基于潜力度的分布式电源优化配置

殷杰; 向铁元; 杨瑶

殷杰,向铁元,杨瑶.基于潜力度的分布式电源优化配置[J].电测与仪表,2016,53(11):.
Yin Jie,Xiang Tieyuan,Yang Yao.Optimal Placement of Distributed Generation Based on Potentiality[J].Electrical Measurement & Instrumentation,2016,53(11):.

基于潜力度的分布式电源优化配置

Optimal Placement of Distributed Generation Based on Potentiality

DOI：

中文关键词: 分布式电源灵敏度分析潜力度自适应灾变遗传算法

英文关键词:distributed generation sensitivity analysis potentiality self-adaptive catastrophic genetic algorithms

基金项目:国家科技支撑计划项(2013BAA02B00)

作者中文名	作者英文名	单位
殷杰	Yin Jie	武汉大学电气工程学院
向铁元	Xiang Tieyuan	武汉大学电气工程学院
杨瑶	Yang Yao	武汉大学电气工程学院

摘要点击次数: 1791

中文摘要:

利用传统的灵敏度分析进行分布式电源(DG)优化配置,易造成选点布局不合理及选点失准问题。首先在二阶灵敏度模型的基础上,得到目标函数与DG接入容量的非线性关系。然后提出了一种全新的DG选点方式,用潜力度指标替代传统的一阶灵敏度来指导接入位置的选取。最后采用自适应灾变遗传算法对IEEE15节点系统进行优化计算,比较了各配置方案的优化结果。算例分析表明本文的选点方式能更有效地改善网损、电压综合指标。

英文摘要:

Optimal placement of DG based on traditional sensitivity analysis may lead to improper location layout and inaccurate location selection. Through setting up a second-order model, the nonlinear relationship between objective function and sizing of DG is presented. Instead of traditional first-order sensitivity, a new potentiality index is used to guide DG location selection. Through applying self-adaptive catastrophic genetic algorithms into the IEEE15-bus system as an example, the optimization results of all configurations are compared. The results demonstrate the effectiveness of the proposed method on improving power loss and voltage quality.

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