Electricity Market-Clearing With Extreme Events

TL;DR

This paper introduces a novel market design incorporating an 'extreme reserve' to better manage power system reliability during extreme weather events, using advanced probabilistic models to optimize resource allocation and reduce costs.

Contribution

It proposes a new co-optimization framework for extreme reserve procurement using large deviation theory, and introduces a less conservative weighted chance constraint model for cost-effective extreme event preparedness.

Findings

The new market design ensures reliability during extreme events.

The LDT-WCC model reduces reserve costs compared to LDT-CC.

Numerical experiments demonstrate improved system resilience and cost efficiency.

Abstract

Extreme events jeopardize power network operations, causing beyond-design failures and massive supply interruptions. Existing market designs fail to internalize and systematically assess the risk of extreme and rare events. Efficiently maintaining the reliability of renewable-dominant power systems during extreme weather events requires co-optimizing system resources, while differentiating between large/rare and small/frequent deviations from forecast conditions. To address this gap in both research and practice, we propose managing the uncertainties associated with extreme weather events through an additional reserve service, termed extreme reserve. The procurement of extreme reserve is co-optimized with energy and regular reserve using a large deviation theory chance-constrained (LDT-CC) model, where LDT offers a mathematical framework to quantify the increased uncertainty during extreme events. To mitigate the high additional costs associated with reserve scheduling under the LDT-CC model, we also propose an LDT model based on weighted chance constraints (LDT-WCC). This model prepares the power system for extreme events at a lower cost, making it a less conservative alternative to the LDT-CC model. The proposed market design leads to a competitive equilibrium while ensuring cost recovery. Numerical experiments on an illustrative system and a modified 8-zone ISO New England system highlight the advantages of the proposed market design.