An smart stochastic approach to model plug-in hybrid electric vehicles charging effect in the optimal operation of micro-grids

This paper proposes a sufficient stochastic framework to assess the influence of charging demand of plug-in hybrid electric vehicles (PHEVs) on the operation of renewable micro-grids (MGs). In this regard, an intelligent charging approach is proposed to shift the charging demand of PHEVs to off-peak load hours. In order to reduce the total cost of the MG, battery as the storage device is incorporated in the MG. Since the problem investigated is a hard complicated optimization problem, a new optimization method called Modified Clonal Selection algorithm (MCSA) is utilized too. The proposed MCSA employs two modification techniques to improve the position of antibodies in the face of local optima. For modeling the uncertainty of parameters, 2m-point estimate method (2m-PEM) is utilized as the stochastic framework. The feasibility and appropriate performance of the proposed method are examined on a standard MG.