Jie Zhao, Chenhao Wang, Biao Zhao, Xiao Du, Huaixun Zhang, Lei Shang
{"title":"Neural network-based integrated reactive power optimization study for power grids containing large-scale wind power","authors":"Jie Zhao, Chenhao Wang, Biao Zhao, Xiao Du, Huaixun Zhang, Lei Shang","doi":"10.1049/gtd2.13176","DOIUrl":null,"url":null,"abstract":"<p>The high uncertainty of wind power output greatly affects the rapid reactive power optimization of power systems. This paper proposes a neural network-based comprehensive reactive power optimization method for large-scale wind power grids, effectively addressing the challenges of rapid reactive power optimization in power systems. Firstly, by constructing typical wind-power-load scenarios, the generalization ability of the neural network is improved. Then, focusing on the comprehensive reactive power optimization problem after integrating typical wind-power-load scenarios into the system, the improved Harris hawks optimization algorithm (HHO) is compared with the particle swarm optimization algorithm and traditional HHO algorithm, highlighting its advantages. Finally, HHO is utilized for solving, thereby constructing a comprehensive reactive power optimization strategy tag set. Furthermore, through deep fitting of the neural network between the power grid operating state and the comprehensive reactive power optimization strategy, the computational complexity and decision-making time of reactive power optimization are reduced.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13176","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iet Generation Transmission & Distribution","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/gtd2.13176","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
The high uncertainty of wind power output greatly affects the rapid reactive power optimization of power systems. This paper proposes a neural network-based comprehensive reactive power optimization method for large-scale wind power grids, effectively addressing the challenges of rapid reactive power optimization in power systems. Firstly, by constructing typical wind-power-load scenarios, the generalization ability of the neural network is improved. Then, focusing on the comprehensive reactive power optimization problem after integrating typical wind-power-load scenarios into the system, the improved Harris hawks optimization algorithm (HHO) is compared with the particle swarm optimization algorithm and traditional HHO algorithm, highlighting its advantages. Finally, HHO is utilized for solving, thereby constructing a comprehensive reactive power optimization strategy tag set. Furthermore, through deep fitting of the neural network between the power grid operating state and the comprehensive reactive power optimization strategy, the computational complexity and decision-making time of reactive power optimization are reduced.
期刊介绍:
IET Generation, Transmission & Distribution is intended as a forum for the publication and discussion of current practice and future developments in electric power generation, transmission and distribution. Practical papers in which examples of good present practice can be described and disseminated are particularly sought. Papers of high technical merit relying on mathematical arguments and computation will be considered, but authors are asked to relegate, as far as possible, the details of analysis to an appendix.
The scope of IET Generation, Transmission & Distribution includes the following:
Design of transmission and distribution systems
Operation and control of power generation
Power system management, planning and economics
Power system operation, protection and control
Power system measurement and modelling
Computer applications and computational intelligence in power flexible AC or DC transmission systems
Special Issues. Current Call for papers:
Next Generation of Synchrophasor-based Power System Monitoring, Operation and Control - https://digital-library.theiet.org/files/IET_GTD_CFP_NGSPSMOC.pdf