Webinar Series: Machine learning improves CCGT availability, capacity, and efficiency

Case studies on generation M&D, predictive analytics, capacity/fuel demand forecasting, and performance testing

This webinar series, presented by Primex Process Specialists, is directed specifically towards power plant owners and operators to introduce machine-learning basics and how this rapidly evolving technology can improve power plant availability, capacity, and efficiency. Each webinar will include a 30-minute live presentation followed by Q&A with audience members.

Introduction to Machine Learning and Power Plant Use Cases

Discover how machine learning works, how it differs from AI and an overview of how it can (and cannot) be used in the power plant environment to improve availability, capacity, and efficiency.

Date: Tuesday June 13th, 2pm ET

Power Plant Machine Learning Use Case # 1: Generation Monitoring and Diagnostics

Combined with human expertise, machine-learning can transform asset productivity and value. Attend this webinar to learn how this rapidly evolving technology accelerates recognition, quantification, and realization of high-level performance improvement opportunities.

Date: Tuesday June 20th, 2pm ET

Power Plant Machine Learning Use Case # 2: Capacity and Fuel Demand Forecasting

Accurately predicting the future has always been valuable. Learn how managers responsible for generation assets bidding into day-ahead merchant markets can realize greater accuracy in daily forecasts of capacity and (for some) fuel consumption with machine-learning.

Date: Tuesday June 27th, 2pm ET

Power Plant Machine Learning Use Case # 3: Performance Testing and Guarantee Validation

Making investment decisions and quantifying value around generating unit upgrades or repairs can be tricky business. Discover how machine-learning helps untangle performance data to gain accuracy and confidence in test results for comparison with supplier performance guarantees, asset valuation and vendor compensation.

Date: Tuesday July 11th, 2pm ET

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