WorkGroups
Research areas identified to achieve technical, social and economic objectives that allow the deployment of Local Energy Communities with a positive balance.
Prediction and advanced data processing
The rising level of digitalization applied on the electrical network is associated with the application of advanced Big Data management techniques for the realization of an effective sampling. It improves the categorization of information, the patterns recognition and time reduction obtaining and processing the data. data for decision-making in real-time. The information processed differs from traditional networks, therefore it implies an investigation of data analysis techniques that allow optimal control and operation.
This working group will promote the research and development of advanced data analysis and prediction techniques (Data Mining, data science techniques, Machine Learning, Deep Learning, Big Data Analytics) for the development of algorithms that can accurately extract patterns, trends, and categorization of loads by obtaining information from large volumes of data, techniques for the development of preprocessing (edge computing) and reducing the size of the data. By means of improving processing efficiency and the cost of communication, prediction in the short-term for renewable generation, storage, and flexibility, taking into account associations such as the interdependence of price and demand, of innovative systems for computing data in real-time in distributed information systems that allow reducing time processing (Data mining distributed, Grid Computing, Cluster, multi-core, parallelization techniques of tasks/calculations).
Actions:
- Advanced data processing for microgrids in real-time.
- Development of short-term prediction techniques in electrical systems and characterization of thermal demand.