Management of renewable-based multi-energy microgrids with energy storage and integrated electric vehicles considering uncertainties

One of the best solutions to overcome environmental, technical as well as economic problems in the power system is the use of Plug-in hybrid electric vehicles (PHEVs). The penetration of a large number of PHEVs in the power system and the possibility of their proper control and management provide benefits of a large energy storage system for the distribution system operator. However, the correct management of PHEVs along with renewable energy sources (RESs) is a very important challenge that requires more research in this field. The main goal of the article is the scheduling of a microgrid with several PHEVs and RESs in order to achieve economic, technical and environmental benefits. To obtain more accurate results in microgrid operation, the intermittent behavior of renewable resources, PHEVs and loads has been modeled using the Mont Carlo simulation (MCS). Uncertainty parameters considered in this article include the charging demand of PHEVs, loads, electricity price and output power of RESs. The objective function is to reach minimum total costs considering the technical constraints. In order to resolve the defined optimization problem, including the objective function and the constraints of the problem, the modified sparrow search (MSS) algorithm is applied. The recommended tech-nique is simulated on the test network with the MATLAB software and the outcomes are compared with con-ventional algorithms. As the results of the simulations show the suggested scheme performs superior performance than other optimization algorithms.