Research On Electric Vehicle Charging Scheduling Based On Backpack Algorithms

Large-scale electric vehicles are disorderly charged.Without reasonable guidance and scheduling,the load peak-to-valley difference will increase,causing the phenomenon of “peaking on the peak”,increasing line loss,affecting the safe and stable operation of the power grid.Therefore,rationally scheduling the charging behavior of electric vehicles is crucial for improving the peak-to-valley difference of the charging system,stabilizing the load fluctuations,and reducing the users' charging cost.The specific research contents are as follows:1)Modeling the charging load of electric vehicles,and construct a charging load model for a single electric vehicle,and propose a method for calculating the total load of multiple electric vehicles.The disordered charging load is simulated by Monte Carlo method.The results show that under the disordered charging mode,the load peak-to-valley difference of the charging system increases and the load fluctuation increases.2)Aiming at the 24-hour time span,the feasibility of time-of-use electricity price is analyzed,and the pricing strategy of time-of-use electricity price is proposed.Based on BP neural network,the time-of-use electricity price is predicted to provide users with the trend of electricity price change,which encourages electric vehicle users to choose the charging period reasonably,and also provides the basis of electricity price for the electricity price criterion in the knapsack algorithm.Simulation experiments show that the time-of-use electricity price is more conducive to the purpose of charge scheduling than the ladder electricity price.3)Aiming at the charging scheduling of single residential area and multiple residential areas,a charging algorithm based on knapsack algorithm is proposed,and an improved charging scheduling architecture is built,and an optimal scheduling model is established.The value of charging level is set to the electric vehicle by the aggregating level function,and the greedy-select characteristic of the knapsack algorithm is used to obtain the charging priority of electric vehicle.The experimental results show that the charging scheduling strategy reduces the load peak-to-valley difference and the load fluctuation,and improves the load utilization of the charging system and the economics of the power system,and reduces the users' charging cost.