Robust Energy Management of Multi-microgrids System Considering Incentive-Based Demand Response Using Price Elasticity

Abstract

The worldwide exponential augmentation of energy consumption has prompted the emergence of microgrids (MGs) integrated with various distributed generations, storage systems, renewable energy resources (RERs), and plug-in hybrid electric vehicles (PHEVs). This paper investigates the energy scheduling and trading of the interconnected MGs to minimize the total operational cost of the multi-MGs system. In this regard, a robust optimization technique is employed for attributing the intrinsic intermittencies of RERs, load demands, and PHEVs charging demands. The proposed scheme also considers an incentive-based demand response model and assesses the impacts of the energy pricing along with incentives in response to the pricing elasticity for effective consumer participation. Within this framework, each MG schedules its operation and responds to energy trading with the adjacent MGs and the utility grid via peer-to-peer communication. The formulated EM problem is solved using a hybrid grey-wolf and whale optimization algorithm. Comprehensive studies are conducted on a 5-MG system comprising residential and industrial MGs and several simulation outcomes are reported to validate the proposed scheme.