Optimizing Bidding Curves for Renewable Energy in Two-Settlement Electricity Markets
Dongwei Zhao, Stefanos Delikaraogloub, Vladimir Dvorkin Alberto J. Lamadrid L., Audun Botterud
TL;DR
The paper tackles the challenge of coordinating day-ahead and real-time dispatch in two-settlement electricity markets under high variable renewable energy (VRE) penetration by optimizing day-ahead VRE bidding curves within a bilevel framework that anticipates real-time redispatch costs. It formulates the BiD problem, where the upper level selects VRE bid prices and quantities and the lower level solves the DAM and scenario-based RTM, aiming to minimize the total expected cost $S^{\text{BiD}} = f_0^{\text{DA}}(\Phi^{\text{DA}\star}) + \mathbb{E}_\omega[f_\omega^{\text{RT}}(\Phi_\omega^{\text{RT}},\Phi_\omega^{\text{DA}\star})]$. A key theoretical result shows that a single-segment zero-price VRE bid suffices to achieve system-optimality when VRE marginal cost is zero, and an LP-based relaxation using strong duality and McCormick envelopes enables scalable solution to large networks such as the 1576-bus NYISO system. Case studies indicate that BiD reduces expected dispatch costs compared with a baseline wind-forecast bidding strategy and closely approaches the stochastic optimum, with multi-segment bidding offering further gains. Overall, the framework provides practical guidance for market design and potential regulatory tools to shape VRE bidding strategies in two-settlement markets.
Abstract
Coordination of day-ahead and real-time electricity markets is imperative for cost-effective electricity supply and also to provide efficient incentives for the energy transition. Although stochastic market designs feature the least-cost coordination, they are incompatible with current deterministic markets. This paper proposes a new approach for compatible coordination in two-settlement markets based on benchmark bidding curves for variable renewable energy. These curves are optimized based on a bilevel optimization problem, anticipating per-scenario responses of deterministic market-clearing problems and ultimately minimizing the expected cost across day-ahead and real-time markets. Although the general bilevel model is challenging to solve, we theoretically prove that a single-segment bidding curve with a zero bidding price is sufficient to achieve system optimality if the marginal cost of variable renewable energy is zero, thus addressing the computational challenge. In practice, variable renewable energy producers can be allowed to bid multi-segment curves with non-zero prices. We test the bilevel framework for both single- and multiple-segment bidding curves under the assumption of fixed bidding prices. We leverage duality theory and McCormick envelopes to derive the linear programming approximation of the bilevel problem, which scales to practical systems such as a 1576-bus NYISO system. We benchmark the proposed coordination and find absolute dominance over the baseline solution, which assumes that renewables agnostically bid their expected forecasts. We also demonstrate that our proposed scheme provides a good approximation of the least-cost, yet unattainable in practice, stochastic market outcome.