Research On Operation Of Power Systems Integrating Electric Vehicles

The increasing energy shortage and environmental pollution make the electrification of transportation become major trends. In recently, the research and promotion of electric vehicles has become the focus of governments and automobile manufacturers. The application of electric vehicle will alleviate the problem of energy shortage and environmental pollution, and it also significantly affects the operation and management of the power grid, which involves many levels such as distribution system, transmission system, generation system and Electric power dispatching data network. In view of this, the operation of power systems integrating electric vehicles is chosen to be the research topic, and the research work and outputs of the thesis are listed as follows:The strategy of improving the distribution system’s ability to accept electric vehicle based on network reconfiguration technology is proposed, which is used to mitigate the impact of electric vehicle on the power system. Multi-objective distribution network reconfiguration model is proposed, and its objective involves reducing power loss, improving the voltage quality and load balance of the transformers. Fuzzy sets are used to handle the multi-objective, and the quantum-inspired binary particle swarm algorithm is used to solve the optimal problem. In addition, coordinated charging model aiming to minimize the peak-valley load is proposed, and the load profile of distribution with electric vehicles’charging load is analyzed. The simulation results show that it is effective to alleviate the adverse effect from electric vehicle by using distribution network reconfiguration technique, which will be of great helpful for improving the ability of distribution network to access electric vehicle.Robust comprehensive optimization for distribution system considering the uncertainties is proposed, which uses the sum of standard deviation punishment and mean value of power loss in uncertain environment as objective function. The uncertainties contain the travel time of electric vehicle, load power and active power output of the small-sized wind farms in distribution network, and the control means include network reconfiguration, capacitor switching, regulating positions of on-load transformer changer. The simulation results show that the robust optimization will effectively reduce the generation of infeasible solutions, and maintain the robustness of solutions in the uncertain environment.The probabilistic power flow of transmission grid with electric vehicles is analyzed. Based on the national household travel survey, the correlation between the first travel time, the returning time and day mileage is investigated, which is described by the copula function. Monte Carlo method is used to calculate the distribution of the electric vehicles’ charging load, and the probabilistic power flow of transmission system with electric vehicles is analyzed. The simulation results show that Copula function can effectively fit the correlation between the travel datas. Night coordinated charging strategies can be effectively arrange the charging load of electric vehicles into the time interval with low load, however, with the increasing of electric vehicles, the charging load will increase significantly, and the voltage distribution of part of nodes and power distribution of part lines will have significant change.The impact of charging and discharging behavior of electric vehicles on the unit commitment is analyzed. Based on the coordinated charging strategy, the inverse discharge capacities of electric vehicles are estimated. Simulation results show that applying different charging and discharging schemes to electric vehicle will obviously impact the optimization results of unit commitment, which depends on the characteristics of charging and discharging of electric vehicle. Applying different charging and discharging schemes will obviously impact the optimization results of unit commitment. The proposed coordinated charging strategy makes the load profile become flat, which generates less generation cost. Utilizing inverse discharging capacity of electric vehicle as spinning reserves will reduce the reserve requirement from the traditional units and further lower the generation cost.The data transmission model was built, and the packet congestion rate was used as information congestion indicator in this paper. Meanwhile, the model took the direction of information flow into account and defined two typical information flow modes, which were vertical information flow and random information flow. The transmission characteristics of electric power dispatching data network (EPSDDN) with star and mesh structure were investigated. Furthermore, the transmission characteristics of two EPSDDNs under attacks were investigated with removal of the core nodes and the key links. Simulation result shows that, there is a close relationship between the transmission characteristic of EPSDDN and network structure. In the normal case, the star network has better performance than the mesh network because of its outstanding capability to relieve the information congestion; while under attacks, the transmission performance of two EPSDDNs show varying degrees of deterioration, and the star network exposes much higher vulnerability than the mesh network does.