Grid Integrated Smart Charging Management of Electric Vehicles for Demand Response in Distribution System

Abstract

The ever-increasing energy demand accompanied by fossil fuel depletion and environmental degradation has paved the way for transportation electrification. Electric Vehicles (EVs) are environmentally friendly alternatives to conventional Internal Combustion Engine (ICE) driven vehicles. For large-scale deployment of EVs, sustainable charging infrastructure needs to be developed. However, the increasing popularity of electric vehicles will pose a significant threat to existing electric grids due to added load of electric vehicles in the power systems distribution network. This thesis provides the solution for stabilizing electric grid health through two objectives. First is to charge EV batteries at variable charge rates, and second, to provide utilities with active and reactive power support using EV batteries and charging stations, respectively. This will essentially level the utility load throughout the day by providing power to charge EV batteries during off-peak hours, and, on the other hand, utilities will take power from EV batteries for peak power shaving during peak power demand hours of the day. The peak shaving and valley filling potential of the energy management system (EMS) is investigated in high-rise residential buildings equipped with PV storage systems. The battery bank is capable of charging from the off-peak load of the grid with PV generation. The EMS could effectively reshape the net electricity demand profile and match customer demand and PV generation. The charging station placement problem is a complex problem involving the power distribution network and road network. The charging stations must be placed in the distribution network in such a way that the negative impact of the placement of charging stations on the operating parameters of the distribution network is minimized. The impact of EV charging stations on operating parameters of the distribution network, such as voltage stability, load variance and power losses, are thoroughly analyzed in this thesis. Differential evolution optimization is developed and used for solving the charging station placement problem. The proposed formulations of the charging station placement problem are validated on superimposed IEEE 33 bus distribution. Currently installed transformers are of a certain fixed rating and cannot accommodate the rapid continuous growth, resulting in the utility not being able to meet the power demand. The concept of load shedding is utilized when supply cannot meet demand due to certain system constraints and demand reduction is required. The demand response is made to support EV fleet connected to the distribution circuit while assuming that the first peak demand can be met. The Programmable logic control (PLC) for EV demand side integration follows two categories (1) Smart charging connection and (2) The vehicle to grid concept. It also emphasizes managing battery security and safeguarding it from unfavorable operating conditions, including overcharging, severe discharge, over/under voltage, and thermal degradation. A humane machine interference (HMI) is developed and connected with the PLC in order to further provide reliable and efficient control monitoring of the battery parameter. Siemens S7 1200 and Siemens TIA WinCC Advanced V16.0 software are used to create and code the recommended digital battery management systems (BMS) HMI/ SCADA interface.