Artificial Neural Network Based Active Power Management Controller for Electric Vehicle Charging Station

ABSTRACTThis paper presents a DC microgrid based electric vehicle charging station (EVCS). It consists of solar photovoltaic (PV) system, stationary battery storage (SBS), grid as power generation source and electric vehicle as load. An adaptive interaction artificial neural network (ANN)-based active power management controller (APMC) is proposed for DC microgrid based EVCS. It works in three different modes of operation. The mode of operation depends upon the PV power available and current state of charge of SBS. This APMC is designed to get the electricity from the PV array and SBS preferably. If the PV and battery power both are not sufficient to fulfil the requirement, power is drawn from the grid. When a solar PV system generates excess power and the SBS is sufficiently charged, then excess power is delivered to grid. The proposed APMC is tested for three different modes using MATLAB Simulink software.Keywords: Artificial neural network (ANN)Bidirectional converterHybrid microgridElectric vehicle charging stationStationary battery storageDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also.