Research On Economic Dispatch Of The Microgrid With Electric Vehicles

The electricity and transportation industries are the main sources of greenhouse gas emissions on Earth. The study on Microgrid(MG) and Electric vehicle(EV) have become hotspot researches in recent years for their friendly environment and low cost of energy consumption. Microgrid(MG), which can be operated either interconnected or isolated from the utility grid as one controlled entity, are low voltage distribution networks comprising various distributed generators, storage devices and loads. Electric vehicles(EV) plugged into the MG system can be used as mobile storage devices, which can supply power to the MG system when the load is in the peak.Economic dispatch(ED) problem plays an important role in the operation of the MG system, that is how to coordinate the output of the distributed generations to minimize the total operation cost of the microgrid as well as to meet the load demand and the various constraints. The greatest differences between the ED problem of the microgrid with EV and without EV are the owner’s behavior, battery’s SOC and output limit of the EV, so the ED problem of the microgrid is more complex. The purpose of this thesis is to research on the economic dispatch problem of the microgrid with EV and analyse the EV’s impacts on the economic operation of the MG system.This thesis firstly developed the structure of a microgrid which consists of photovoltaic cell, wind turbine, microturbine, fuel cell, diesel engine, battery storage and EV, and assumed a typical owner’s behavior. Secondly, four typical control strategies of the microgrid are proposed. According to control strategies, this thesis established the economic dispatch model of the microgrid with electric vehicles under independent and grid-connected operation model, and proposed the lowest operating costs, the lowest emission cost and the lowest comprehensive cost optimization objectives. And then, this thesis proposed an improved particle swarm optimization(PSO) method for solving the proposed model. The calculation example compared the optimization results under different control strategies and different optimization objectives, and the optimization results show that the proposed model and the improved particle swarm optimization method are effective. It is indicated that better economy can be achieved while microgrids are connected with utility power grid and the plug-in EV can benefit both of the microgrid and the EV owners.