Development of energy management framework and power converters for electric vehicle application

Abstract

Growing need of electrical energy always motivates the energy engineers to manage newlinethe demand with existing resources, optimize the usage according to the generation and newlinedemand with the help of conventional resources and renewable based energy generation. newlineHowever, recent trends show that the penetrated variable renewable power often makes newlinetechnical issues for grid operators, especially in weak distribution networks. A solution newlineto control the highly penetrated renewable power is utilizing maximum energy for newlinemeeting in-house demand through energy management strategies with help of demand newlineside management (DSM) techniques and storage facilities. However, the cost of storage newlinefacilities often constraints the implementation of such solution techniques. Meanwhile, newlinethe developments in electric vehicle (EV) technology and its commercialization facilitate newlinemore EVs in residential/commercial transportation sector with a storage facility. This newlineprovides a chance to use the EV storage for energy balancing services through scheduled newlinecharging (Grid to Vehicle G2V) and discharging (Vehicle to Grid V2G) and thereby newlineovercome the need of dedicated storage facilities. Hence, an effective energy newlinemanagement framework and on-board power converters for EV are required to newlineimplement such solution techniques that benefits both the consumer and the utility grid. newlineThis research focus on the development of energy management framework and power newlineelectronic converters for EV application. A novel objective function is proposed for the newlineenergy management of residential consumers who owns EVs and renewable power plants newlineto impart energy self-sufficiency. The objective function tries to meet the demand newlinerequirements of critical loads and shiftable loads through load scheduling with minimized newlineenergy transactions with the utility grid by controlling charge-discharge sequence of EV newlinestorage according to the variation in the renewable energy. Mixed Integer Linear newlineProgramming (MILP) technique is used to solve the optimization problem.