Stochastic energy management of smart microgrid with intermittent renewable energy resources in electricity market

Highlights: • A stochastic management algorithm for multi MGs is proposed to minimize total cost. • The interactions between MGs, upstream networks, and the electricity market are modeled. • Market clearing price (MCP) is modeled due to renewable resources intermittencies. • The optimal size of renewable resources in MGs are determined before and after participation in the electricity market. • The method's robustness is validated through sensitivity analysis. Stochastic energy management of smart microgrids (MGs) is an important subject due to the high integration of intermittent resources, including wind turbine (WT) and photovoltaic (PV) units. The complexity of the multi MGs management algorithm increases, considering their participation in an electricity market. In this paper, we proposed a stochastic energy management algorithm to address the participation of smart MGs in the electricity market, which minimizes the total cost and finds the optimal size of different components, including WT, PV unit, fuel cell, Electrolyzer, battery, and microturbine. The intermittencies in the PV output power, WT output power, and electric vehicle (EV) are modeled and integrated into the management algorithm using the Copula method. The market clearing price (MCP) is found using a game theory (GT) model and Cournot equilibrium. To verify the efficiency of the proposed method, it is tested on a sample three-MG, where the optimal size of various components is obtained. The obtained results verify that the total cost of MG decreases and the better performance can be obtained after participation in the electricity market. A sensitivity analysis is also done to evaluate the effects of various parameter changes (e.g., capital cost, replacement cost, and operation and maintenance cost) in various scenarios, where the obtained results verify that the cost reduction is obtained over different scenarios.