A Risk-Based Gaming Framework for VPP Bidding Strategy in a Joint Energy and Regulation Market

This paper presents a risk-based game theoretic model for virtual power plant (VPP) bidding strategy in both energy and balancing markets, in the presence of conventional generation companies (GenCos) as rivals. The objective is to provide a method for finding strategic bidding of VPP comprising traditional units, wind turbine, interruptible and shiftable loads along with other strategic rivals. In this regard, a novel shifting load scheme is introduced into the VPP portfolio in which VPP is penalized based on shifting load amount and shifting load time as well. A bi-level mathematical program with equilibrium constraint (MPEC) is represented for modeling behavior of each producer in which the upper level deals with profit maximization of each strategic unit and the lower level encompasses social welfare maximization considering transmission constraints. Power transfer distribution factors are employed to model transmission constraints. The proposed bi-level problem is converted to a traceable mixed-integer linear programming problem using duality theory and Karush–Kuhn–Tucker optimization conditions. Simultaneous solution of all MPECs forms an equilibrium problem with equilibrium constraint that results in market Nash equilibrium point. Finally, information gap decision theory is employed for modeling load price uncertainty and evaluating risk of VPP decision making. The proposed model is tested on a standard IEEE-24 bus system, and the accuracy of the results is indicated.