Multi-Objective Economic-Environment Scheduling of Microgrids in the Presence of Hybrid Electric Vehicles and Demand Response to Smooth the Distribution Nodal Prices

Today, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper introduces a new multi-objective optimization model, which in the first objective, minimizes the total operation cost of the microgrid, and in the second objective, improves the reliability index by reducing the amount of energy not supplied. Due to these two objectives, a multi-objective evolutionary seagull optimization algorithm is used to find the optimal global solutions. In this regard, hybrid electric vehicles and demand response programs are used to smooth out distribution nodal prices and reduce CO2 emissions. The 69-bus distribution network has been used to evaluate the efficiency of the proposed method.