Scheduling And Simulation Of Vehicular Power Cloud Based On V2G

As people gradually attach great importance to the problem of ecological environment,Electric vehicle(EV)attracts more and more attention because of its advantages of energy conservation,Low-Carbon,and low noise.However,random and disorder charge of large-scale electric vehicle have caused a significant impact that can not neglected.V2G(Vehicle to Grid)is the result of the increasing contradiction between the rising demand and the limited energy.V2 G achieve the two-way interaction of energy and information between EV and grid,EV can feed back to the power grid when they are idle,thesis focuses on the study of V2 G.Energy Internet promotes the development of the energy world,the randomness and uncertainty of the new energy makes distributed energy storage become one of the basic technologies of Energy Internet.Under the link of V2 G,EV in the electrified transportation system will become an important part of the Energy Internet.The vehicle batteries of V2 G composed a distributed storage system,which will become a vital part of Energy Internet.The dispersal electric vehicle of V2 G has lots in common with the distributed resources of cloud computing.And Combined with the energy Internet's connotation of “applying the idea and technology of the Internet to the energy systems”,the author puts forward the concept of vehicular power cloud,and analyzes the properties of vehicle power resources from the perspective of access,capacity and cost,then analyzes the characteristics and difficulties of electric vehicle cloud scheduling.The concept of vehicular power cloud is the foundation of the succeed contents.In order to solve the complex and multiple-constrained problem of electric vehicle cloud scheduling,thesis proposes an optimal algorithm fits for that kind of problem.Based on the limitation of particle swarm algorithm,an improved particle swarm optimization(IPSO)algorithm is designed based on the variance of population fitness,and its correctness and validity are tested.Inspired by the application of Membrane optimization algorithm in cloud computing,the author puts forward the Modified Particle Swarm Optimization based P Systems(MPSOPS).By combining the existing optimization algorithm with the membrane computing,the convergence speed and the optimization precision of the optimization process have been greatly improved by MPSOPS.Finally,in order to emulate the relevant scene and verify the scheduling algorithm,the author and the member of the related project build a co-simulation platform: V2 Gsimulator.The author is in the charge of designing a joint simulation architecture involving domains of power,communication and transportation.And the author is responsible for the design and programming of layered multi-module of node,system event mechanism and message communication.At last,some ceses are simulated on V2 Gsimulator to verify the feasibility and performance of the proposed algorithm.