Stochastic programming based model of an electricity retailer considering uncertainty associated with electric vehicle charging

In this paper, a mathematical model is proposed for optimization of the portfolio of an electricity retailer in the forward and spot markets considering flexibility offered by electric vehicles (EV). The model provides a guideline to the electricity retailer for aggregated scheduling of EV battery charging, contracting of power in the forward market and setting of retail prices for customers under fixed and variable price electricity retail contracts. The objective of the model is to maximize the retailer's expected profit. A stochastic programming approach is used to account for the uncertainties associated with spot price, customers' demand and EV demand. The model is applied to a case study using data from the Nordic electricity markets, future scenarios for EVs in Sweden and an electricity retailer in Sweden. Results indicate that cost savings from flexibility of EV demand would increase with increasing EV penetration level and the number of customers with variable price contracts as opposed to fixed price contracts. It is also found that the retailer's expected profits would increase with a greater share of variable price contracts.

[1]  Stanislav Uryasev,et al.  Conditional Value-at-Risk for General Loss Distributions , 2002 .

[2]  G. Sheblé,et al.  Price and volume risk management for power producers , 2005, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[3]  A. Salo,et al.  Optimization of Electricity Retailer's Contract Portfolio Subject to Risk Preferences , 2010, IEEE Transactions on Power Systems.

[4]  Filipe Joel Soares,et al.  Integration of Electric Vehicles in the Electric Power System , 2011, Proceedings of the IEEE.

[5]  Bohn Stafleu van Loghum,et al.  Online … , 2002, LOG IN.

[6]  R. Rockafellar,et al.  Conditional Value-at-Risk for General Loss Distributions , 2001 .

[7]  Richard E. Rosenthal,et al.  GAMS -- A User's Guide , 2004 .

[8]  Willett Kempton,et al.  Using fleets of electric-drive vehicles for grid support , 2007 .

[9]  M. Carrion,et al.  Forward Contracting and Selling Price Determination for a Retailer , 2007, IEEE Transactions on Power Systems.

[10]  Manuel A. Matos,et al.  Models for the EV aggregation agent business , 2011, 2011 IEEE Trondheim PowerTech.

[11]  Le Anh Tuan,et al.  Effects of plug-in electric vehicle charge scheduling on the day-ahead electricity market price , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).