Determination of Stochastic Based Medium-term Strategy for an Electricity Retailer Considering Uncertainty Associated with Electric Vehicles

This paper proposes a novel decision makingframework for an electricity retailer that procures its electricpower in a competitive electricity market. The operationalframework is a medium-term programming model in whichthe retailer determines selling price offered based oncompetitive time-of-use (TOU) rates to the consumers andamount of power that should be purchased from bilateralcontracts and pool market. These decisions are made onemonth prior to real-time market. Moreover, the risks aremeasured using conditional value at risk (CVaR) methodology.The reaction of the consumers to the retailer’s selling prices aswell as the competition between retailers is modeled through aprice-quota curve. The objective is to maximize the profit andsimultaneously to minimize the risks in terms of a multi-periodrisk measure. Due to the volatility of pool price anduncertainties associated with the conventional consumers andEVs demand, the medium-term program is a mixed integernonlinear stochastic optimization problem; Finally, a casestudy is presented in order to show the capability and accuracyof the proposed framework.

Keywords:

Pool , Bilateral , Risk Measure , Electric vehicle , Retailer , Stochastic programming