Study On Charging Time Choice Behavior Of Electric Taxi Drivers Under Time-of-use Electricity Price

Now,commercial operations of electric taxis have begun in many Chinese cities,with the encourage of government active policies,the number of electric taxis will be quite huge in future,as a result,the charging peak generated by centralized charging will become more and more obvious.Time-of-use(TOU)electricity price as a means of economic stimulation can induce users to charge at non-peak hours,with reasonable TOU price,the charging peak can be transferred and the negative impact caused by charging peak can also be reduced.In order to provide a reference for the formulation of TOU tariff policy,this paper studies the charging time choice behavior of electric taxi drivers under TOU price.Firstly,the charging data of electric taxis are statistically analyzed,it is found that there exists obvious regularity in the charging start time and charging duration in the 14:30～19:30 period,using the Gaussian function to fit the data,the probability density functions of the charging start time and charging duration are obtained respectively.The Monte Carlo method is used to simulate the charging load of this time period,the result shows that the centralized charging behavior before the shift will have a certain impact on the operation of power grid,with the analysis of other impacts brought by centralized charging behavior,it is concluded that it is necessary to implement the TOU tariff policy to guide taxi drivers’ charging behavior.Secondly,using orthogonal design method to generate stated preference(SP)questionnaire,according to the collected preference data,a multinomial logit model and a nested logit model were developed and NLOGIT5.0 software was used to solve the models,the model parameter significance test and model goodness test show that the multinomial logit model is more reasonable for studying taxi drivers’ charging choice behavior.By analyzing the parameter calibration results,it is found that taxi drivers expect to recharge at low price hours with the smallest time changing,compared to charging earlier than usual,taxi drivers have a lower preference for charging later than usual.Thirdly,elasticity approach was used to analyze continuous significant variables,the results show that price increase has been the most concern factor of taxi drivers and it has the biggest influence on drivers’"charge as usual" decision,when the driver considers whether or not to charge later than usual,their behavior will be affected by the delayed time.Marginal method was also used to analyze the discrete variable,it is concluded that for different charging peak periods,even if TOU tariff policy is the same,the drivers will respond differently.Finally,several combinations of TOU tariff were set to do what-if analysis,it is found that even with the same electricity price difference,taxi drivers will have different response for different combinations of price increases,and that compared to reducing electricity price at non-peak hours,raising the price at peak hours may have a better effect on the shift of charging peak.