skip to Main Content

Project PID2022-142221OB-I00 funded by:

Project Details

Reference:

Execution:

Web:

Main researchers:

Center:

Contact:

Telephone:

PID2022-142221OB-I00

01/09/2023 – 31/08/2026

Joaquim Meléndez and Joan Colomer

+(34) 650507142

Outline

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.

Project PID2022-142221OB-I00 funded by MICIU/AEI/10.13039/501100011033 and by FEDER, UE

Related publications

Methodological Advances in Temperature Dynamics Modeling for Energy-Efficient Indoor Air Management Systems.

Iglesias, F., Massana, J., Burgas, L., Planellas, N., & Colomer, J. (2025). Methodological Advances in Temperature Dynamics Modeling for Energy-Efficient Indoor Air Management Systems. Applied Sciences, 15(8), 4291. | DOI: 10.3390/app15084291

Enabling charging point operators for participation in congestion markets

Massana, J., Burgas, L., Cañigueral, M., Sumper, A., Melendez, J., & Colomer, J. (2025). Enabling charging point operators for participation in congestion markets. International Journal of Electrical Power & Energy Systems, 167, 110604. https://doi.org/10.1016/j.ijepes.2025.110604

Transició energètica: electrificació de la demanda i gestió de la flexibilitat.

Meléndez i Frigola, J. (2024). Transició energètica: electrificació de la demanda i gestió de la flexibilitat. Revista de tecnologia, 2024, núm. 12, p. 56-68. DOI 10.2436/20.2004.01.53

Back To Top