO) determines the main part of the initially cleaned wind power curve images and maps them back to the normal wind power points to complete the final cleaning. The CWPAD-IPCDA method was applied to clean datasets from 25 wind turbines (WTs) in two wind farms in northwest China to validate its feasibility. A comparison was conducted using density-based spatial clustering of applications with noise (DBSCAN) algorithm, an improved isolation forest algorithm, and an image-based (IB) algorithm. The experimental results demonstrate that the CWPAD-IPCDA method surpasses the other three algorithms, achieving an approximately 7.23% higher average data cleaning rate. The mean value of the sum of the squared errors (SSE) of the dataset after cleaning is approximately 6.887 lower than that of the other algorithms. Moreover, the mean of overall accuracy, as measured by the F1-score, exceeds that of the other methods by approximately 10.49%; this indicates that the CWPAD-IPCDA method is more conducive to improving the accuracy and reliability of wind power curve modeling and wind farm power forecasting.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 3","pages":"Pages 293-312"},"PeriodicalIF":1.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000409/pdf?md5=76bef55c59575e27e863e1a13c83d015&pid=1-s2.0-S2096511724000409-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster","authors":"Song Gao ,&nbsp;Wei Wang ,&nbsp;Jingyi Chen ,&nbsp;Xinyu Wu ,&nbsp;Junyan Shao","doi":"10.1016/j.gloei.2024.06.005","DOIUrl":"https://doi.org/10.1016/j.gloei.2024.06.005","url":null,"abstract":"<div><p>Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events, causing surveillance and energy loss. This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters. Initially, the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes. Subsequently, it delves into communication and data processing mechanisms, specifically focusing on central data processing (CDP), communication routers (CRs), and phasor measurement units (PMUs), to re-establish an equipment recovery model based on these data transmission methodologies. Furthermore, it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution. The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system. The findings suggest that the proposed branch- and-bound algorithm significantly augments the observational capabilities of a power system with limited resources, thereby bolstering its stability and emergency response mechanisms.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 3","pages":"Pages 336-346"},"PeriodicalIF":1.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000446/pdf?md5=d63f241ebeeb7dd6a4ba0a18a66b48c3&pid=1-s2.0-S2096511724000446-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing wind farm layout for enhanced electricity extraction using a new hybrid PSO-ANN method","authors":"Mariam El Jaadi ,&nbsp;Touria Haidi ,&nbsp;Abdelaziz Belfqih ,&nbsp;Mounia Farah ,&nbsp;Atar Dialmy","doi":"10.1016/j.gloei.2024.06.006","DOIUrl":"https://doi.org/10.1016/j.gloei.2024.06.006","url":null,"abstract":"<div><p>With the growing need for renewable energy, wind farms are playing an important role in generating clean power from wind resources. The best wind turbine architecture in a wind farm has a major influence on the energy extraction efficiency. This paper describes a unique strategy for optimizing wind turbine locations on a wind farm that combines the capabilities of particle swarm optimization (PSO) and artificial neural networks (ANNs). The PSO method was used to explore the solution space and develop preliminary turbine layouts, and the ANN model was used to fine- tune the placements based on the predicted energy generation. The proposed hybrid technique seeks to increase energy output while considering site-specific wind patterns and topographical limits. The efficacy and superiority of the hybrid PSO-ANN methodology are proved through comprehensive simulations and comparisons with existing approaches, giving exciting prospects for developing more efficient and sustainable wind farms. The integration of ANNs and PSO in our methodology is of paramount importance because it leverages the complementary strengths of both techniques. Furthermore, this novel methodology harnesses historical data through ANNs to identify optimal turbine positions that align with the wind speed and direction and enhance energy extraction efficiency. A notable increase in power generation is observed across various scenarios. The percentage increase in the power generation ranged from approximately 7.7% to 11.1%. Owing to its versatility and adaptability to site-specific conditions, the hybrid model offers promising prospects for advancing the field of wind farm layout optimization and contributing to a greener and more sustainable energy future.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 3","pages":"Pages 254-269"},"PeriodicalIF":1.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000458/pdf?md5=003c2e7dab35208a53690af4e89f1a1c&pid=1-s2.0-S2096511724000458-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Primary frequency control considering communication delay for grid-connected offshore wind power systems","authors":"Xueping Pan ,&nbsp;Qijie Xu ,&nbsp;Tao Xu ,&nbsp;Jinpeng Guo ,&nbsp;Xiaorong Sun ,&nbsp;Yuquan Chen ,&nbsp;Qiang Li ,&nbsp;Wei Liang","doi":"10.1016/j.gloei.2024.06.008","DOIUrl":"https://doi.org/10.1016/j.gloei.2024.06.008","url":null,"abstract":"<div><p>Offshore wind farms are becoming increasingly distant from onshore centralized control centers, and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control. This causes a deterioration in the performance of the primary frequency control and, in some cases, may even result in frequency instability within the power system. Therefore, a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power. The Padé approximation was used to model the time delays, and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays. The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored. In addition, a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics. Finally, a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform. The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 3","pages":"Pages 241-253"},"PeriodicalIF":1.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096511724000471/pdf?md5=ec0664517588acdeb30e1ceddebb072c&pid=1-s2.0-S2096511724000471-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}