Executive summary
Executive summary
LOCATION: Italy
KEY SOLUTION: s-EM | Power forecast
BENEFIT: Day-Ahead market strategy improvement
Background
PV plants Trading and Operational Strategy improvement from accurate power generation forecast
High penetration levels of Distributed Energy Resources (DERs), typically based on renewable generation, introduce several challenges in the new energy ecosystem, due to the intrinsic intermittent and uncertain nature of such DERs, the availability of distributed source of generation and consumption, the issues related to the integration into the grid. In this new complex energy context, it is fundamental to provide accurate forecast energy production from renewable sources, coming from solar photovoltaic (PV) in short and mid-term horizon.
Challenge
Provide accurate power forecast to mitigate issues of intermittent and uncertain generation
Solar power plant operation is affected by the intermittent and uncertain nature of solar source that impact on its: dispatchability, efficiency and monitoring. The ability to accurately forecast power generation from renewable sources is nowadays recognized as a fundamental skill to improve both trading strategy (for the market of energy) and the operation of PV plants.
The following challenges could influence service quality:
The i-EM forecast solution, thanks to its proven accuracy, fill the gap of this quality service.
Solution
Accurate forecast for Trading and Operational Strategy improvement
i-EM provides power forecasting service to support the operation of the renewable asset ensuring optimal energy forecasting according to different time horizons (typically from 6 hours till 15 days). Optimal solar power forecasting ensures optimal dispatching strategy, optimal maintenance scheduling, and efficient monitoring of plant production. Those optimizations are ensured by the following innovative features:
- use of different algorithms according to the time and spatial scale considering different signals availability and to always ensure the optimal performance
- use of different NWP data input models to reduce weather prediction errors impact.
- models blending for the optimal combination of many ML models and to foster the strength of each technique to improve the final accuracy.
- use of satellite data to improve short term forecast PV application (i-EM owns a satellite chain to transform satellite imagery in irradiation data product on a global basis)

Business impact
The improvement of your power forecasts accuracy can save you money and benefit entire community

Interested in this solution?
Our team will be happy to look at your specific needs and help you reach your goals in Energy Management.

