| The disorderly charging behavior of large-scale electric vehicles has brought tremendous pressure on the normal operation of power grid.Based on the theory of demand-side management,this paper uses the time-of-use(TOU)price as a means to guide users to adjust their electricity consumption.Monte Carlo model is used to simulate the charging load.To achieve the central task of “load shifting and valley filling” on grid load,three coordinated charging strategies are proposed.Firstly,the coordinated charging strategy which is based on static TOU tariffs policy establishes a multi-objective optimization model.The model aims at reducing load peak-to-valley differences and minimizing user charging costs.It uses NSGA-II algorithm which is based on the Pareto multi-objective optimization.The simulation result shows that this strategy can’t coordinate the two opposed objective functions when the time division is inconsistent with the load level.At the same time,it may also lead to another peak in grid load.Therefore,the charging tariffs policy may needs to be adjusted.To solve the above problem,the charging strategy based on the improved static TOU tariffs is proposed,the load data is reclassified by membership function method.Then k-means clustering is used to test the division result.Recalculate the total distribution network load using the new partition period.The example simulation shows that the new scheme is consistent with the load fluctuation level,basically achieve the goal that using the coordinated charging strategy to make the fluctuation of the load stabilized.The last strategy is only for specific distribution networks.Considering different regions have different load diagrams,a new coordinated charging method based on dynamic TOU tariffs is proposed.This strategy does not rely on the fixed TOU period.Instead,it is based on the load margin at the current moment,and it can be autonomously responded by the users.In the end,the operation effects of each strategy are compared and analyzed.The dynamic strategy is the better than any other scheme in reducing peak-to-valley differences and tying load fluctuations.What’s more,this strategy does not fix the price period,which improves the adaptability to the changing load.It will have a positive effect on guiding users to change their power consumption patterns and achieving a win-win situation between the power grid and electric vehicle users. |
