{"title":"Optimal parameter tuning for voltage control thresholds in distribution networks using MOPSO and Pareto fronts","authors":"Nien-Che Yang, Chen-Hong Su, Hao Yang","doi":"10.1016/j.epsr.2025.111552","DOIUrl":null,"url":null,"abstract":"<div><div>This study presents a method based on a multi-objective optimisation algorithm to improve the voltage control strategy for distributed generation, taking into account daily variations in actual loads. The proposed approach involves adjusting the voltage control thresholds of the on-load tap changer, switched capacitor, and voltage–reactive power control of smart inverters. A multi-objective particle swarm optimisation algorithm, utilizing Pareto fronts, is employed to optimise key objectives, including voltage deviation, system power losses, and the frequency of changes in the on-load tap changer and switched capacitor. By minimising these objectives, an optimal set of control set-points is determined. To validate the effectiveness of the proposed methodology, multiple operating scenarios with varying daily load patterns are simulated using the IEEE 33-bus test system. The simulation results demonstrate that the proposed approach successfully optimises voltage control, enhancing both voltage stability and distribution system reliability.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"244 ","pages":"Article 111552"},"PeriodicalIF":3.3000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electric Power Systems Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378779625001440","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This study presents a method based on a multi-objective optimisation algorithm to improve the voltage control strategy for distributed generation, taking into account daily variations in actual loads. The proposed approach involves adjusting the voltage control thresholds of the on-load tap changer, switched capacitor, and voltage–reactive power control of smart inverters. A multi-objective particle swarm optimisation algorithm, utilizing Pareto fronts, is employed to optimise key objectives, including voltage deviation, system power losses, and the frequency of changes in the on-load tap changer and switched capacitor. By minimising these objectives, an optimal set of control set-points is determined. To validate the effectiveness of the proposed methodology, multiple operating scenarios with varying daily load patterns are simulated using the IEEE 33-bus test system. The simulation results demonstrate that the proposed approach successfully optimises voltage control, enhancing both voltage stability and distribution system reliability.
期刊介绍:
Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview.
• Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation.
• Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design.
• Substation work: equipment design, protection and control systems.
• Distribution techniques, equipment development, and smart grids.
• The utilization area from energy efficiency to distributed load levelling techniques.
• Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.