Research On Electric Vehicle Optimal Charging-Discharging Strategy Considering Multi-profile Interest

As the important parts of electric vehicle charging-discharging system, grid?electric vehicle user and service provider are correlate but antagonistic to each other. This paper conducts a systematic research on the electric vehicle intelligent charging-discharging strategy.In order to meet the practical value of electric vehicle dispatch, from user profile, chapter 2 adequately takes the electric vehicle users' driving demand into consideration, defines the users' satisfaction the combination between charging-discharging cost and reasonability, and puts forward the electric vehicle optimus charging-discharging tactics in terms of the users' satisfaction maximization, with combination of the battery cost. On this base, this chapter discusses the different users' satisfaction pattern under different weight combinations. Through Particle Swarm Optimization, the simulation result in MATLAB can verify that users' satisfaction maximization can be realized by the tactics put forward in this chapter, under different patterns, meanwhile, the tactics under all of the patterns will not arouse serious effects on the existing urban electric distribution network.The charge-discharge dispatch problem for a large scale of electric vehicles is relevant not only to electric grid's secure and stable operation, but also to the providers' economic profits and users' feel. Chapter 3 creatively and reasonably introduces the delaminating-districting scheduling concept, establishes a two-layer electric vehicle smart charge-discharge model, based on bi-level programming, and realizes the simulation verification in MATLAB through Particle Swarm Optimization(PSO) and sequential selection method within the IEEE16 node standard test system. In the up-layer model, providers' profit maximization is ensured, and the charge-discharge activities' effects on grid is reasonably evaded, through the gross charge-discharge power optimization to every precinct at every time interval. In the down-layer model, the scheduling scheme of down-layer mode is brought into correspondence with the gross district charge-discharge power of up-layer model as far as possible, and the users' satisfaction is reasonably taken into consideration, through optimization for the concrete charge-discharge tactics of the electric vehicles in every district. At last, the coordination among the provider's, grid's and user's interest are realized, through the data interaction between the two layers.The optimization dispatch problem for the access of a large scale of electric vehicles is an optimal flow problem. It is relevant not only to the providers' economic profits, but the electric grid's security and stability, and users' randomness. Chapter 4 creatively and reasonably introduces the delaminating-districting scheduling concept, establishes a three-layer electric vehicle smart charge-discharge tactic, based on multi-level programming and space-time distribution, and realizes the simulation demonstration in MATLAB through Particle Swarm Optimization(PSO) and classical flow calculation based on the IEEE16 node standard test system, within the given network structure and parameters. In the up-layer model, this chapter sets the providers' profit maximization as objective function, optimizes the comprehensive charge-discharge power of each district at each time interval, and realizes the time-scale optimization; In the mid-layer model, the relevant variables to power quality and its function are set as objective function, and space-scale optimization is realized; In the down-layer model, through the time-of-use electricity price and incentive mechanism, this chapter realizes the practical dispatch result's maximal uniformity with the space-time optimal tactics. At last, the optimal coordination among the provider's, grid's and user's interest is realized, through the data transmission and feedback among the three layers.