Economic energy and reserve management of renewable-based microgrids in the presence of electric vehicle aggregators: A robust optimization approach

Renewable energies and electric vehicles are introduced as promising solutions to save energy costs and reduce environmental impacts in microgrid systems. However, the uncertainty of such resources would necessitate the development of advanced management models for optimal operation of microgrids. To address this issue, this paper proposes a new model for energy and reserve management of microgrids in the presence of electric vehicles. To effectively cope with uncertainties, a robust optimization methodology is proposed and applied to handle the uncertain parameters. Furthermore, the optimization problem is transferred into a mixed-integer linear programming model to ensure achieving near-global and tractable solutions. The proposed model aims to coordinate energy serving entities a way that the microgrid social welfare is optimized while at the same time driving requirements of the electric vehicle owners satisfied reliably. The methodology is implemented to a microgrid and solved over a day-ahead scheduling time horizon. The trends of techno-economic-environmental indices confronting to the increasing level of uncertainty control parameter are evaluated thoroughly in four case-studies. A robust multi-objective model is developed to trade-off between social welfare and emission. The numerical results are verified through a Monte-Carlo Simulation strategy to demonstrate the impressiveness of the proposed methodology.