Equilibrium Analysis Incorporating Risk-Seeking Virtual Bidders in Electricity Market Considering Wind Power Generation

This paper addresses the operational risks faced by wind power producers (WPPs) in electricity markets, primarily caused by real-time (RT) price volatility and wind power output fluctuation. We analyze how risk-seeking virtual bidders (VBers) influence WPPs' expected profits and risks in the DA market. A day-ahead (DA) market equilibrium model is developed, incorporating the risk management of both VBers and WPPs. Mean-standard deviation (M-S) model is adopted for VBers' risk management, while conditional value-at-risk (CVaR) quantifies the risks faced by WPPs. Scenario generation and reduction method, combined with scenario tree method, are employed to obtain the joint distribution of forecasted wind speed and RT market prices. The model is solved by nonlinear complementarity method and the Levenberg-Marquardt (L-M) algorithm. Case studies demonstrate that the introduction of risk-seeking VBers enhances WPP's profits during higher forecasted RT price time periods and reduces WPP's risks during lower forecasted RT price time periods.