Two-stage stochastic operation considering day-ahead and real-time scheduling of microgrids with high renewable energy sources and electric vehicles based on multi-layer energy management system

Abstract

In this paper, two- stage operation of a grid-connected microgrid (GCMG) with high penetration rate of renewable energy sources (RESs) and electric vehicles (EVs) is presented based on day-ahead and real time energy markets, where GCMG follows multi-layer energy management system (EMS). In the proposed method, all microgrids (MGs) are categorized to individual MGs and an MG community (MGC) connected to the distribution network which manages other MGs. Hence, the first/second layer of EMS is applied to individual MGs/MGC according to hourly operation in the day-ahead market at the first stage of the problem. The first layer model minimizes the operating cost of the MG subject to network model, distributed generations (DGs), energy storage systems (ESSs) and EVs parking lot constraints in individual MGs. The second layer model minimizes the sum of expected operation and risk costs of the MGC, limited by the same constraints of the first layer problem. In the second stage, the imbalance cost between day-ahead and real time operation is minimized, constrained to MGs and their devices model based on 5 min real-time dispatch. Stochastic programming based on coupling Mont Carlo Simulation (MCS) and fast backward/forward approach is used to model uncertainties of load, renewable power, energy price, and EVs parameters. Therefore, multi-layer energy management, coordination and RESs and EVs in GCMG, two-stage operation including day-ahead and real-time scheduling, and the procedure used for stochastic modeling of uncertainties are among the contributions of the proposed scheme. Finally, to evaluate the efficacy of proposed approach, it is tested on a standard system in GAMS software.