Value of forecasting
| WS: | WP1 Weather | WP2 Power | WP3 Applications | Deliverable | #, Due | Collaboration |
| Value of forecasting (WP3) | X | Paper | D 3.4 / M33 |
Without value for the end users, there wouldn’t be a market for forecasts. The incremental value of increase accuracy is though much harder to assess. The value proposition is though quite country and market specific. Therefore, we will analyse different market structures w.r.t. to the regulatory framework, the amount of renewable power in the system (i.e. whether it is a price taker or price maker), the possibilities for gaming and the implications of gaming for the system.
D.3.4: Documentation and communication of the assessment of the value of probabilistic forecasts in selected markets, bidding strategies (M24)
Workstream Outcomes
In the following, some selected outcomes from the workstream are presented. Not all of them are purely wind, Some are also focusing on solar or both wind and solar forecasting tools. All these finding are equally interesting from a “windy” perspective , and should be looked upon as important milestones for renewable energy integration into the system operations, rather than on the choice of energy source chosen as focus point.
Quantifying the value of probabilistic forecasting for power system operation planning
The DOE funded project Operational Probabilistic Tools for Solar Uncertainty (OPTSUN) developed and demonstrated new methods to operate power systems with high penetration of solar power. These methods use probabilistic solar power forecasts, which capture the uncertainty inherent in solar power output, to support decision making in utility operations.
The highlights from the project:
- Development of enhanced probabilistic power forecasts for utility-scale and behind-the-meter (BTM) solar
- Identification of advanced methods for managing uncertainty in utility operations
- Validattion of methods through detailed simulation of power system operations using data from utility regions across the United States
- Demonstration of a scheduling management platform to integrate probabilistic forecasts and scheduling decisions, with code released as open-soucrce
The project’s overview, final report, access to the open-source software and contact details to the researcher can be found here. The journal publication (“Quantifying the value of probabilistic forecasting for power system operation planning”) following the project can be seen here. or in our publication list for 2023