Distributed home energy management system with electric vehicles

Abstract

Due to the increasing concerning within protecting environment by reducing CO2 emissions from vehicles, the adoption of electric vehicles in the world has increased dramatically. Since the loads of electric vehicles are seldom considered in the current practice of power system planning, it may bring negative impacts on the stability of power grids and risks in system operations and management. Thus, more intelligent management should be applied to improve the scenarios. A smart grid is a modernized electrical grid, using analog or digital information and communications technology to gather and act on infor- mation. By enabling two-way communication, the smart grid becomes an intelligent electricity network that could save energy, reduce cost and enhance reliability of the grid. Distributed power generation is one of the main highlights of the smart grid. With the generated resources from solar panels and wind turbines, the electricity consumption from the grid could be fairly reduced to some degree. In this thesis, a home energy management scenario is considered where the system is integrated with electric vehicle as additional electricity stor- age and solar panel to generate power locally. Scheduling algorithms are developed to focus mainly on the requirements of reducing consumption from the power grid and electricity expenses. In the Maximum Renew- able Resources Scheduling, the generated resources from solar panels are maximally used. In the Minimum Cost Scheduling, the aim is to minimize the charging expenses. Due to the high complexity problem of the optimization algorithm, greedy algorithm is considered to search for a suboptimal solution.