Coordinated Scheduling And Planning Of Electric Vehicles And Distribution Network

The main research of the article focus on load forecasting of electric vehicle, optimal scheduling of electric vehicles and its influence on distribution network and charging station planning.Among them, the electric vehicle load forecasting is the basis of the optimal scheduling, and directly affect the power quality of distribution network and charging station planning.The optimal scheduling of electric vehicles can reduce the impact of charging load on the power grid, and reduce the cost of the user's charging.For electric vehicles a lot of popularity after a huge load demand, charging station planning more to one step ahead, scientific and comprehensive consideration. These aspects are related to each other but with the urgency of the solution, this paper on the basis of the existing research results do some supplement and improvement, with the body of work can be divided into the following points.Firstly, the analysis of the related factors of the electric vehicle modeling, electric vehicle load forecasting model is set up, and under the different scale and charging power load forecasting curve were analyzed and compared. In this paper, we propose an improved load forecasting method, different with the traditional method, this method is through carries on the classification to forecast the load curve.From the point of view of charging time and power consumption, the results show that the method is more in line with the use of battery.Secondly, construct the optimal scheduling model of electric vehicle. The model with network load curve variance and the cost of using electricity for the minimum objective function,using multi-objective genetic algorithm, electric vehicles to 24 hours charging load were optimized, and the system of the 33 node distribution network is simulated and analyzed. The load curve under different conditions and their impact on the power grid caused. To verify the effectiveness of the proposed model and algorithm. The results show that the proposed method can optimize both user and network interests, and the method can be extended to different objective functions to go. In terms of the impact on the grid. Mainly from the voltage offset and loss angle, analyzes the voltage excursion of network loss change before and after optimization of the system and each node.Finally, charging station planning problems were discussed, charging station planning not only need to consider the constraint of charging users convenient and transportation network, also reduce due to large-scale load access to the grid with the adverse effects. This paper establishes a major consideration for electric vehicle retains the quantity of charging station planning model, also the model considered charging load caused by the offset voltage of the influence factors, to electric vehicle retains the quantity is corrected, the immune optimization algorithm for a given position and keep the amount of charging station is used to solve the problem.