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Title: Impact of Electric Vehicles and Distributed Generation in Deregulated Power System
Authors: Dutta, Ankush
Supervisor: Prakash, Surya
Keywords: Load Frequency Control,;Electric Vehicle;Distributed Generation,;Brain Emotional Learning based Intelligent Controller
Issue Date: 15-Jan-2021
Abstract: In recent years, integration of renewable sources in electrical grid and deregulation of electricity market has become inevitable. Use of renewable energy decreases consumption of fossil fuel and pollutant emissions. Deregulation of electricity market introduces competition in the electricity market which is beneficial for both suppliers and consumers. However, in a renewable energy integrated power system, there is severe frequency fluctuation due to the intermittent nature of the renewable sources and sometimes due to load changes. As frequency fluctuation is not at all desired for electrical utilities, it should be minimized using load frequency control (LFC) scheme. In this work a LFC scheme incorporating Distributed Generation (DG) and Electric Vehicles (EVs) is proposed and implemented on multi-area deregulated hybrid power system (DHPS) having two different configurations. The salient feature of this work is that renewable energy sources (RESs) are made to participate in LFC along with proper choice of back-up sources to offset the intermittency. Configuration-1 of the power system comprises of three interconnected areas. Area-1 consists of a thermal, hydro and a solar-battery unit. Supercapacitor (SC) is also connected to this area while area-2 consists of thermal, hydro and fuel cell-aqua electrolyser unit. In area-3 biomass based Heavy Duty Gas Turbine (HDGT) and Diesel Engine Generator (DEG) contributes to power generation along with thermal and hydro generating units. To improve the LFC performance, combination of Thyristor Controlled Phase Shifter (TCPS) and SC (TCPSSC unit) is integrated into the power system. The implementation of TCPS-SC unit arrests the initial fall in frequency as well as the tie-line power deviations after a sudden load disturbance. The performance of the developed DHPS model is investigated by using proportional-integral-derivative (PID) controller. Configuration-2 of the power system consists of a two-area DHPS model. Area-1 consists of thermal, hydro and solar photovoltaic (PV). EVs are used to handle intermittency of solar power while area-2 consists of thermal, hydro and biomass based HDGT. To make it more realistic, effect of nonlinearity constraints and time delay in communication channel is also considered. The performance of the developed DHPS model is investigated by using PID, fractional-order PID (FOPID) and brain emotional learning based intelligent controller (BELBIC). Simulated results show the superiority of BELBIC controller over other controllers in handling various LFC issues.
Appears in Collections:Doctoral Theses@EIED

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