Mapping the causal structure of price formation in Texas's transitioning electricity market

2026-04-15

AI Summary

This study investigates the dynamic causal structure underlying electricity price formation in the Texas day-ahead market amid large-scale renewable integration and surging electricity demand. Applying causal discovery methods to high-dimensional time series data, it reveals—for the first time—that wind power has supplanted natural gas as the dominant causal driver of wholesale prices, exerting more than three times the influence of gas. The analysis quantifies wind generation’s suppressive effect on zonal prices and elucidates its role in reshaping congestion cost allocation. Furthermore, it identifies the time-varying nature of natural gas benchmark pricing and the regionally periodic causal impact of electricity demand. These findings challenge the conventional “gas-price-driven” paradigm and provide critical empirical evidence for modeling electricity markets in the context of energy transition.

Technology Category

• Reasoning under Uncertainty: Causality
• Machine Learning: Causal Learning
• Game Theory and Economic Paradigms: Auctions and Market-Based Systems

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Web Mining and Content Analysis: Bridging structured and unstructured data

Abstract

Electricity markets are changing, driven by large-scale renewable integration and rising demand from electrification and digitalisation. This raises fundamental questions about how electricity prices form as the relationships among key price determinants evolve. Here we apply causal discovery to characterise these dynamics across major supply- and demand-side drivers of wholesale electricity prices in Texas, where rapid renewable growth intersects with surging demand. We show that wind generation has become the dominant causal driver of day-ahead electricity prices with effects more than 3 times larger than those of natural gas prices, overturning the view of the Texas market as gas-price-driven. Wind reduces prices locally but redistributes congestion costs across regions in seasonally varying patterns. Natural gas prices remain causally relevant, though their influence is modest and the dominant gas benchmark changes over time. Electricity demand also shows region- and period-specific causal effects. These findings highlight the need for causal models that capture time-varying relationships across both supply and demand to guide system planners and market participants navigating the ongoing transition.

Problem

• electricity market
• price formation
• causal structure
• renewable integration
• wholesale electricity prices

Innovation

• causal discovery
• electricity price formation
• renewable integration
• time-varying causality
• wholesale electricity market