基于改进蝙蝠算法的配电网分布式电源规划

合理规划接入电网的分布式电源能够提高能源利用效率，提高电力系统运行的经济性、灵活性和可靠性。建立了以分布式电源建设和运行总费用最小、系统网损最小、静态电压稳定指标最大为优化子目标的多目标规划模型。采用了一种新的仿生算法--蝙蝠算法，并针对蝙蝠算法的不足之处进行了改进，有效地解决了该算法易陷入局部最优、后期收敛速度慢等问题。通过14节点配电网测试系统进行了分布式电源选址和定容仿真分析。仿真结果表明，与传统的蝙蝠算法、粒子群算法相比，采用改进的蝙蝠算法能够更好、更快地得到分布式电源接入配电网的最优规划方案，验证了算法的正确性和可行性。

Distributed Generation Planning for Distribution Network Based on Modified Bat Algorithm

Rational planning of distributed generation in power grid can improve the energy efficiency and the economy, reliability and flexibility operation of power system. This paper constructed the multi-objective planning model with minimizing total investment cost in the construction and operation of the distributed power system and the power loss of system, as well as maximizing the investment the static voltage stability index as optimization subgoals. This paper used and improved a new bionic algorithm-bat algorithm, which could effectively solve the problems of easily trapping into local optimal solution and slow convergence speed in the later stage. Then, 14-node distribution network test systems were used to simulate and analyze the location and capacity of distributed generation. The simulation results show that, compared with the traditional bat algorithm and particle swarm optimization, the improved bat algorithm can better and faster get the optimal planning scheme of distributed generation connected to distribution network, which can validate the correctness and feasibility of the algorithm.