International Transactions on Electrical Energy Systems最新文献

{"title":"Novel Path Planning Algorithm for the Mobile Robot in Power Transformer Substation","authors":"Chunxiang Mao,&nbsp;Jing Ma,&nbsp;Pengyang Qi,&nbsp;Dong Wang","doi":"10.1155/etep/7599732","DOIUrl":"https://doi.org/10.1155/etep/7599732","url":null,"abstract":"<div>\u0000 <p>In response to the issue of low search efficiency caused by the large number of expanded nodes when mobile robots use traditional <i>A</i>^∗ algorithm for path planning in complex environments, an improved <i>A</i>^∗ algorithm based on four-way search has been proposed. This algorithm leverages Euclidean distance to weight the heuristic function on the basis of the traditional <i>A</i>^∗ algorithm and reduces the number of expanded nodes and search time through the four-way search algorithm. Subsequently, experiments were conducted using maps to verify the performance of the improved algorithm. The experimental results indicate that the simulation of the improved <i>A</i>^∗ algorithm based on four-way search can achieve higher search efficiency, with fewer expanded nodes, which is more conducive to the path planning of mobile robots.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/7599732","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144148575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Microgrid Optimization With Electric Vehicle Mobile Energy Storage Considering Travel Characteristics","authors":"Xiaoyi Zhang,&nbsp;Jie Ma,&nbsp;Zheng Yang,&nbsp;Xiang Zhang,&nbsp;Yishuo Qiao,&nbsp;Yudong Du,&nbsp;Zhiwei Li","doi":"10.1155/etep/2656439","DOIUrl":"https://doi.org/10.1155/etep/2656439","url":null,"abstract":"<div>\u0000 <p>To address the economic challenges posed by the integration of a large number of electric vehicles (EVs) into microgrids, while leveraging their mobile energy storage (MES) capabilities and accounting for the impact of EV users’ travel patterns on charging and discharging behaviors, a microgrid scheduling model is proposed that incorporates the MES characteristics of EVs under user travel habits. Firstly, based on the spatial and temporal characteristics of the EV travel chain, the upper and lower bounds of the state of charge (SOC) that EVs must maintain at specific moments during their driving process are determined. Secondly, a mathematical model of a microgrid operation incorporating EV mobile storage batteries, wind power, photovoltaic systems, stationary batteries, and micro-gas turbines is developed. This model considers the costs of electricity purchase and sale, wind and solar curtailment, and natural gas consumption, with the objective of minimizing the total operating cost. To validate the effectiveness of the proposed approach, the optimal scheduling model is implemented and solved using YALMIP and GUROBI. Simulation results demonstrate that the proposed model significantly reduces the total operating cost of the microgrid compared to traditional methods. It also improves the profitability of EV users to a certain extent, promoting new energy consumption when new energy resources are abundant.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/2656439","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed Hierarchical Controller Resilience Analysis in Islanded Microgrid Under Cyber-Attacks","authors":"Abdollah Mirzabeigi,&nbsp;Ali Kalantarnia,&nbsp;Negin Zarei","doi":"10.1155/etep/9385286","DOIUrl":"https://doi.org/10.1155/etep/9385286","url":null,"abstract":"<div>\u0000 <p>In islanded microgrid configurations, synchronization of distributed generators (DGs) becomes imperative. Achieving synchronization and control necessitates the establishment of communication links. However, communication channels are susceptible to various challenges, with cyber-attacks emerging as a primary concern. This paper examines the vulnerability of cooperative hierarchical controllers in the face of diverse cyber-attacks, including DoS, sensor and actuator attacks, and hijacking attacks. DGs are considered a multiagent system for stabilization and global synchronization of the network. Cyber-attacks on the secondary controller have been formalized, and an appropriate controller is designed for system synchronization and stability. The appropriate Lyapunov function is introduced to prove the stability. Then, the simultaneous stabilization and global synchronization conditions have been investigated by proving suitable theorems. A comprehensive case study is executed via simulation in MATLAB/Simulink, incorporating cyber-attack scenarios. The effects of cyber-attacks on this controller are eliminated, and the DGs are synchronized. For comparison, the resilience indicator has been used. In this controller, the cyber-attacks of the sensor and hijacking attack are well controlled. A DoS cyber-attack is more effective than other attacks and causes some DGs to go off the network. Also, comparing this controller to other controllers shows its greater resilience.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/9385286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Data Driven Model for Voltage Stability Status Prediction and Instability Mitigation","authors":"F. Kh. Alabbas,&nbsp;M. Khalilifar,&nbsp;S. M. Shahrtash,&nbsp;D. A. Khaburi","doi":"10.1155/etep/6575682","DOIUrl":"https://doi.org/10.1155/etep/6575682","url":null,"abstract":"<div>\u0000 <p>An intelligent power system is either a system that is smartly designed from zero to 100, or a system that was not smartly designed but currently uses all its facilities to be smartly operated in different sectors. This paper presents a novel data-driven model for real time voltage instability diagnosis and instability mitigating. The method combines deep recurrent neural techniques to forecast future voltage stability and mathematical morphology (MM) tools to pinpoint the specific on-load tap changers (OLTCs) contributing to instability and issuing blocking commands to prevent their operation and consequently instability. The approach for voltage stability assessment is centralized, using real-time data, while the method for voltage instability mitigation is localized, focusing on real-time voltage magnitude related to the secondary side of the load transformer. The network was trained and tested on the Nordic32 test system. Results show that the method accurately predicted the stability status just one second after a disturbance, and successfully mitigated all voltage instability events related to load restoration by blocking only the OLTCs that were effective in causing instability. This selective approach provides a significant selectivity index and improves the system resiliency index.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/6575682","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143938965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hybrid PV/Fuel Cell–Fed Multiport DC-DC Converter for Water Irrigation Application","authors":"Sivaram N. V.,&nbsp;Lavanya A.,&nbsp;Jagabar Sathik Mohamed Ali,&nbsp;Divya Navamani J.","doi":"10.1155/etep/6942146","DOIUrl":"https://doi.org/10.1155/etep/6942146","url":null,"abstract":"<div>\u0000 <p>This paper introduces a novel hybrid multiport converter (MPC) for water irrigation systems. The proposed MPC is characterized by its simplicity and the ability to maintain a consistent DC-link voltage. A power management technique has been developed to ensure the maximum power utilization sources even if either one of the sources is absent and simultaneously manages power demanded by the load. This technique facilitates active power sharing, rapid output voltage control, and handling the load disturbances. The proposed converter’s performance is assessed through simulation tools and experimental validation for a 1-kW system, considering three different scenarios. Thus, the proposed converter achieves high gain, high efficiency of 96%, and faster dynamic response.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/6942146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy","authors":"Muhammad Aurangzeb,&nbsp;Yifei Wang,&nbsp;Sheeraz Iqbal,&nbsp;Md Shafiullah,&nbsp;Sultan Alghamdi,&nbsp;Zahid Ullah","doi":"10.1155/etep/1192925","DOIUrl":"https://doi.org/10.1155/etep/1192925","url":null,"abstract":"<div>\u0000 <p>In this study, we proposed a novel multiobjective optimization technique for electric vehicles’ (EVs) charging and vehicle-to-grid (V2G) scheduling. The ring seal search (RSS) algorithm ensures the optimum compatibility of the EV charging and discharging profiles revolving around multiple objectives, such as cost of charging, peak load demand reduction, and grid stability. The proposed algorithm is tested on the distribution model through the IEEE 33-bus system. A comprehensive model with real-time data from EV charging station operators (CSOs) is also ported in this research so that the EVs can be illustrated in the power distribution network. A convenient energy management strategy (EMS) called multiobjective optimization has been introduced to provide practical solutions for CSOs and EV users. The strategy had been developed based on multiple objectives to counter different trade-offs, including EV charging and discharging profiles suitable for numerous objectives encompassing charging costs, peak load demand reduction, and grid stability. The efficiency of the deterministic approach has been verified via extensive simulations and analysis, and the outcomes incorporate a definite enhancement in metrics since the RSS algorithm considerably optimized EV charging and V2G scheduling. The EV charging and discharging profiles had been optimized to take better advantage of available resource requirements by accommodating priority-based scheduling. The RSS will be able to investigate the modified parameter and the modified real system, which tells about the versatility and adaptability of the proposed method, i.e., it will be able to incorporate the changing implementation and its real-world efficacy, which is an immense merit for the adaptation of the real system. The proposed method offers a comprehensive, advanced EV charging and V2G scheduling solution. It addresses the limitations of previous methods by considering multiple objectives, utilizing a novel optimization algorithm, handling uncertainties, promoting renewable energy integration, and providing ancillary grid support. These enhancements make our method more effective, flexible, and capable of supporting the transition to a sustainable and efficient energy system.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/1192925","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiobjective Reactive Power Optimization Planning for Medium Voltage Distribution Networks Based on Improved Genetic Algorithm","authors":"Min Li,&nbsp;Juncheng Zhang,&nbsp;Jing Tan,&nbsp;Xiaohong Tan,&nbsp;Lingjie Tang","doi":"10.1155/etep/3199158","DOIUrl":"https://doi.org/10.1155/etep/3199158","url":null,"abstract":"<div>\u0000 <p>The medium voltage distribution network is a key bridge between the power sector and electricity users. In the process of increasing user demand for electricity, the medium voltage distribution network system has encountered problems such as insufficient reactive power, unreasonable distribution, and insufficient voltage at the end nodes of the line, which have affected the power supply quality and stability of the power system. Therefore, a multiobjective reactive power optimization planning method for medium voltage distribution networks based on an improved genetic algorithm is studied. Establish a mathematical model for medium voltage distribution network planning based on the multiobjective functions of active power loss, total voltage deviation of system nodes, and minimum total compensation amount of system compensation devices. The balance equation between active and reactive power of power nodes and power absorption losses is taken as the equality constraint, and the maximum and minimum constraints of variables such as voltage at the generator end and tap position of the on-load tap changer are taken as the constraints of the model. By combining the advantages of the standard genetic algorithm and simulated annealing algorithm, an improved genetic algorithm is formed to effectively solve the constructed mathematical model. After countless iterations, the effective solution of the model is obtained to achieve multiobjective reactive power optimization planning for medium voltage distribution networks. The experimental results show that this method can achieve multiobjective reactive power optimization in medium voltage distribution networks and improve the stability of the power system.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/3199158","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Warning of Low-Frequency Oscillations in Power System Using Rough Set and Cloud Model","authors":"Miao Yu,&nbsp;Jinyang Han,&nbsp;Shuoshuo Tian,&nbsp;Jianqun Sun,&nbsp;Honghao Wu,&nbsp;Jiaxin Yan","doi":"10.1155/etep/7250421","DOIUrl":"https://doi.org/10.1155/etep/7250421","url":null,"abstract":"<div>\u0000 <p>The stability of the power system is largely affected by low-frequency oscillations, so early warning research on low-frequency oscillations in power grids has become an urgent task. Traditional low-frequency oscillation early warning methods are still deficient in handling incomplete and highly discrete information. Compared with the existing methods, we have pioneered a synergistic mechanism of discrete attribute screening and continuous probabilistic feature fusion by combining the dynamic attribute approximation algorithm of rough sets with the cloud model, which effectively solves the loss of information caused by the discretization of continuous data in the traditional methods. Firstly, we analyze the principle of grid oscillation, use rough sets to process the raw data and indicators, remove redundant attributes, and get the set reflecting the relationship of different attributes. Then we construct a standard cloud based on grid operation data and a comprehensive cloud based on PMU data and obtain the oscillation warning evaluation. Finally, through the validation and simulation of 10 machine and 39 node systems in New England, as well as the comparison with other methods, the rationality and effectiveness of the proposed method are proved to be of theoretical and practical application value.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/7250421","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term Wind Power Prediction Based on MVMD-AVOA-CNN-LSTM-AM","authors":"Xiqing Zang,&nbsp;Zehua Wang,&nbsp;Shixu Zhang,&nbsp;Mingsong Bai","doi":"10.1155/etep/3570731","DOIUrl":"https://doi.org/10.1155/etep/3570731","url":null,"abstract":"<div>\u0000 <p>Due to the intermittent and fluctuating nature of wind power generation, it is difficult to achieve the desired prediction accuracy for wind power prediction. For this reason, this paper proposes a combined prediction model based on the Pearson correlation coefficient method, multivariate variational mode decomposition (MVMD), African vultures optimization algorithm (AVOA) for leader–follower patterns, convolutional neural network (CNN), long short-term memory (LSTM), and attention mechanism (AM). Firstly, the Pearson correlation coefficient method is used to filter out the meteorological data with a strong relationship with wind power to establish the wind power prediction dataset; subsequently, MVMD is used to decompose the original data into multiple subsequences in order to handle the meteorological data better. Thereafter, the African vultures algorithm is used to optimize the hyperparameters of the CNN-LSTM algorithm, and the AM is added to increase the prediction effect, and the decomposed subsequences are predicted separately, and the predicted values of each subsequence are superimposed to obtain the final prediction value. Finally, the effectiveness of the model is verified using data from a wind farm in Shenyang. The results show that the MAE of the established MVMD-AVA-CNN-LSTM-AM model is 2.0467, and the MSE is 2.8329. Compared with other models, the prediction accuracy is significantly improved, and it had better generalization ability and robustness, and better generalization and robustness.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/3570731","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Multiobjective Operation of Multicarrier Energy Hub Taking Energy Buffering Into Account","authors":"Mohammad-Mehdi Mohammadi-Zaferani,&nbsp;Reza Ebrahimi,&nbsp;Mahmood Ghanbari","doi":"10.1155/etep/9107639","DOIUrl":"https://doi.org/10.1155/etep/9107639","url":null,"abstract":"<div>\u0000 <p>This paper introduces a pioneering model for short-term planning of an energy hub (EH) that goes beyond traditional approaches by considering a comprehensive multicarrier energy system. The proposed model focuses on minimizing energy buffering costs while ensuring system operation and optimizing economic performance. The novelty of this study lies in its integrated approach, which simultaneously addresses operational efficiency, energy storage requirements, and overall system performance. The EH in this study is modeled as a prosumer within a day-ahead energy market, where both inflows and outflows of energy are optimized. The system’s capability to interact with upstream energy networks, including gas, heat, and electricity, is a critical aspect of the model. This interaction is managed through various technologies that enhance the hub’s ability to meet local demands efficiently. By employing an advanced improved particle swarm optimization (IPSO) algorithm, this model solves the complex multiobjective optimization problem inherent in EH management. The proposed model’s effectiveness is validated through extensive simulation on a test system, where its performance is compared with conventional heuristic optimization algorithms. The results demonstrate the superior efficiency and applicability of the IPSO algorithm, confirming that the proposed model offers a significant advancement in the field of sustainable energy management.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/9107639","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143849143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}