Bidding Strategy for Virtual Power Plant With Intraday Demand Response Exchange Market Using Stochastic Programming

This paper presents a mathematical model for the energy bidding problem of a virtual power plant (VPP) that participates in the regular electricity market and intraday demand response exchange (DRX) market considering different system uncertainties due to the intermittent renewable energy sources, retail customers' demand and electricity prices. By participating in the DRX market, the VPP can purchase demand response (DR) services from several demand response providers (DRP) as "virtual energy resources" to reduce the penalty cost of energy bidding mismatch in the energy market, increase its profit, and improve its renewable energy utilization significantly. The overall energy bidding problem is modeled as a three-stage stochastic program, which can be solved efficiently by the scenario based optimization approach. Extensive numerical results show the positive impact of DRX market on VPP's energy management and effectiveness of the proposed optimization framework.