TY  - CONF
AU  - Zambrano, Holguer Humberto Noriega
AU  - Benigni, Andrea
AU  - Lazzari, Riccardo
AU  - Piegari, Luigi
TI  - A Forecast-Driven Energy Management Methodology for Microgrids under Seasonal Variability
PB  - IEEE
M1  - FZJ-2026-01399
SP  - 1108-1114
PY  - 2025
AB  - This paper introduces a dynamic energy management strategy based on model predictive control (MPC) for a microgrid with photovoltaic generation and an energy storage system. The strategy is designed to be able to acclimate to different seasonal situations. Moreover, to model realistic scenarios, some forecasting uncertainties are made current, using noise models for photovoltaic, load and cost variables. The performance of the MPC was also compared with an open-loop controller with pre-known trajectory prediction. Moreover, some week scenarios are carried out using real and processed solar generation data and load profiles from Milan, Italy, considering summer and winter periods. The results show the MPC strategy is able to optimize grid transactions, while the stability of the battery is kept even in hard and noisy scenarios.
T2  - 2025 International Conference on Clean Electrical Power (ICCEP)
CY  - 24 Jun 2025 - 26 Jun 2025, Villasimius (Italy)
Y2  - 24 Jun 2025 - 26 Jun 2025
M2  - Villasimius, Italy
LB  - PUB:(DE-HGF)8
DO  - DOI:10.1109/ICCEP65222.2025.11143761
UR  - https://juser.fz-juelich.de/record/1053059
ER  -