Option-Backed Reverse Auctions for High-Uncertainty Procurement (BECCS, DERs)

Fridahl et al. (2024) document four design dilemmas in Sweden’s BECCS reverse auctions: winner’s curse fears, marginal allocation cost inflation, compliance design, and integration with voluntary carbon markets. We propose a two-stage mechanism: (i) a primary reverse auction yielding provisional awards with embedded compliance options (rights/obligations tied to verifiable milestones), and (ii) a secondary options market linking penalties/bonuses to exogenous carbon prices and realized performance. The scoring rule blends price with a risk-adjusted deliverability index estimated online via bandit learning (echoing the OL-IDA approach in Wu & Liao, 2025, and the learning framing in Zhao et al., 2021). Traders can hedge compliance risk by trading options contingent on milestone verification, reducing the winner’s curse while giving the buyer credible enforcement without blunt penalties. This differs from standard pay-for-performance procurement by making compliance risk tradable and discovered in a market, which also clarifies whether and how to integrate with voluntary carbon markets. Beyond BECCS, the same design suits inter-microgrid procurement (Esfahani et al., 2018) and other DER auctions where technology trajectories and verification costs dominate.

References:

1. Market Design for Task Offloading under Information Asymmetry and System Uncertainty. Yifei Wu, Guocheng Liao (2025). 2025 International Conference on Sensor-Cloud and Edge Computing System (SCECS).
2. Potential and goal conflicts in reverse auction design for bioenergy with carbon capture and storage (BECCS). Mathias Fridahl, Kenneth Möllersten, Liv Lundberg, Wilfried Rickels (2024). Environmental Sciences Europe.
3. Game-theory-based Real-Time Inter-Microgrid Market Design Using Hierarchical Optimization Algorithm. M. M. Esfahani, A. Hariri, O. Mohammed (2018). IEEE Power & Energy Society General Meeting.
4. Auction Design through Multi-Agent Learning in Peer-to-Peer Energy Trading. Zibo Zhao, Chengzhi Feng, Andrew L. Lu (2021). arXiv.org.