Virtual Trading in Multi-Settlement Electricity Markets

2025-08-16

AI Summary

This paper investigates how virtual trading—arbitrage based on price differentials without physical delivery—affects efficiency in multi-settlement electricity markets. Method: Employing a supply-function equilibrium model calibrated with real-world data from the California and New York ISOs, the study conducts empirical analysis of market outcomes. Contribution/Results: While virtual trading significantly narrows or eliminates the day-ahead–real-time price spread, enhancing price efficiency, it systematically reduces day-ahead cleared energy below actual load requirements, exacerbating energy mismatch. This stems from load-serving entities strategically lowering bids to mitigate arbitrage pressure, inducing a novel equilibrium mechanism. Crucially, this mechanism reveals that virtual trading cannot endogenously correct supply–demand imbalances and particularly impairs system flexibility for renewable generation integration. The study challenges the conventional assumption that price convergence implies market efficiency, and—first to our knowledge—identifies and empirically validates the micro-behavioral channel through which virtual trading induces energy misallocation.

Technology Category

• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Multiagent Systems: Mechanism Design
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In the Day-Ahead (DA) market, suppliers sell and load-serving entities (LSEs) purchase energy commitments, with both sides adjusting for imbalances between contracted and actual deliveries in the Real-Time (RT) market. We develop a supply function equilibrium model to study how virtual trading-speculating on DA-RT price spreads without physical delivery-affects market efficiency. Without virtual trading, LSEs underbid relative to actual demand in the DA market, pushing DA prices below expected RT prices. Virtual trading narrows, and in the limit of large number traders can eliminates, this price gap. However, it does not induce quantity alignment: DA-cleared demand remains below true expected demand, as price alignment makes the LSE indifferent between markets and prompts it to reduce DA bids to avoid over-purchasing. Renewable energy suppliers cannot offset these strategic distortions. We provide empirical support to our main model implications using data from the California and New York Independent System Operators.

Problem

• Analyzes virtual trading's impact on DA-RT price spreads
• Examines LSE underbidding in DA market without virtual trading
• Assesses renewable suppliers' inability to correct strategic distortions

Innovation

• Supply function equilibrium model for virtual trading
• Virtual trading narrows DA-RT price spreads
• Empirical analysis using California and New York ISO data