Sharing the Shortfall: Algorithmic Solutions for Fair Demand Curtailment in Zonal Power Markets

Abstract

The transition to renewable energy sources introduces volatility in supply and pricing, which increases the need for robust transmission networks and large electricity market pools. These markets, managed by multiple system operators, rely on central algorithms to balance supply and demand. In situations where supply cannot meet demand, involuntary demand curtailment becomes necessary. In zonal markets with flow-based constraints and uneven zone sizes, curtailment often disproportionately affects smaller zones. This paper evaluates alternative "adequacy patches"—rules for more equitable curtailment allocation—ranging from utilitarian to Rawlsian strategies, and assesses their impact on zonal resource adequacy, marketplace stability, and algorithmic complexity.Through theoretical approaches and simulated outcomes, we show that traditional minimization strategies disproportionately curtail demand in smaller zones, while alternative strategies, although resulting in higher overall curtailment volumes, offer more equitable solutions. The findings emphasize the importance of fair, predictable, and robust curtailment rules for maintaining trust and stability in interconnected electricity markets. These rules are critical for resource adequacy and instruments like Capacity Remuneration Mechanisms (CRMs).

Keywords: Resource AdequacyDemand CurtailmentElectricity Market Design