BKOAI developed a forecasting tool that uses weather and plant data to support market bidding and production planning across a 168-hour forecast horizon
Goals
Improve the accuracy of market bidding strategies for power generation.
Leverage week-ahead forecasted weather conditions to plan operational capacity.
Standardize and streamline the integration of plant simulation data into bidding workflows.
Improve profitability by optimizing power-generation asset utilization.
Challenges
Limited visibility into the complex interaction of market dynamics and plant operations.
Difficulty incorporating week-ahead weather forecasts into manual bidding workflows.
Lack of a centralized interface to simulate and test ERCOT market bidding scenarios.
Inefficient operational planning leading to missed revenue opportunities during periods of volatility.
Solutions
Developed an advanced forecasting tool integrating week-ahead weather conditions.
Implemented the CCTWIN simulator to model plant operations under forecasted conditions.
Created a user-friendly spreadsheet interface to easily configure and fine-tune weekly inputs.
Integrated automated reporting to deliver bidding forecasts across a 168-hour horizon via email or direct market APIs.
Results
Supported more informed market-bidding decisions during periods when the application was available.
Provided clear visibility into granular bidding forecasts across a 168-hour horizon.
Streamlined data sharing through automated email delivery and direct API integration.
Improved strategic decision-making by aligning weather forecasts with simulated plant outputs.
.svg){kind=small}
.svg){kind=small}
.svg){kind=small}