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河北工业大学
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基于小世界CSO算法的含风电的配电网重构.

Title: 基于小世界CSO算法的含风电的配电网重构.
Alternate Title: Distribution network reconfiguration with wind power generations based on small - world and CSO algorithm.
Language: Chinese
Authors: 殷豪1
李德强1
孟安波1
魏明磊1
洪俊杰1
Source: Heilongjiang Electric Power Journal. oct2016, Vol. 38 Issue 5, p399-404. 6p.
Document Type: Article
Author-Supplied Keywords: distribution network reconfiguration model ; robustness ; scenario analysis method ; small - world GSO algorithm ; wind power generations (WPG) ; 场景分析法 ; 小世界CS0算法 ; 配电网重构模型 ; 风电(WPG) ; 鲁棒性 ; Language of Keywords: English; Chinese
Abstract (English): Due to the randomness of wind power generations (WPGs) output, it is difficult to establish the model of distribution network reconfiguration. The author proposed to establish the model according to scenario analysis method and several states of wind speed, analyzed the situation of the distribution network with single WPG and multiple WPGs in the single scenario and mixed scenarios partitioned, and calculated the probability of each scenario to get the objective function value. In this paper, a novel reconfiguration algorithm based on the network idea of small world and the duo - crossover mechanism of GSO was applied in the process of the configuration of the distribution network with WPGs. By this method, the neighbor, generated in the dynamic link of each particle and its nearby particles with better fitness, was updated so as to enhance the swarm diversity and the global search ability. The simulation results show that this method enjoys better robustness and search ability. [ABSTRACT FROM AUTHOR]
Abstract (Chinese): 针对风电(WPG)出力的随机性导致配电网重构模型难以建立问题,笔者提出根据场景分析法与风速的几种状态构造 适应于含风电的配电网重构模型,然后划分单一场景和组合场景,分析单个风电和多个风电接人配电网情况,计算每种场景 出现的概率得出目标函数值。同时,将基于小世界网络思想和CS0算法双交叉机制的重构新算法应用于含风电的配电网重 构过程中,让每个粒子与其周围优秀的粒子动态连接而产生邻域,不断更新邻域,以增强种群的多样性和全局收敛能力。仿 真分析结果表明,该算法具有较强的鲁棒性和较好的搜索能力。 [ABSTRACT FROM AUTHOR]
(Copyright applies to all Abstracts.)
Author Affiliations: 1广东工业大学自动化学院,广州510006
ISSN: 2095-6843 (Sherpa/RoMEO, JCR)
PageCount: 399-405
volume: 38
issue: 5
issn: 20956843
pubdate: 2016
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