Virtual power plant
Generation forecasts for photovoltaic, wind and biomass plants as well as load forecasts for mandatory load metered facilities (RLM)
What significance do data have for a business model such as the virtual power plant of an energy company and how can self-learning algorithms help to reliably provide the best possible generation forecasts for solar, biogas, wind and power plants as well as customer consumption forecasts. SANDY provides the colleagues of a virtual power plant with a full-managed service via REST-API and delivers reliable forecasts around the clock.
The operator of a virtual power plant requires generation and consumption forecasts for every single distributed energy source and customer in their portfolio, to be able to market electricity directly as well as to trade in flexibilities. It must therefore be possible to make flexible, reliable forecasts for the constantly changing portfolio of facilities, with and without a given data history.
Zielgruppe
- Energiemanagement-System-Entwickler
- Energiehändler
- App- und Anwendungsentwickler
- Netzbetreiber
Added values for your company
- Fast, simple and cost-effective integration into existing systems
- all advantages of “Software as a Service”, e.g. high availability, automatic updates, no maintenance effort
- no use of personal data
- flexible scaling with growing corporate structure
- high degree of security due to secured and encrypted interfaces
SANDY AI Solution
- Forecasts for several hundred photovoltaic-, wind- and biomass plants as well as mandatory load metered customer (RLM) are created under consideration of facility-specific production or consumption measurements and site-specific weather forecasts
- Fully automatic provision of day-ahead and 7-day-ahead forecasts with 15 min resolution
- Delivery of the best possible individual facility forecast by independent selection of the best respective mathematical model
- Fully automated self-learning model parameter training for each individual facility