A real-time demand response market through a repeated incomplete-information game

Abstract

Demand Response (DR) programs have been developed to help traditional power market to meet demand specially with increasing penetrations of renewable energies. This paper focuses on application of a game-theoretic framework to model competition between demand response aggregators to sell aggregated energy stored in storage devices directly to other aggregators in a market. This proposed market is cleared in each time interval of a day using a repeated game-theoretic framework. After finding optimal bidding strategies of the aggregators in each time interval, Dynamic Economic Dispatch (DED) is performed to update the dispatch of generators based on updated demand. Dynamic pricing has been considered in the proposed market framework in two forms: Real-Time Pricing (RTP) in each time interval of a day with updating demand and supply and Time-of-Use (TOU) with demand price-based scheduling through dynamic programing. The proposed method minimizes the fuel consumption and operation costs and optimally schedules the generation in grid's supply side. It also presents optimal prices during different periods simultaneously. Customers in light of the utility's optimal price minimize theirs electricity costs and optimally schedule their power consumption in order to participate in the DR market. The presented model is applied to IEEE 24-bus model.