基于多目标混沌量子遗传算法的分布式电源规划

Distributed Generation Planning Based on Multi-Objective Chaotic Quantum Genetic Algorithm

针对配电网加入分布式电源的经济技术优化目标,给出了分布式电源多目标规划的数学模型;结合实数编码量子遗传算法和非支配排序、精英保留、分层聚类等多目标优化策略,提出了多目标混沌量子遗传算法,并对分布式电源的安装位置和容量进行了综合规划研究。算例分析表明,所提算法在计算精度、收敛速度和寻优能力上均优于传统多目标遗传算法,为实现分布式电源的多目标规划提供了理论依据。

In allusion to economic-technical optimization objective of distribution network to which distributed generation （DG） is added, a mathematical model for multi-objective planning of DG is given. Integrating real-coded quantum generic algorithm with such multi-objective optimization strategies as non-dominated sorting, elite reservation and hierarchical clustering, a multi-objective chaotic quantum generic algorithm is proposed, and comprehensive planning research on installation sites and capacities of DGs is performed. Analysis on calculation results shows that the proposed algorithm possesses better performances in computational accuracy, convergence speed and searching ability than traditional multi-objective generic algorithms, thus it is available for reference to the implementation of multi-objective planning of DGs.