Controlled electric vehicle charging for reverse power flow correction in the distribution network with high photovoltaic penetration: case of an expanded IEEE 13 node test network

Abstract

Over the past years, the penetration of photovoltaic (PV) systems into the distribution network has experienced significant augmentation as the pressure to reduce greenhouse gas emissions into the atmosphere keeps increasing while the prices of the solar components keep reducing. Despite the benefits PV systems bring to the distribution network, the high penetration of this technology into the distribution network could lead to reverse power flow (RPF) when the PV systems produce more than the local loads require. This RPF could result in the malfunctioning of protective devices and their coordination. This research addresses this problem by utilizing electric vehicles (EVs) that are currently revolutionizing the transport sector. Here, the charging of EVs during the day is intelligently controlled to mitigate RPF as a result of the excess power produced by the PV systems. Resolving RPF is achieved through a control system that measures the power flow on each phase of the main grid substation. If at any instance negative power is detected (reverse power), quantified EVs needing recharge are instantly incorporated into the network for charging through the automatic closure of the power switches of the required number of charging points with EVs whose total power demand equals the amount of reverse power detected. The excess power is hence absorbed and stored by the EVs. The proposed method is tested on an expanded IEEE 13 node test feeder and simulated using ETAP software. Simulation results show the effectiveness of the proposed method in eliminating RPF which occurs from 10:00 am to 12:00 noon by connecting the required number of EVs during that timeframe. The proposed method involves the distribution network operators working in synergy with the transport sector to effectively solve the problem of RPF in the distribution network.