摘要
为提高清洁能源利用率、降低高渗透率可再生能源型微网成本,基于分时电价背景,在综合考虑风电、光伏、燃气轮机、大电网联络线等多类型电源运行特性的基础上,以经济成本为目标,建立了冷热电联供(combined cooling,heating and power,CCHP)型微网协同优化模型,同时提出一种结合粒子群思想、协同进化理论框架和天牛须搜索(beetle antennae search,BAS)算法的改进优化算法——CoPSO-BAS算法。该算法同时兼顾了BAS算法、协同进化算法与粒子群算法的优点,具有良好的全局最优解搜索能力与收敛性。以我国西北某微网系统作为实际算例,应用CoPSO-BAS算法进行计算,并与经典BAS算法对比,验证了CoPSO-BAS算法的全局最优解搜索能力和收敛性能上的优越性。
To improve utilization rate of clean energy and reduce cost of the high-permeability renewable energy micro-grid,a kind of collaborative optimization model for the combined cooling,heating and power(CCHP)micro-grid is established on the basis of time-of-use electricity price and comprehensive consideration of operating characteristics of wind power,photovoltaic,gas turbine,interconnecting ties of large power grids and other types of power supplies which aims at economic cost.Meanwhile,an improved optimization algorithm called CoPSO-BAS combining particle swarm idea,co-evolution theory and beetle antennae search(BAS)algorithm is proposed which gives consideration to advantages of BAS algorithm,the co-evolution algorithm and the particle swarm optimization(PSO)algorithm and has favorable global optimal solution search ability and convergence.Taking one micro-grid in Western China for an example,the CoPSO-BAS algorithm is used for calculation and compared with traditional BAS algorithm,superiority of the CoPSO-BAS algorithm in global optimal solution search ability and convergence is verified.
作者
谭碧飞
陈皓勇
梁子鹏
陈思敏
TAN Bifei;CHEN Haoyong;LIANG Zipeng;CHEN Simin(School of Electric Power,South China University of Technology,Guangzhou,Guangdong 510640,China)
出处
《广东电力》
2019年第9期85-93,共9页
Guangdong Electric Power
基金
国家重点研发计划项目(2016YFB0900100)
关键词
微网
冷热电联供
协同进化理论
粒子群算法
天牛须搜索算法
经济调度
micro-grid
combined cooling,heating and power(CCHP)
co-evolution theory
particle swarm optimization
beetle antennae search algorithm
economic dispatch
