基于免疫算法的电力系统最优潮流计算  

Calculation of Electric Power Optimal Flow Based on Artificial Immune Algorithm

作　　者：杨建宁[1] 孙玉坤[1] 李自成[1] 矛青锋[1] 孙运全[1] 

机构地区：[1]江苏大学电气信息学院,江苏镇江212013

出　　处：《中国农村水利水电》2007年第5期104-107,110,共5页China Rural Water and Hydropower

基　　金：江苏省高新技术资助项目(GB2004024);江苏省教育厅博士基金创新技术项目(1223000017)

摘　　要：根据人和其他高等动物免疫系统的机理,研究一种计算具有非线性多峰值的非凸规划性质的电力系统最优潮流的新算法人工免疫算法。该算法结合电力系统最优潮流的数学模型,将目标函数和不等式约束条件作为抗原,将潮流搜索空间的解作为抗体,依据抗原与抗体的结合力以及抗体之间的结合力对表示潮流解的抗体进行评价和选择,通过记忆细胞对抗体的抑制作用有效地摆脱潮流解局部最优点,通过抗体之间的相互激励作用提高了最优点附近的搜索效率。提出可以运用于工程上的模型和基本算法步骤,以及求解的实现过程,通过对IEEE30节点系统运用人工免疫算法、遗传算法和原对偶内点法三种方法计算结果对比,说明了人工免疫算法收敛速度快和全局搜索能力好的有效性。A novel algorithm -- artificial immune algorithm, inspired by the mechanism of immune system of human and other mammals, was studied for electrical optimal power flow （OPF） with the character of non-protruding program in non-linearity and multiple peaks. The algorithm improved the search speed of the optimal power flow through integrating the math model of electrical optimal power flow, using the objective function and inequality constrains as antigen and the solution in the search space of power flow as antibody. The antibody of power flow answer was estimated and chosen according to the combining force between antigen and antibody, and the local optimal solution could be avoided by the restrain effect between memory cells and antibodies. The interaction between antibodies speeded up the convergence of solution near optimal point, Engineering model and basic algorithm process on OPF problem and realization process were described in the paper. Comparison of results of the artificial immune algorithm, genetic algorithm and primal-dual interior point method was conducted in IEEE30 bus system, the feasibility of the algorithm in convergence velocity and search ability globally was demonstrated.

关 键 词：人工免疫算法 最优潮流 IEEE-30系统 遗传算法 原对偶内点法 

分 类 号：TM744[电气工程—电力系统及自动化]