多能互补微网集群分布式优化调度

Distributed Optimal Dispatch of Interconnected CCHP Microgrids

互联的微网集群有利于不同微网之间的功率流动,从而使得微网之间形成优势互补,有利于能源的有效利用。为了保护不同微网之间的信息隐私性以及实现调度的独立性,分别基于广义的Benders分解(generalized benders decomposition, GBD)、最优条件分解(optimal condition decomposition, OCD)和辅助问题原则(auxiliary problem principle,APP)的分布式算法框架求解多能互补(combined cooling,heating,and power, CCHP)微网集群(microgrid cluster,MGC)的优化调度问题。为有效表征可再生能源以及冷热电负荷的不确定性,机会约束规划(chance constrained programming,CCP)用来处理微电网与外界功率交换之间的联络线约束以及热回收系统约束。同时,引入虚拟区域协调器解耦微网集群母线与大电网的电力线连接以便应用分布式算法。4个互联的多能互补微网验证了所提算法在夏季场景典型日下的有效性,并对3种算法的特点进行对比分析。

Interconnected microgrids enable mutual power support among microgrids and improve utilization of renewable energy sources.To preserve information privacy and achieve scheduling independence of microgrids,the problem of multi-area economic and environmental dispatch is computed with distributed algorithm framework,i.e.generalized Benders decomposition(GBD),optimal condition decomposition(OCD)and auxiliary problem principle(APP).Moreover,chance constrained programming(CCP)is added to address the uncertainty factors of renewable energy,cooling,heating,and electrical loads.Meanwhile,virtual area coordinator is introduced to decouple power line connection between the bus and main grid to apply the distributed algorithm.A case study with four networked CCHP(combined cooling,heating,and power)microgrids in two kinds of topologies is performed to demonstrate effectiveness of the proposed approach in summer scenario.