PENGUIN is AMIGO’s AI-powered renewable energy forecasting service that aims to provide fine-scale forecasts of meteorological variables that affect solar, wind, and hydropower sectors. The accuracy of meteorological models in providing short-term forecasts for renewable energy sources is limited, which results in significant risks to grid stability and penalty fees for plant operators. PENGUIN will use AI-enhanced estimates of key meteorological variables, such as cloud coverage, wind speed and direction, and runoff, through a suite of state-of-the-art AI techniques.
PENGUIN builds upon existing technology developed by AMIGO for hydropower and wind energy monitoring and forecasting and integrates it with a novel tool for short-term forecasting of solar energy generation. The solution is developed through co-design processes based on three study areas, and its flexibility will be validated at different locations. The exploitation of the services of PENGUIN will enable the stakeholders of the renewable energy value chain to increase the resilience, strengthen mitigation and prevention, and establish a sound preparedness strategy to RES fluctuations to ultimately make renewable energy production more efficient.
Usage of Standards for data interoperability:
For general IT standards, we conform to the Representational State Transfer(RESTful) architecture for our API implementation, using the GeoJSON format for data interchange. We also employ the Open Geospatial Consortium (OGC) and Network Common Data Form (NetCDF) standards for handling geospatial data.