The PrecX project will develop a forecast service that provides highly accurate, hyper-local, and on demand precipitation prediction everywhere in the world. PrecX will be a ready-to-go digital solution for hydropower-related companies to easily get a tailor-made precipitation forecast. Hydropower companies are dependent on the accuracy of hyper-local precipitation forecast as this is crucial information used to establish the inflow of water to rivers or reservoirs, consequently establishing the right pricing of produced electricity. The energy market is increasingly digital, and PrecX will be a lower cost solution that provides accurate forecasts based on deep learning combining different data sources. This milestone project will prepare PrecX for full-scale development, and address the R&D challenges of making an operationally viable deep learning based forecast, as well as investigate the potential business model for PrecX.
Project leader: Jean-Marie Lepioufle
Institution: NILU - STIFTELSEN NORSK INSTITUTT FOR LUFTFORSKNING