基于改进萤火虫算法的分布式电源优化配置研究

分布式电源(DG)的位置和容量优化配置可确保其发挥更好的技术经济效用。本文在分析DG特性的基础上,建立了考虑含分布式电源的有功网损费用最小和投资成本最小模型;鉴于传统萤火虫算法具有容易早熟、收敛速度慢、过度依赖控制参数的缺陷,将混沌搜索策略融入到萤火虫算法,提出了一种改进型多目标萤火虫算法;为克服算法对控制参数依赖性较强缺陷,利用混沌理论的随机性、遍历性及其规律性特性,对萤火虫算法的参数进行调整。最后,以PG&E69节点配电网为例,采用Matlab仿真软件验证本文所提算法在求解DG优化配置问题上的有效性,及其与粒子群算法、常规萤火虫算法相比所具有的更好的寻优精度和优化结果。

Research on Optimized Distributed Generations Locating Based on Modified Firefly Algorithm

The optimal configuration of location and capacity of the distributed generation(DG) can widen its technical and economic utilization. Based on the detailed analysis on the characteristics of DG, a model is built to minimize active power loss cost and investment cost. In terms of the defects of traditional firefly algorithm which has such characteristics as easy premature, slow convergence speed and excessive dependence on control parameters, a kind of modified multi-objective firefly algorithm is proposed in this paper by integrating Chaotic search method into firefly algorithm. In order to overcome the disadvantage that the algorithm depends strongly on control parameters, the parameters of firefly algorithm can be adjusted by using the randomness, ergodicity and regularity of the chaos theory. In the end, taking PG & E 69-node distribution network as an example, the Matlab software is used to verify the effectiveness of modified firefly algorithm to locate DG optimally. Results show that it has higher optimization precision and better optimization results than particle swarm optimization(PSO) algorithm and conventional firefly Algorithm.