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采用改进遗传算法的无功优化规划
引用本文:李渊博,蒋铁铮. 采用改进遗传算法的无功优化规划[J]. 电力科学与工程, 2014, 30(9): 39-45
作者姓名:李渊博  蒋铁铮
作者单位:长沙理工大学电气与信息工程学院,湖南长沙,410114
摘    要:提出了以有功网损和无功补偿设备投资最小的无功规划数学模型,以无功裕度法确定无功补偿点,采用逐年规划方式和利用改进遗传算法对模型进行求解。在最小负荷方式和最大负荷方式下无功规划的基础上建立了场景检验模型,以IEEE30节点系统为算例,将逐年优化方式与整体优化方式的规划结果进行对比,验证了所提模型和求解方法的有效性。

关 键 词:无功规划  补偿点  逐年规划  遗传算法  场景检验

Optimization of Reactive Power Planning Using Improved Genetic Algorithm
Li Yuanbo,Jiang Tiezheng. Optimization of Reactive Power Planning Using Improved Genetic Algorithm[J]. Power Science and Engineering, 2014, 30(9): 39-45
Authors:Li Yuanbo  Jiang Tiezheng
Affiliation:( School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China)
Abstract:Reactive power compensation nodes were confirmed according to reactive power margin and a reactivepower planning mathematical model was proposed with minimum yearly active power loss fee and minimum invest-ment in new addition of VAR equipment being both taken as objective function. The model was resolved by usingannually planning and improved genetic algorithm method. A kind of scenario based checking model was built un-der minimum and maximum load operation condition. Taking IEEE30 bus test system as an example, the resultcomparison between annually planning method and entire optimization method is carried out, which show the feasi-bility and validity of the proposed model.
Keywords:reactive power planning  compensation point  annually planning  improved genetic algorithm  scenarioinspection
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