Prediction-Free Online Energy-Macroclimate Management for Agricultural Microgrids
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.
Authors
- Zhihao Hua (ORCID: https://orcid.org/0000-0001-5718-4451)
- Yingping Cao (ORCID: https://orcid.org/0009-0002-1172-2204)
- Yi Yu
- Massimo La Scala (ORCID: https://orcid.org/0000-0002-7257-2599)
- Muhammad Muzammal Islam (ORCID: https://orcid.org/0000-0003-0795-4547)
- Ziqiang Wang (ORCID: https://orcid.org/0000-0002-6883-8569)
- Canbing Li (ORCID: https://orcid.org/0000-0001-9116-7487)
Institutions
- Hong Kong Polytechnic University (HK)
- Hunan University (CN)
- Shanghai Jiao Tong University (CN)
- Polytechnic University of Bari (IT)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1109/tsg.2025.3604634
- Citations
- 2
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 1.46
Funders
- National Natural Science Foundation of China