基于改进免疫遗传算法的含分布式电源配电网规划

Distribution Network Planning with Distributed Generation Based on Improved Immune Genetic Algorithm

随着大量的分布式电源的接入,配电网规划变得越来越复杂。在优化分布式电源接入总量和考虑传统电源多种约束的基础上,建立以最佳配电网年费用为目标函数的配网规划数学模型。针对改进免疫遗传算法具有生物免疫系统中抗体多样性的保持机制和基于抗体浓度的调节更新机制,同时又具有一般进化算法的随机搜索能力,采用改进免疫遗传算法对配电网规划问题进行求解,并借鉴支路交换的思想设计杂交算子和变异算子,以避免辐射性检查过程,使得算法的寻优能力增强。通过算例分析,与简单遗传算法和常规免疫遗传算法相比,提出的改进免疫遗传算法更适合于求解含分布式电源的配电网规划问题,结果表明了该算法的可行性;同时表明,含分布式电源规划方案较无分布式电源规划方案具有很大的经济和社会效益。

With the access of a large number of distributed generations, distribution network planning becomes more and more complex. Based on the amount of optimization distributed power access and considering a variety of traditional power constraint, the paper establishes the mathematical model of distribution network planning taking the best annual cost of the distribution network as the objective function. According to the biological immune system antibody diversity of keep mechanism with improved immune genetic algorithm and based on antibody concentration regulation update mechanism, as well as a general evolutionary＇ algorithm of random search ability, this paper uses the improved immune genetic algorithm for solving distribution network planning problem, and references branch exchange thoughts to design cross operator and mutation operator, in order to avoid the radioactive inspection process, which makes the algorithm optimization ability enhancement. Through the example analysis, and comparing it with simple genetic algorithm and normal immune genetic algorithm, the results show that the proposed improved inmlune genetic algorithm is more suitable for solving distribution network planning problem with DGs and feasible, and show that the planning scheme with DGs has more economic and social benefits comparing with the planning scheme without DGs.