传统的粒子群优化（PSO）算法因在微网优化中不易达到全局最优而导致微网运行成本过高,该文采用小生境混沌粒子群优化（NCPSO）算法对混合微网群的运行策略进行协同优化,以实现区域微网经济性最优、环境治理成本最低、风光等可再生能源利用率高等目的。根据所提出的调度策略,建立的优化调度模型包括动态电价下的负荷模型、经济收益模型以及成本模型等,使用NCPSO算法得到多微网在一个周期内的最佳运行状态,实现微网群系统综合能源的互动调控、空间互补。通过分析微网群的功率交互动态、可控能源的发电以及储能电池的荷电状态等,验证微网群的电力负荷响应动态电价,表明了NCPSO算法优化微网群运行的优越性、有效性。
Abstract
The ordinary particle swarm optimization（PSO） algorithm is quite difficult to reach the target of global optimum in the process of optimizing microgrids, which leads to the high operation cost of microgrid. In this paper, the niche chaotic particle swarm optimization（NCPSO） algorithm was used to collaboratively optimize the operation strategy of hybrid microgrid clusters, so as to achieve the goal of regional microgrid economic optimization, environmental governance cost minimum, high utilization rate of renewable energy such as wind and solar energy. On the basis of the expected dispatching tactics, the best dispatching model including load model, economic benefit model and cost model under dynamic electricity price was established. The optimal operation state of multi microgrid in one cycle is obtained by using NCPSO algorithm, o as to realize the interactive regulation and spatial complementarity of comprehensive energy in microgrid clusters system. By analyzing the power interaction dynamics of microgrid groups, the generation of controllable energy and the state of charge of energy storage battery, the power load responding dynamic price of microgrid clusters is verified, which shows the superiority and effectiveness of NCPSO algorithm in optimizing operation of microgrid clusters.
关键词
微电网 /
优化运行 /
调度 /
小生境混沌粒子群优化算法 /
动态电价
Key words
microgrid /
optimization /
scheduling /
NCPSO algorithm /
dynamic pricing
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