Artificial neural network based active power management controller for electric vehicle charging station

Abstract

This paper presents a DC microgrid-based electric vehicle charging station (EVCS). It consists of a solar photovoltaic (PV) system, stationary battery storage (SBS), grid as a 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 the 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 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 the grid. The proposed APMC is tested for three different modes using MATLAB Simulink software.

KEYWORDS:

• Artificial neural network (ANN)
• bidirectional converter
• hybrid microgrid
• electric vehicle charging station
• stationary battery storage

Disclosure statement

No potential conflict of interest was reported by the author(s).