A Data-Driven Study to Discover, Characterize, and Classify Convergence Bidding Strategies in California ISO Energy Market
Ehsan Samani, Hamed Mohsenian-Rad

TL;DR
This study analyzes three years of California ISO market data to understand convergence bidding strategies, revealing three distinct classes of strategies and highlighting discrepancies with existing literature.
Contribution
It provides a comprehensive data-driven analysis of real-world convergence bidding strategies and introduces new strategic classes not previously documented.
Findings
Identified three distinct classes of convergence bidding strategies.
Most active participants use strategies outside existing literature.
Detailed characterization of bidder performance and strategy differences.
Abstract
Convergence bidding has been adopted in recent years by most Independent System Operators (ISOs) in the United States as a relatively new market mechanism to enhance market efficiency. Convergence bidding affects many aspects of the operation of the electricity markets and there is currently a gap in the literature on understanding how the market participants strategically select their convergence bids in practice. To address this open problem, in this paper, we study three years of real-world market data from the California ISO energy market. First, we provide a data-driven overview of all submitted convergence bids (CBs) and analyze the performance of each individual convergence bidder based on the number of their submitted CBs, the number of locations that they placed the CBs, the percentage of submitted supply or demand CBs, the amount of cleared CBs, and their gained profit or…
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