Impact of plug-in hybrid electric vehicles charging demand on the optimal energy management of renewable micro-grids

This paper suggests a new stochastic expert framework to investigate the charging effect of plug-in hybrid electric vehicles (PHEVs) on the optimal operation and management of micro-grids (MGs). In this way, a useful method based on smart charging approach is proposed to consider the charging demand of PHEVs in both residential location and public charging stations. The analysis is simulated for 24 h considering the uncertainties associated with the forecast error in the charging demand of PHEVs, hourly load consumption, hourly energy price and Renewable Energy Sources (RESs) output power. In order to see the effect of storage devices on the operation of the MG, NiMH-Battery is also incorporated in the MG. According to the high complexity of the problem, a new optimization method called θ-krill herd (θ-KH) algorithm is proposed which uses the phase angle vectors to update the velocity/position of krill animals with faster and more stable convergence. In addition, a new modification method is proposed to improve the search ability of the algorithm, effectively. The suggested problem is examined on an MG including different RESs such as photovoltaic (PV), fuel cells (FCs), wind turbine (WT), micro turbine (MT) and battery as the storage device.