In the energy domain (Use Case 3), led by Predictia Intelligent Data Solutions, EOSC-SIESTA aims to develop a user-friendly service for forecasting and optimising battery usage in solar power stations.
The use case includes the development of a web-based application for energy forecasting, enabling users to analyse and predict energy production and storage needs. To support this, an anonymised dataset will be generated and made available for users to download and experiment with.
Given the sensitivity of certain data sources, different anonymisation techniques will be explored and evaluated, including approaches based on differential privacy. In addition, the project investigates anonymisation methods applied to geospatial data, such as orthophoto maps, through image recognition techniques.
Overall, the objective is to provide reliable forecasting tools while ensuring that data privacy is preserved, allowing users to work with realistic datasets without compromising sensitive information.