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基于改进萤火虫算法的含多种新能源地区电网的无功电压优化

Reactive power and voltage optimization based on improved firefly algorithm in regional power grids with a variety of new energies
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摘要 为了解决风电和光伏等新能源场站大规模并网时带来的电压波动及越限问题,以及传统无功电压优化求解算法易陷入局部最优问题,提出了基于改进萤火虫算法(IFA)的含多种新能源的地区电网无功电压优化模型。该模型以标准化的有功网损、节点电压偏差和火电机组无功出力偏差之和最小为优化目标,以潮流计算、火电机组端电压和无功出力、变压器变比、新能源场站有功出力和静止无功补偿器出力等作为需满足的约束条件,采用IFA对优化模型进行求解,通过引入自适应步长和位置更新优化公式提高模型的计算精度和全局寻优能力。改进IEEE-30节点系统仿真分析表明:所提出的优化模型可降低系统有功网损,改善了地区电网无功分布,同时抵制了系统电压波动,提高了地区电网电能质量;IFA能有效提高计算精度和速度,提升全局寻优能力。 In order to solve voltage fluctuation and off-limit problems caused by the large-scale grid connection of new energy stations such as wind power and photovoltaic,as well as the problem of traditional reactive power and voltage calculation methods easily falling into local optima,a new optimization model based on improved firefly algorithm(IFA) for the regional power grid is proposed.In this model,the sum of standardized active power losses,node voltage deviations,and reactive output deviations is used as the optimization objective.Meanwhile,regional power flow calculation,terminal voltage and reactive capacity of thermal power units,transformer ratios,active power of new energy stations and reactive power of static var compensators are used as constraints that needs to be met.Then,by using an IFA to solve the optimization model,the algorithm's computational accuracy and global optimization ability are increased by introducing new step size and position update formulas.Finally,the effectiveness of the presented model is validated using an IEEE-30 bus system.The results indicate that the proposed optimization model can reduce the active power loss of the system,improve the reactive power distribution of the regional power grid,resist the voltage fluctuation of the system,and improve the power quality of the regional power grid.IFA can effectively improve the calculation accuracy and speed,and improve the global optimization ability.
作者 于佰建 陈卓尔 宋长城 李慧 王艳波 YU Baijian;CHEN Zhuoer;SONG Changcheng;LI Hui;WANG Yanbo(State Grid Shandong Electric Power Company,Jinan 250021,China;School of Automation,Beijing Information Science&Technology University,Beijing 100192,China;Technical and Economic Consulting Centre of Electric Power Construction,CEC,Beijing 100053,China)
出处 《河海大学学报(自然科学版)》 CAS CSCD 北大核心 2024年第5期93-100,共8页 Journal of Hohai University(Natural Sciences)
基金 北京市自然科学基金项目(3232045)。
关键词 新能源场站 无功电压优化 萤火虫算法 new energy stations reactive power and voltage optimization firefly algorithm
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