Research On Double-layerb Optimal Scheduling Of EV And New Energy Generation In V2G Mode

At present,the world is faced with many precipitous problems,such as climate warming,climate change,the worsening energy crisis,the deterioration of the natural environment,and the depletion of resources.Due to the economic and environmental characteristics of electric vehicles and new energy,their research changes with each passing day and is widely popularized.But the influx of EVs,or electric vehicles,into the grid will have an impact.The disordered charging and discharging of electric vehicles will seriously affect the stability of system load and increase the peak-valley load difference.In addition,the random fluctuation of new energy will interfere with the safe and stable operation of the distribution network.V2G mode,namely Vehicle-to-grid,aims to realize bidirectional power flow between EV and distribution network.On the one hand,orderly charge-discharge scheduling strategy is used to alleviate the load peak problem when a large number of EV enters the network.On the other hand,users can realize their own benefits through discharge.In this study,a double-layer optimal scheduling strategy of EV and new energy generation under V2G mode is proposed to deal with the problem of how to fully tap the flexible resources on both sides of supply and demand to take into account the low-carbon and economic operation of the distribution network.First of all,EV can be effectively controlled by centralized regulation and grid-connection of EV due to its characteristics of easy dispersion,large load and small capacity.After in-depth analysis,the author selected 200 electric private cars equipped with lithium-ion batteries to explore EV driving characteristics by conventional centralized charging and discharging mode.Monte Carlo simulation method can simulate the adverse effects of unordered charging of electric vehicles on the power grid.It is found that disorderly charging of electric vehicles will lead to changes in the peak value and average value of system load,resulting in "peak on peak".In order to eliminate the above adverse effects,an intelligent distribution network based on V2G mode is proposed.Intelligent distribution network uses reasonable time-of-use electricity price to guide EV users to carry out orderly charging and discharging behavior with the lowest cost as the goal,and also guides the optimization of two kinds of flexible loads,such as reduced load and transferable load.Through power balance,flexible load and EV power constraints,the net total load after "peak cutting and valley filling" at load side is obtained.Next,the authors model the source-side distributed energy sources that provide the electricity.The mathematical model includes: wind power generation,photovoltaic power generation,EV energy storage battery discharge,diesel generator set,gas turbine set,and main network purchasing power.The net total load demand on the load side constrains the power supply requirement on the source side to realize the load determination of the source.The multi-period optimization of source side new energy is carried out with the goal of minimum operation cost and minimum carbon emission.The source-side model is constrained by power balance,output of all new energy sources,remaining electric capacity of EV batteries,and node power flow voltage and current.The two-layer optimal scheduling model is composed of the energy balance interaction on both sides of the source and load.Finally,this paper introduces the solution of the model.The author simulated the model in a cycle of 24 h on the MATLAB platform.In the upper model,particle swarm optimization algorithm is used to solve the load curve under the minimum economic cost.The lower model is solved by NSGA-Ⅱ algorithm to achieve the goal of economy and low carbon at the source side,and is simulated by IEEE33-node distribution system.The optimal compromise solution of the two-level strategy model is obtained by solving the upper and lower model.By comparing the simulation results of this study with the schemes provided in the references,the author verifies that this study plays a positive role in stabilizing load fluctuation and improving the low-carbon economic operation on both sides of the source load of the distribution network.The above studies indicate that this strategy can serve as a reference for establishing effective scheduling schemes and response strategies when EV and new energy generation are connected to the distribution network under V2G mode in the future.