基于ε-支配域的模糊多目标无功优化方法

A New ε-domination Based Fuzzy Multi-objective Reactive Power Optimization Approach

基于模糊评价函数建立多目标无功优化模型,采用自适应ε-多目标进化优化算法获取Pareto-近似最优解集,应用后评价模糊控制器实现最优控制策略的选取。该方法相比当前后评价多目标优化方法,寻优时间缩短,优化结果针对性强,能实现自动控制。在IEEE14,IEEE30,IEEE118系统上的计算表明,相比其他几种典型后评价多目标优化方法,该方法在保证寻优质量的同时,提高了寻优效率。

This paper establishes a multi-objective reactive power optimization model based on fuzzy membership functions. A new adaptive ε-MOEA approach is employed to obtain ε-approximate Pareto set. The optimal resolution is obtained by a post-evaluation fuzzy logic controller. Compared to other post-evaluation methods, this approach features fast calculation speed, good orientability and self-adaption. Tests on IEEE 14, IEEE 30 and IEEE 118 system demonstrate that the method achieves high efficiency while retains a good quality in solution compared to other methods.