基于启发式免疫遗传算法的配电网广义电源规划

在分布式电源接入配电网的规划中将广义电源的有功功率作为控制变量,考虑了广义电源无功功率对配电网分布式电源优化配置的影响,从而合理规划广义电源接入,降低系统的网络损耗,进一步提高系统运行的电压水平。针对传统优化算法在局部搜索能力和收敛性能等方面的缺陷,根据累加优化原理对系统种群进行初始优化以提高收敛速度,在疫苗接种时利用矢量矩浓度的概念进行抗体选择,依据抗体浓度和抗体适应性原则进行个体优选,提出了启发式免疫遗传算法。对IEEE-33节点系统的计算分析表明,该方法能够对广义电源在配电网中的选址和定容进行有效配置和优化,在寻优能力和收敛速度上优于传统算法。

Generalized Power Sources Planning of Distribution Network Based on Heuristic Immune Genetic Algorithm

Considering the influence of generalized reactive power source on the distributed generation optimization planning in distribution network, the generalized power sources are reasonably planned in distribution system by taking the active power of generalized power source as control variables. The loss of distribution network is reduced and the quality of voltage is improved. Aiming at the problems of convergence and local search ability in traditional optimization method, a new heuristic immune genetic algorithm (HIGA) is introduced to accelerate the convergence and enhance the accuracy. According to the theory of accumulation optimization, the system population is initialized to improve convergence. The principle and concept of vector distance during the process of vaccination is adopted to save the best individual. According to the principle of antibody density and fitness, the fittest population can be selected. Taking IEEE-33 node system for an example, the result shows that the proposed algorithm can effectively solve the optimal problem of selection site and capacity for generalized power sources in distribution network. Compared with the traditional algorithm, HIGA has some advantages, such as quickly convergence and higher efficiency.