Applied Research On Electric Vehicle Virtual Energy Storage In Multi-scenes

With the increasing environmental problems,the number of electric vehicles is increasing year by year.The disorderly charging of a large number of electric vehicles is not conducive to the stability of the power grid.At the same time,electric vehicles have much idle time.Taking idle electric vehicles as energy storage to participate in auxiliary services of the power system can fully play the role of energy storage of electric vehicle power batteries and improve the stability of the power grid.Meanwhile it can also bring certain economic benefits to the grid and electric vehicles’ owners.At present,most countries have carried out research on electric vehicle virtual energy storage.However,the research on the multi-dimensional model for predicting the available capacity of electric vehicle virtual energy storage,the research on auxiliary services for electric vehicle virtual energy storage based on the prediction results,and the research on its operation model are currently problems that have not been properly solved.So,it is of great significance to study the application of electric vehicle virtual energy storage in Multi-scenes.This paper studies the application of electric vehicle virtual energy storage in Multi-scenes,and establishes an optimal scheduling model of electric vehicle virtual energy storage participating in auxiliary services in different scenarios.The main research contents are as follows:Firstly,the method for predicting the available capacity of electric vehicle virtual energy storage is studied,and a method for predicting the available capacity of electric vehicle virtual energy storage based on Markov chain is proposed.According to Markov chain theory,and the number of electric vehicles at different parking locations is predicted in 24 periods.Combined with the daily driving mileage,driving power consumption,schedulable capacity threshold,and electric vehicle efficiency,a mathematical model of the schedulable amount and schedulable power of electric vehicle virtual energy storage is established,Which provides data support for electric vehicle virtual energy storage to participate in power system auxiliary services.Secondly,the control strategy of electric vehicle virtual energy storage participating in grid-assisted peak shaving is researched,and a model of electric vehicle virtual energy storage participating in power grid-assisted peak shaving optimization scheduling based on particle swarm optimization algorithm is proposed.Aiming at minimizing load fluctuations,and taking into account constraints such as the daily mileage of the electric vehicle and the end time of travel,an optimal control model based on the electric vehicle virtual energy storage to participate in power grid peak regulation is established.Then,genetic algorithms,particle swarm optimization,and fish swarm algorithm are used to solve the model.Then,the output control strategy of the electric vehicle-supercapacitor hybrid system tracking photovoltaic plan is studied.First,a PSO-BP photovoltaic output prediction model based on principal component analysis is proposed,and the power required for the hybrid energy storage system is calculated.EEMD is used to preliminarily allocate energy to a hybrid energy storage system,and then proposed an output optimization model with the goal of minimum tracking deviation and minimum mutual compensation of two types of energy storage,and the NSGA-Ⅲ algorithm is used to solve the model to make a reasonable energy distribution for the hybrid energy storage system.Finally,the operation model of electric vehicles virtual energy storage is researched.Firstly,two different operation modes of user self-investment model and third-party investment are proposed and analyzed.Then,a mathematical model of electric vehicles virtual energy storage dominated by the grid is established.The simulation study compares two electric vehicles virtual energy storage operation modes,which has certain reference value for actual investment and decision-making.