Design of a Power Management Strategy in Smart Distribution Networks with Wind Turbines and EV Charging Stations to Reduce Loss, Improve Voltage Profile, and Increase Hosting Capacity of the Network

Today, due to environmental and political reasons, countries around the world are required to use green energies, such as wind and solar energy. Also, most countries have switched to using electric vehicles (EVs) to reduce environmental pollution. Since smart distribution systems’ distributed generation (DG) power output is limited, this paper addresses this issue by planningcharging parking lots of EVs. The problem was formulated as a nonlinear optimization model. The objective function was to increase the power output, reduce the loss cost, and reduce the bus voltage deviations. Also, technical and economic limitations were considered in solving the planning problem. The uncertainty of consumption load, the behavior of EVs, and the output power of wind DGs were modeled using a combination of Monte Carlo and means methods. The improved gray wolf optimization (IGWO) algorithm was adopted to optimize the objective function. A standard IEEE 33-bus smart distribution system was studied to show the efficacy of the suggested solution. The results demonstrated the proposed solutions' high performance in improving the wind DG power output of the distribution system (PODS).