Incorporating financial entities into spot electricity market with renewable energy via holistic risk-aware bilevel optimization

Financial entities' integration into renewable energy-rich electricity markets via virtual bidding introduces liquidity benefits but might amplify systemic risks due to their risk-driven strategies. This study develops a holistic risk-aware bi-level optimization framework to analyze their impact: the upper level optimizes virtual bids using a multi-criteria objective, including expected profit, Conditional Value-at-Risk, and Value at Best to model risk-averse, neutral, and seeking behaviors, while the lower level simulates day-ahead (DA) real-time (RT) market clearing under renewable uncertainty. This bilevel model could enable a comprehensive analysis of the impacts of various risk-aware financial entities' bidding strategies, especially aggressive bidding strategies, on both DA and RT electricity market clearing processes, which has been overlooked in most relevant research. Case studies reveal that aggressive strategies increase volatility but enhance liquidity, while risk-averse approaches stabilize prices but reduce arbitrage. Higher renewable penetration exacerbates price fluctuations, yet financial entities can mitigate this through risk-calibrated bidding. A critical bid capacity threshold emerges, beyond which marginal returns diminish and price spreads stabilize, suggesting regulatory caps to curb speculation. Results demonstrate trade-offs between market efficiency, risk exposure, and renewable integration, with moderate risk aversion optimizing risk-adjusted returns. The framework provides policymakers with tools to design adaptive market rules and helps participants align bidding strategies with grid dynamics. By unifying risk-aware decision-making, renewable uncertainty, and market design, this work bridges a critical gap in managing profitability and stability during the energy transition.