Optimal energy management strategy for a renewable based microgrid with electric vehicles and demand response program

This paper suggests an optimal management for a microgrid containing renewable sources and electrical vehicles (EVs) with responsive loads for minimizing operation costs and emissions. The role of EVs is coping with peak load conditions while responsive loads can deal with uncertainties of renewable-based sources. A two-stage model is implemented for clearing the energy and reserve markets. The costs of generation and reserve power are minimized first, and then the costs of variations in the management owing to the changes in wind turbine and photovoltaic (PV) are optimized. To optimize the objective function, an improved shuffled frog leaping algorithm (ISFLA) is used. Simulation results are provided for different case studies in a microgrid and the outcomes confirm the superiority of the recommended algorithm in comparison with other conventional approaches. The use of EVs and responsive loads provides advantages such as minimizing the operational cost, emissions and the changing behavior of the PV and wind turbines.