Author
Listed:
- Jiajie Peng
(School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China)
- Yu Peng
(School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China)
- Zijian Ye
(School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China)
- Songlin Cai
(School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China)
- Xin Huang
(College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)
- Junjie Zhong
(School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China)
Abstract
The sustainable collaborative operation of multi-park integrated energy systems (MPIESs) with shared energy storage (SES) provides a significant pathway for low-carbon transition, renewable energy utilization, and energy efficiency improvement, thereby supporting regional energy sustainability. However, realizing this potential faces challenges, including source-load uncertainty, conflicts of interest among multiple entities, and the need for privacy-preserving distributed coordination. To address these issues, this paper proposes a distributed robust energy management strategy for MPIESs with SES, which is decomposed into two sub-problems. In the first sub-problem, a robust optimization model incorporating the SES leasing mechanism is established to handle the uncertainties of photovoltaic (PV) generation and loads. In the second sub-problem, a cooperative game model based on Nash bargaining theory is constructed to fairly allocate the cooperative surplus among participating parks. The alternating direction method of multipliers (ADMM) is employed to solve the overall model in a distributed manner, and enabling collaborative scheduling with limited information exchange. Case studies indicate that the proposed strategy reduces the total system operating cost by 17.57% compared to the independent operation mode. The benefit allocation mechanism achieves Pareto improvement and effectively mitigates the uneven distribution of cooperative surplus among parks. Furthermore, the distributed algorithm converges within 13 iterations in the test case, demonstrating good computational tractability. Consequently, the results verify the effectiveness of the proposed framework in balancing economy, fairness, and robustness, thereby promoting the low-carbon and sustainable operation of regional integrated energy systems.
Suggested Citation
Jiajie Peng & Yu Peng & Zijian Ye & Songlin Cai & Xin Huang & Junjie Zhong, 2026.
"Robust and Fair Collaborative Energy Management for Sustainable Multi-Park Integrated Energy Systems with Shared Energy Storage,"
Sustainability, MDPI, vol. 18(9), pages 1-30, April.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:9:p:4422-:d:1933245
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