A Novel Energy Management Scheme for a Microgrid with Renewable Energy Sources Considering Uncertainties and Demand Response

In recent years, the grid penetration of renewable energy resources and electric vehicles has increased rapidly. However, their environmental benefits will lead to uncertainty in their profile due to their stochastic behavior. In this article, a linearized energy management model is proposed to improve the operating cost of the microgrid, including renewable energy resources, energy storage systems, distributed generation, combined heat and power, and electric vehicle parking. Uncertainty in stochastic parameters of the system, including load demand, electricity price, and profile of renewable energy resources, are managed using a machine learning approach and the availability of electric vehicles in the parking lot using the point estimate method. Furthermore, the effect of an electricity price increase on the total operating cost has been evaluated, and the results show that despite a 40% increase in the price of electricity, the total cost increases by 5.35%.