As the energy transition advances, large power systems are encountering emerging challenges as they integrate higher shares of Variable Renewable Energy (VRE). Short-term VRE forecasting is becoming increasingly critical in real-time power system operations, as inaccuracies can negatively affect system frequency, increase dispatch complexity, and raise the economic cost of reserves.
The ETSI team is driven to create solutions that strengthen the grid through the energy transition, by designing forecasting models that deliver value both to the power system and market stakeholders.
System Benefits
Accurate short-term forecasting improves the overall stability and efficiency of the power system.
Improved forecast accuracy reduces the need for residual units to compensate, allowing the system operator to dispatch resources more effectively and minimise reliance on costly frequency reserves. This, in turn, lowers the economic burden of maintaining reliability.
Better forecasting also supports the integration of higher shares of VRE. With fewer imbalances and smoother alignment between dispatched and actual generation, power systems can accommodate greater renewable penetration without compromising security or operational performance.
Customer Benefits
Different electricity markets take different approaches to short-term VRE forecasting. In some markets, the responsibility sits solely with the market operator, while in others it is placed on individual participants. Some markets use a hybrid approach.
In markets where participants are involved with this responsibility, incentives and penalties often exist aimed to improve overall forecasting or generator performance. This is typically done through cost allocations or market charges linked to poor performance.
Case Study: Australia’s NEM uses a hybrid approach to VRE forecasting, allowing large wind and solar farms the option to submit their own ‘Self-Forecasts’ in place of the market operator’s central forecast model for market dispatch.
ETSI supports participants by delivering more accurate and reliable self-forecast values. This in turn reduces costs associated with related market mechanisms (e.g., Regulation FCAS costs and Frequency Performance Payments) and enables generators to produce additional electricity that might otherwise have been curtailed.
