| With the breakthrough of key technologies,the battery energy storage system(BESS)is becoming more and more widely used in the power system.And BESS is playing a more and more important role in shaving peak and filling valley,improving the load characteristics and improving the economy.On the other hand,electric vehicles are connected to the power system on a large scale.Their fluctuation,intermittent and other load characteristics have a negative impact on the distribution network.And as the load permeability of electric vehicles is increasing,the negative impact will become more and more obvious.One of the effective measures to improve the load characteristics of electric vehicles is by using BESS.In view of the above situation,the bus fast charging station containing BESS was taken as the research object,and the energy management control strategy of BESS was studied to solve the real-time online energy dispatch problem of fast charging station in this paper.And the aim of the strategy was to improve the load characteristic and economy of fast charging station.The strategy was divided into day-ahead strategy and real-time strategy.In chapter 2,the measured data of a fast charging station in Beijing was analyzed,and the main characteristics of the charging load were obtained.On this basis,the day-ahead energy management control strategy of bus fast charging station was studied,the purpose of this control strategy was to provide the load tracking curve in real-time online scheduling for the next day.The optimization model was established based on the optimization target of minimum purchase cost and constraint condition of reducing peak load.The effectiveness and feasibility of the strategy was verified by an example simulation.In chapter 3,three real-time energy management control strategies were studied.The first control strategy was the real-time control strategy by directly tracking target curve.The control strategy took into account the current load,and combined energy storage capacity and power constraints.On this basis,the control strategy was improved by considering the life of energy storage,and second control strategy and third control strategy were obtained.The second and third control strategies adopted the model predictive control method with the the core idea of "online rolling optimization",and combined with state space prediction model.The difference was that the second control strategy was aim to minimize the throughput of BESS,and the third control strategy was aim to minimize the fluctuation range of SOC.In chapter 4,three real-time energy management control strategies were example simulated.And there wre there example scenarios whose prediction accuracy rate were 100%,87.27%and 82.57%.The simulation results were analyzed from three aspects:improving the load characteristic,optimizing the use effect of energy storage and improving the economy of fast charging station.Compared with the first control strategy,two improved real-time control strategies had been improved,and the purpose of improving the control strategy was achieved.The two improved real-time control strategies were suitable for different scenarios,the throughput of BESS of second strategy was lowest,so it has the best effect of prolonging the life of BESS;the third strategy had the lowest fluctuation of SOC,which had the largest remaining energy margin and the best effect of improving the load characteristics.In chapter 5,according to the above study,the software of the intelligent micro grid data monitoring system and the energy management system were presented based on the hybrid programming technology of MATLAB and C#in the intelligent micro grid platform of Beijing Jiaotong University.The experiment proved that the control strategy can be applied to real-time online control,the real time characteristic and stability of the software. |
PDF Full Text Request