Abstract:
An electric power system is a meshed network which includes three major components: transmission, distribution, and demand systems. The future smart grid will be a highly intelligent electric power system that will have a profoundly impact on all the three areas. This dissertation focuses on 1) the competitive power market study, 2) optimal power management in microgrid, and 3) intelligent demand response strategies of residential system. In the transmission system, generation companies and load serve entities are encouraged to compete for the amount of power generation and load demand. Therefore, utility companies require an efficient and reliable computational tool to analyze the competitive power markets. However, most of existing commercial power system simulators are unable to evaluate a competitive power market directly. This dissertation proposes a method to convert a competitive power market problem in such a way that PowerWorld can be used for broad competitive power market studies, including optimal power flow, unit commitment, and agent-based learning. In the distribution system, it's urgent to develop an efficient computational tool that can be used in the energy management system to control different types of renewable energy in microgrid. This dissertation develops a mechanism to use PowerWorld for comprehensive analysis of microgrid power markets as well as optimal power flow under different power converter operating modes. In the demand system, demand response (DR), a critical component for smart grid, will adjust the load power consumption pattern to achieve high economic efficiency. This dissertation proposes several different DR strategies for home appliance of the residential system.
