基于免疫禁忌混合算法的多目标最优潮流计算

针对电力系统多目标最优潮流计算问题,提出了一种基于免疫禁忌混合算法的多目标模糊优化潮流计算的新方法。该方法运用模糊集理论来构造评价函数,实现了多目标优化问题向单目标优化问题的转化,兼顾了各子目标,保证了较高的整体优化水平;采用求解精度高、使用灵活的免疫禁忌混合算法来进行单目标寻优,准确地获取了符合实际的全局最优解。通过对IEEE 30节点系统进行多次多目标最优潮流仿真计算,并将计算结果分别与单目标最优潮流计算及采用粒子群算法、免疫算法等其它算法的结果进行比较和分析,验证了该方法是解决电力系统多目标最优潮流问题的一种有效方法。

Multi-objective Optimal Power Flow Calculation Based on Immune/Tabu Search Hybrid Algorithm

Aiming at multi-objective optimal power flow calculation problem in power system, this paper presents a new method of multi-objective fuzzy optimal power flow calculation based on immune/Tabu search hybrid algorithm. The fuzzy set theory is used to construct the evaluation function in this method, and multi-objective optimization problem is converted into single-objective optimization problem. Every sub-targets are considered through application of the fuzzy set theory, so as to ensure high overall optimization level. High accuracy and flexible immune/Tabu search hybrid algorithm is applied for single-objective optimization, and global optimal solution corresponding to practice is obtained accurately. Using the method, several multi-objective optimal power flow simulations for IEEE 30-bus system are conducted. Compared single-objective optimal power flow with particle swarm optimization and immune algorithm, the results show that the method is an effective to solve the multi-objective optimal power flow problem in power system.