基于改进细菌群体趋药性算法的电力系统无功优化  

Reactive Power Management Based on Improved Bacterial Colony Chemotaxis Algorithm

作　　者：张晓辉[1] 卢志刚[1] 秦四娟 

机构地区：[1]电力电子节能与传动控制河北省重点实验室(燕山大学),河北省秦皇岛市066004 [2]秦皇岛电力公司,河北省秦皇岛市066000

出　　处：《电网技术》2012年第2期109-114,共6页Power System Technology

基　　金：国家自然科学基金项目(61071201);河北省自然科学基金项目(F2010001319);河北省教育厅基金项目(20094831)~~

摘　　要：建立了无惩罚因子策略的数学模型,并应用改进细菌群体优化(bacterial colony chemotaxis,BCC)算法进行无功优化。该模型利用可行细菌的占比指导细菌向可行空间搜索或最小网损空间搜索,快速搜索到可行的最优值。在基本BCC算法中引入速度、感知范围的动态调整以及高斯变异机制以提高寻优精度;同时引入映射因子以改善BCC算法解决离散域问题的性能。算例结果表明,改进BCC算法具有较好寻优性能,结合无惩罚因子策略的数学模型能快速得出合理的无功优化策略。A no-penalty factor strategy model is proposed and reactive power optimization is performed by use of bacterial colony chemotaxis （BCC） algorithm. In the proposed model the possible bacterial proportion is used to guide the bacteria onto the search of possible space or the smallest network loss space. The dynamic adjustment of speed and perception range as well as Gaussian mutation mechanism are led into basic BCC algorithm to improve optimizing accuracy; the mapping factors are led in to improve the performance of BCC algorithm to solve the problem of discrete domain. Case calculation results show that the improved BCC algorithm possesses a better optimizing performance, and combining with the mathematical model of no-penalty strategy a rational reactive power optimization strategy can be obtained rapidly.

关 键 词：无功优化 改进BCC算法 无惩罚因子策略 动态调整 变异 映射因子 

分 类 号：TM72[电气工程—电力系统及自动化]