Stochastic Energy Management Framework for Multi-Microgrid with Demand Response and Battery Storage

Abstract

this paper proposes a techno-economic assessment of the integration of the Demand Response Program (DRP) and Battery Energy storage system (BESS) in Multi-Microgrid (MMG) energy management (EM). Additionally, to consider the uncertainties in MMG resources, the Point estimation method (PEM) with Quantum Artificial Rabbits Optimization (QARO) technique is developed to estimate the probability density function (PDF) of operating cost and Independence Performance Index (IPI). A day-ahead EM problem is modeled for operating and transaction cost minimization while the MMG benefit is maximized. The Proposed QARO is employed to solve the deterministic problem in three case studies. The operating cost is reduced with the integration of DR and the BESS. The integration of DR and BESS enhanced the IPI by 2.4%. In addition, the proposed hybrid QARO-PEM is implemented to solve the stochastic EM problem, and the PDF for operating cost and IPI are estimated.