Multiobjective Optimization Model considering Demand Response and Uncertainty of Generation Side of Microgrid

Abstract

To make better use of renewable power generation, a microgrid system is constructed, containing a multitype power supply and a multienergy storage structure. A multiobjective scheduling optimization model is proposed considering MS differential cost, power abandonment cost, and operation income, and demand response models are introduced to improve the ability of storage and users’ participating in peak shaving. To solve the uncertainty of WPP and PV’s output, the scenario reduction method is adopted, and a single target conversion of multiobjective functions is made through a desion attribute table. The results show that scenario reduction can put a brake on the impact of WPP and PV’s output uncertainty on system dispatch; demand response helps solve the problem of poor matching between the source and load. ESS’s co-operative effect can improve the system’s stability.

Assessment Method for Demand Side User Response Potential based on Game Theory and Information Value

“…DR can improve load characteristics, improve energy efficiency, reduce the peak-valley difference, and promote new energy consumption [1] . It also can adjust the contradiction between power supply and demand quickly and effectively by changing users' behaviors [2] . With smart grids as the implementation platform, electric power companies provide various incentive plans while initiating DR invitations.…”