This letter proposes an energy-macroclimate management mechanism for rural agricultural microgrids (AMGs) and develops a prediction-free online method to address the reliance on prediction in real-time decision making. This method reformulates the AMG energy-macroclimate management model into a time-decoupled optimization problem, enabling real-time decision making based solely on the current system state, without requiring uncertainty prediction. Comparative studies validate the effectiveness and long-term performance of the proposed method.
Prediction-Free Online Energy-Macroclimate Management for Agricultural Microgrids / Hua, Z., Cao, Y., Li, C., Wang, Z., Yu, Y.i., Islam, M.M., Scala, M.L.. - In: IEEE TRANSACTIONS ON SMART GRID. - ISSN 1949-3053. - 16:6(2025), pp. 5689-5692. [10.1109/tsg.2025.3604634]
Prediction-Free Online Energy-Macroclimate Management for Agricultural Microgrids
Islam, Muhammad MuzammalMembro del Collaboration Group
;Scala, Massimo LaMembro del Collaboration Group
2025
Abstract
This letter proposes an energy-macroclimate management mechanism for rural agricultural microgrids (AMGs) and develops a prediction-free online method to address the reliance on prediction in real-time decision making. This method reformulates the AMG energy-macroclimate management model into a time-decoupled optimization problem, enabling real-time decision making based solely on the current system state, without requiring uncertainty prediction. Comparative studies validate the effectiveness and long-term performance of the proposed method.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

