Plant Simulator with Forecasting Models
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.
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