Optimal scheduling of reconfigurable microgrids incorporating the PEVs and uncertainty effects

Abstract

Here, an intelligent optimization method for optimal switching in reconfigurable microgrids is proposed to reduce the cost of microgrids with the presence of distributed generation resources and electrical vehicles. The suggested model deploys the point estimation to manage the uncertainties in the microgrid. The uncertainties are due to load demand, market price, electric vehicle charging and discharging, wind turbine production capacity and photovoltaic cells. The formulation structure is in the form of a nonlinear and single-objective problem that minimizes the total microgrid asking price by observing the constraints in the problem. In this research, an improved algorithm is used to solve the optimization problem to advance the performance of the process. The capability and efficiency of the proposed method have been investigated on the IEEE 33-Bus standard test network and the simulation results have shown that optimal switching can be useful in more fitting power distribution and reduction of microgrid cost with the presence of electric vehicle and various scattered products.