Excitation Methods for EV Charging Process in Community Considering the Degree of User Response

There are still deficiencies in the research on the optimal control strategy of electric vehicle (EV) charging process. In order to perfect this hot issue, this paper introduces the excitation methods for EV charging process in community considering the degree of user response. The mathematical models of charging process of EVs are firstly established. Then the effect of time-of-use (TOU) power price excitation method is mathematically analyzed. At last, the TOU power price excitation method considering degree of user response is presented. The mainly used method to get the solution is Monte-Carlo method. Comparisons are made to validate the method proposed in this paper.

[1]  Peter Palensky,et al.  Modeling Intelligent Energy Systems: Co-Simulation Platform for Validating Flexible-Demand EV Charging Management , 2013, IEEE Transactions on Smart Grid.

[2]  Jie Zhang,et al.  Optimization of Ordered Charging Strategy for Large Scale Electric Vehicles Based on Quadratic Clustering , 2017, 2017 4th International Conference on Information Science and Control Engineering (ICISCE).

[3]  M. Eissa Demand side management program evaluation based on industrial and commercial field data , 2011 .

[4]  J. Driesen,et al.  The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid , 2010, IEEE Transactions on Power Systems.

[5]  Liu Lin Research on Scheme for Ordered Charging of Electric Vehicles , 2012 .

[6]  Chris Develder,et al.  Quantifying flexibility in EV charging as DR potential: Analysis of two real-world data sets , 2016, 2016 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[7]  Na Yu,et al.  Optimal TOU Decision Considering Demand Response Model , 2006, 2006 International Conference on Power System Technology.

[8]  Saifur Rahman,et al.  Grid Integration of Electric Vehicles and Demand Response With Customer Choice , 2012, IEEE Transactions on Smart Grid.

[9]  Hong Liu,et al.  Optimization of TOU price of electricity based on Electric Vehicle orderly charge , 2013, 2013 IEEE Power & Energy Society General Meeting.

[10]  Yudong Tang,et al.  Investigation on TOU pricing principles , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

[11]  João P. S. Catalão,et al.  Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR , 2015, IEEE Transactions on Smart Grid.

[12]  Wei Chen,et al.  A survey of influence of electrics vehicle charging on power grid , 2014, 2014 9th IEEE Conference on Industrial Electronics and Applications.

[13]  Qi Huang,et al.  A coordinated charging strategy for electric vehicles based on multi-objective optimization , 2017, 2017 2nd International Conference on Power and Renewable Energy (ICPRE).

[14]  Yue Yuan,et al.  Load model for prediction of electric vehicle charging demand , 2010, 2010 International Conference on Power System Technology.

[15]  Canbing Li,et al.  An Optimized EV Charging Model Considering TOU Price and SOC Curve , 2012, IEEE Transactions on Smart Grid.

[16]  Florian Mauser,et al.  Trends in vehicle concept and key technology development for hybrid and battery electric vehicles , 2013, 2013 World Electric Vehicle Symposium and Exhibition (EVS27).