EVS 24 Stavanger , Norway , May 13-16 , 2009 Analysis of the Impact of Plug-In Hybrid Electric Vehicles on Residential Distribution Grids by using Quadratic and Dynamic Programming

The charging of batteries of plug-in hybrid electric vehicles at home at standard outlets has an impact on the distribution grid which may require serious investments in grid expansion. The coordination of the charging gives an improvement of the grid exploitation in terms of reduced power losses and voltage deviations with respect to uncoordinated charging. The vehicles must be dispatchable to achieve the most efficient solution. As the exact forecasting of household loads is not possible, stochastic programming is introduced. Two main techniques are analyzed in this paper: quadratic and dynamic programming. Both techniques are compared in results and storage requirements. The charging can be coordinated directly or indirectly by the grid utility or an aggregator who will sell the aggregated demand of PHEVs at the utility. PHEVs can also discharge and so inject energy in the grid to restrict voltage drops. The amount of energy that is injected in the grid depends on the price tariffs, the charging and discharging efficiencies and the battery energy content. The impact of a voltage controller embedded in a PHEV charger is regarded in this paper. A day and night tariff are applied. The charging and discharging of vehicles can respond to real-time pricing or on a price-schedule as well. Voltage control is the first step in the utilization of distributed resources like PHEVs for ancillary services.

[1]  Sten Karlsson,et al.  World Electric Vehicle Journal , 2016 .

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

[3]  A. Emadi,et al.  Plug-in hybrid electric vehicle developments in the US: Trends, barriers, and economic feasibility , 2008, 2008 IEEE Vehicle Power and Propulsion Conference.

[4]  M. Ferdowsi,et al.  Utilization and effect of plug-in hybrid electric vehicles in the United States power grid , 2008, 2008 IEEE Vehicle Power and Propulsion Conference.

[5]  Xiaolong Yu,et al.  Impacts assessment of PHEV charge profiles on generation expansion using national energy modeling system , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[6]  Johan Driesen,et al.  Robust planning methodology for integration of stochastic generators in distribution grids , 2007 .

[7]  Johan Driesen,et al.  The consumption of electrical energy of plug-in hybrid electric vehicles in Belgium , 2007 .

[8]  Environmental Assessment of Plug-In Hybrid Electric Vehicles Volume 1 : Nationwide Greenhouse Gas Emissions , 2007 .

[9]  Alexander Shapiro,et al.  The empirical behavior of sampling methods for stochastic programming , 2006, Ann. Oper. Res..

[10]  Willett Kempton,et al.  Vehicle-to-grid power implementation: From stabilizing the grid to supporting large-scale renewable energy , 2005 .

[11]  Willett Kempton,et al.  Vehicle-to-grid power fundamentals: Calculating capacity and net revenue , 2005 .

[12]  Menahem Anderman,et al.  The challenge to fulfill electrical power requirements of advanced vehicles , 2004 .

[13]  John W. Labadie,et al.  Optimal Operation of Multireservoir Systems: State-of-the-Art Review , 2004 .

[14]  John W. Labadie,et al.  Dynamic Optimal Unit Commitment and Loading in Hydropower Systems , 2003 .

[15]  W. H. Kersting,et al.  Radial distribution test feeders , 1991, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[16]  Richard Bellman,et al.  Adaptive Control Processes: A Guided Tour , 1961, The Mathematical Gazette.