DeepAI AI Chat
Log In Sign Up

A Data-Driven Study to Discover, Characterize, and Classify Convergence Bidding Strategies in California ISO Energy Market

by   Ehsan Samani, et al.

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 loss. Next, we scrutinize the bidding strategies of the 13 largest market players that account for 75% of all CBs in the California ISO market. We identify quantitative features to characterize and distinguish their different convergence bidding strategies. This analysis results in revealing three different classes of CB strategies that are used in practice. We identify the differences between these strategic bidding classes and compare their advantages and disadvantages. We also explain how some of the most active market participants are using bidding strategies that do not match any of the strategic bidding methods that currently exist in the literature.


page 1

page 2


Axioms for Constant Function Market Makers

We study axiomatic foundations for different classes of constant functio...

Vulnerability Analysis for Data Driven Pricing Schemes

Data analytics and machine learning techniques are being rapidly adopted...

Data Markets to support AI for All: Pricing, Valuation and Governance

We discuss a data market technique based on intrinsic (relevance and uni...

Applications of Mechanism Design in Market-Based Demand-Side Management

The intermittent nature of renewable energy resources creates extra chal...

Thompson Sampling for Bandit Learning in Matching Markets

The problem of two-sided matching markets has a wide range of real-world...