» » »

Convergence Bidding: Leveraging AI and Optimization

Amir Mousavi

In the competitive landscape of energy markets, convergence bidding has become an essential strategy for enhancing market efficiency. This presentation explores the principles and benefits of convergence bidding, focusing on its role in aligning prices between Day-Ahead Markets (DAM) and Real-Time Markets (RTM).

Gridmatic, a leader in energy trading, utilizes cutting-edge AI and optimization techniques to implement convergence bidding strategies across all markets. By forecasting future market prices and making data-driven bids and offers, Gridmatic optimizes participation in convergence bidding to take advantage of arbitrage opportunities across markets while reducing risk and maximizing returns. Attendees will gain insights into the convergence bidding concept, AI models, optimization algorithms, and operational strategies that drive our success in energy trading.

Speaker: Amir Mousavi, Gridmatic

Attend in person or online (see weblink)

Thursday, 05/30/24

Contact:

Website: Click to Visit

Cost:

Free

Save this Event:

iCalendar
Google Calendar
Yahoo! Calendar
Windows Live Calendar

Environment and Energy Building (Y2E2)

Stanford University
Room 292A
Stanford, CA 94305