GERIÓ – GEstión de Recursos energéticos distribuidos: Modelado y Optimización de flexibilidad para comunidades energéticas

GERIO faces the challenge of optimal scheduling of energy resources for energy communities with participation in flexibility programs. Thus, the project aims to leverage energy efficiency management of prosumers (e.g. households) and communities and their interaction with the grid by modelling, forecasting and managing demand flexibility. This imposes a twofold challenge of estimating the individual flexibility potential and the finding of optimal aggregation (i.e. number and schedule of loads) to satisfy an external demand. GERIO aims to combine data driven (machine learning) methods with thermal load modelling to reduce uncertainty and improve accuracy of flexibility forecasting. An accurate forecasting of generation, demand and flexibility improves soundness of schedules obtained with optimisation methods. Time horizons are expected to variate from close-to-real time (15 minutes) to a daily basis (day ahead) in accordance with current energy markets; and this impose some constraints in the implementation of both forecasting and scheduling strategies. Scheduling is also affected by the uncertainties (variability and volatility of renewable generation, stochastic behaviour of consumers, errors in modelling and forecasting, etc.); and, at the same time there exists a rebound. Combination of robust methods and rescheduling will be studied in this project to deal with such issues.