Research Of Energy Allocation Strategy And Pricing Mechanism Based On Hybrid Electric Vehicle

Environmental pollution problem has become one of the important problems that restrict the healthy development of economy and society,therefore to promote the reformation of energy structure and improve energy effciency is one of the important developing directions of future smart grid. As a supplement of centralized power generation, distributed renewable energy sources play an important role of creating a greener energy structure. At the same time, the appearance of smart demand loads,take hybrid electric vehicles(HEV) as an example, have changed the rigid character of traditional loads and bring up some new ideas for power system operation. Based on the above discussion, we focus on the following three challenging works.According to the character of electricity market, we propose a double auction method to help the virtual power plant to get its optimal trading strategy in the dayahead market and classify the hybrid electric vehicles into different types according to their toleration delay time. Then based on the results of the auction and the random character of renewable energy sources, we give the energy dispatch strategy for hybrid electric vehicles while satisfying the delay time constraints.We propose a two-level game approach to describe the dynamic competition relationship between hybrid electric vehicles and charging stations. We use evolutionary game and replicate dynamics to depict the charging station selection process for the vehicles in the lower level and apply differential game to help charging stations in the upper level to set their optimal charging prices. Then we analyse the existence and uniqueness of the equilibrium for the two-level game.Then we study a real-time payoff maximization problem for the aggregator in a dynamic aggregator-HEV system. The aggregator will establish an equivalent fuel cost after studying the electricity-only driving mode of the hybrid electric vehicles. Then based on the equivalent fuel cost price, the aggregator will set a pricing constraint to convert the electricity gas proportion problem into whether choose to trade energy with the aggregator. We apply the Lyapunov optimization framework to decompose the original problem into the charging price decision problem and energy allocation problem and propose an algorithm that do not need statistical information to solve the two subproblems. Then we validate the effectiveness of our algorithm through simulation results.