Enhanced Bi-layer Iterative Stochastic Robust Planning Method for Shared Rental Energy Storage in Industrial Microgrids

Yanxin Wang; Jiajia Chen; Ping Li; Yanlei Zhao; Bingyin Xu

doi:10.35833/MPCE.2025.000822

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Enhanced Bi-layer Iterative Stochastic Robust Planning Method for Shared Rental Energy Storage in Industrial Microgrids

Original Paper | 更新时间：2026-09-28

- Enhanced Bi-layer Iterative Stochastic Robust Planning Method for Shared Rental Energy Storage in Industrial Microgrids
- Journal of Modern Power Systems and Clean Energy Vol. 14, Issue 5, Pages: 1845-1856(2026)
- 作者机构：
  
  1.Shandong Provincial Key Laboratory of New Power Distribution & Utilization Technology and Equipment, Shandong University of Technology, Zibo, China
  2.School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, China
- 作者简介：
  
  Yanxin Wang received the B.S. degree in electrical engineering from Shandong University of Technology, Zibo, China, in 2021. He is currently pursuing the Ph.D. degree at the School of Electrical and Electronic Engineering, Shandong University of Technology. His research interests include distributed power grid-connected technology and application. Email:17852030117@163.com
  Jiajia Chen received the Ph.D. degree from South China University of Technology, Guangzhou, China, in 2015. He is currently working as an Associate Professor in Shandong University of Technology, Zibo, China. His research interests include user-side energy storage operation and control technology, electricity market, smart distribution network operation and control, and agricultural microgrid operation and control. Email:sdjjchen@163.cn
  Ping Li received the B.S. degree in electronic information from Shandong University of Technology, Zibo, China, in 2023. She is currently pursuing the M.S. degree at the School of Electrical and Electronic Engineering, Shandong University of Technology. Her research interest includes dynamic pricing under electricity market operation. Email:2189509576@qq.com
  Yanlei Zhao received the Ph.D. degree from the Graduate University of the Chinese Academy of Sciences, Beijing, China, in 2006. He is currently working as a Professor in Shandong University of Technology, Zibo, China. His research interests include modern power electronics technology and its application in microgrid and smart distribution network. Email:yanleizhao@sdut.edu.cn
  Bingyin Xu received the Ph.D. degree from Xi’an Jiaotong University, Xi’an, China, in 1991. He is currently working as a Professor in Shandong University of Technology, Zibo, China. His research interests include power line fault monitoring, intelligent distribution network, and distribution network automation technology. Email:xuby@ vip.163.com
- 基金信息：
- DOI：10.35833/MPCE.2025.000822
  CLC：
- Received：09 September 2025，
  
  Revised：2025-12-22，
  
  Accepted：22 March 2026，
  
  Online First：06 May 2026，
  
  Published：15 September 2026
- 稿件说明：
移动端阅览
Wang Yanxin,Chen Jiajia,Li Ping,et al.Enhanced Bi-layer Iterative Stochastic Robust Planning Method for Shared Rental Energy Storage in Industrial Microgrids[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1845-1856.
DOI：

Wang Yanxin,Chen Jiajia,Li Ping,et al.Enhanced Bi-layer Iterative Stochastic Robust Planning Method for Shared Rental Energy Storage in Industrial Microgrids[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1845-1856. DOI： 10.35833/MPCE.2025.000822.

摘要

Abstract

The synergistic installation of energy storage (ES) and photovoltaic (PV) systems in industrial microgrids plays an irreplaceable role in improving energy efficiency

curbing carbon emission growth

and promoting sustainable economic development. However

the high initial investment costs of ES

coupled with the inherent uncertainty and volatility of PV

have restricted the large-scale application of ES. To address these challenges

this paper proposes an enhanced bi-layer iterative stochastic robust planning method for shared rental ES (SRES) in industrial microgrids. The upper layer develops a multi-objective probabilistic information gap decision theory (IGDT) method to investigate the optimal capacity and power of SRES among industrial microgrids under PV uncertainty. The lower layer proposes a demand power defense-driven distributed model predictive control (DMPC) method to manage the leased power from SRES to industrial microgrid. Numerical results demonstrate that compared with the self-built ES and shared ES

SRES achieves economic benefit improvements of 2.37% and 2.42%

respectively. The proposed planning method effectively mitigates the impact of PV uncertainty

enhances demand power defense capability

and significantly improves overall economic efficiency.

关键词

Keywords

references

H. Clark and H. Wu, “The sustainable development goals: 17 goals to transform our world,” Furthering the Work of the United Nations , vol. 2016 , pp. 36 - 54 , Aug. 2016 .

Y. Guo, J. Tian, and L. Chen, “Managing energy infrastructure to decarbonize industrial parks in China,” Nature Communications , vol. 11 , p. 981 , Feb. 2020 .

L. Pan, J. Chen, Y. Zhao et al ., “Towards optimal customized electricity pricing via iterative two-layer optimization for consumers and prosumers,” Journal of Cleaner Production , vol. 469 , p. 143208 , Sept. 2024.

N. Pei, X. Song, Z. Zhang et al ., “Optimizing the operation and allocating the cost of shared energy storage for multiple renewable energy stations in power generation side,” Energy Conversion and Management , vol. 302 , p. 118148 , Feb. 2024 .

X. Sun, J. Chen, S. Yang et al ., “Optimal scheduling of multi-regional integrated energy systems with shared energy storage under dynamic rental prices mechanism,” Journal of Energy Storage , vol. 106 , p. 114902 , Jan. 2025 .

J. Qiao, Y. Mi, S. Ma et al ., “Trilayer Stackelberg game scheduling of active distribution network based on microgrid group leasing shared energy storage,” Applied Energy , vol. 382 , p. 125157 , Mar. 2025 .

Y. Zhuang, Z. Li, Q. Tan et al ., “Multi-time-scale resource allocation based on long-term contracts and real-time rental business models for shared energy storage systems,” Journal of Modern Power Systems and Clean Energy , vol. 12 , no. 2 , pp. 454 - 465 , Mar. 2024 .

B. Wang, C. Zhang, C. Li et al ., “Multi-timescale energy sharing with Grid-BESS capacity rental considering uncertainties,” CSEE Journal of Power and Energy Systems , vol. 9 , no. 4 , pp. 1326 - 1336 , Aug. 2022 .

D. Xiao, H. Chen, W. Cai et al ., “Integrated risk measurement and control for stochastic energy trading of a wind storage system in electricity markets,” Protection and Control of Modern Power Systems , vol. 8 , no. 4 , pp. 1 - 11 , Oct. 2023 .

J. Zheng, L. Zhai, M. Tao et al ., “Low-carbon economic dispatch in integrated energy systems: a set-based interval optimization with decision support under uncertainties,” Protection and Control of Modern Power Systems , vol. 11 , no. 1 , pp. 68 - 87 , Jan. 2026 .

Z. Ji, J. T ian, S. Liu et al ., “Optimal scheduling of park-level integrated energy system considering multiple uncertainties: a comprehensive risk strategy-information gap decision theory method,” Applied Energy , vol. 377 , p. 124700 , Jan. 2025 .

H. Wang, F. Wang, D. Han et al ., “Multi-time scale optimal configuration of user-side energy storage considering demand perception,” Renewable Energy , vol. 237 , p. 121533 , Dec. 2024 .

C. Yan, F. Wang, Y. Pan et al ., “A multi-timescale cold storage system within energy flexible buildings for power balance management of smart grids,” Renewable Energy , vol. 161 , pp. 626 - 634 , Dec. 2020 .

C. Tan, Q. Tan, S. Geng et al ., “Multi-timescale interaction of a coupled electricity-hydrogen-gas system with a distribution network considering dynamic games,” Sustainable Cities and Society , vol. 96 , pp. 104639 , Sept. 2023.

Z. Li, Y. Xia, Y. Bo et al ., “Optimal planning for electricity-hydrogen integrated energy system considering multiple timescale operations and representative time-period selection,” Applied Energy , vol. 362 , p. 122965 , May 2024.

J. Salles-Mardones, A. Flores-Maradiaga, R. Barraza et al ., “Sensitivity analysis of peer-to-peer photovoltaic energy trading in a community microgrid in Chile,” Journal of Modern Power Systems and Clean Energy , vol. 12 , no. 6 , pp. 1993 - 2005 , Nov. 2024 .

C. Chen, Y. Li, W. Qiu et al ., “Cooperative-game-based day-ahead scheduling of local integrated energy systems with shared energy storage,” IEEE Transactions on Sustainable Energy , vol. 13 , no. 4 , pp. 1994 - 2011 , May 2022.

N. Vespermann, T. Hamacher, and J. Kazempour, “Access economy for storage in energy communities,” IEEE Transactions on Power Systems , vol. 36 , no. 3 , pp. 2234 - 2250 , Oct. 2020 .

Y. Bian, L. Xie, J. Ye et al ., “Peer-to-peer energy sharing model considering multi-objective optimal allocation of shared energy storage in a multi-microgrid system,” Energy , vol. 288 , p. 129864 , Feb. 2024 .

Y. Liu, X. Xu, C. Deng et al ., “Peer-to-peer based energy management framework for enhancing rural electrification level,” Journal of Modern Power Systems and Clean Energy , vol. 13 , no. 3 , pp. 953 - 966 , May 2025.

L. Affolabi, M. Shahidehpour, W. Gan et al ., “Optimal transactive energy trading of electric vehicle charging stations with on-site PV generation in constrained power distribution networks,” IEEE Transactions on Smart Grid , vol. 13 , no. 2 , pp. 1427 - 1440 , Dec. 2021 .

H. Yang, J. Chen, and Y. Li, “Two-layer iterative optimization for enhanced electricity-carbon pricing to promote renewable integration and load smoothing with multi-type prosumer,” Energy , vol. 336 , p. 138226 , Nov. 2025 .

J. Chen, F. Liu, Y. Wang et al ., “Emergency scheduling of virtual energy storage based on continuous-time model for resilience enhancement under extreme events,” Energy , vol. 342 , p. 139634 , Jan. 2026 .

Y. Zhang, J. Chen, Y. Wang et al ., “Enhancing resilience of agricultural microgrid through electricity-heat-water based multi-energy hub considering irradiation intensity uncertainty,” Renewable Energy , vol. 220 , p. 119739 , Jan. 2024 .

T. Xu, R. Wang, H. Meng et al ., “A coordinated two-stage decentralized flexibility trading in distribution grids with MGs,” Protection and Control of Modern Power Systems , vol. 9 , no. 5 , pp. 54 - 69 , Aug. 2024 .

P. Li, J. Chen, H. Yang et al ., “Peer-to-peer power trading and pricing for rental energy storage shared community microgrid: A coordinated Stackelberg and cooperative game,” Renewable Energy , vol. 256 , p. 123963 , Jan. 2025 .

Z. Wang, H. Hou, B. Zhao et al ., “Risk-averse stochastic capacity planning and P2P trading collaborative optimization for multi-energy microgrids considering carbon emission limitations: an asymmetric Nash bargaining approach,” Applied Energy , vol. 357 , p. 122505 , Mar. 2024 .

X. Fang, M. B. Hodge, H. Jiang et al ., “Decentralized wind uncertainty management: alternating direction method of multipliers based distributionally-robust chance constrained optimal power flow,” Applied Energy , vol. 239 , pp. 938 - 947 , Apr. 2019 .

S. Mhanna, G. Verbič, and C. A. Chapman, “Adaptive ADMM for distributed AC optimal power flow,” IEEE Transactions on Power Systems , vol. 34 , no. 3 , pp. 2025 - 2035 , Dec. 2018 .

E. González, J. Sanchis, V. J. Salcedo et al ., “Conditional scenario-based energy management algorithm with uncertain correlated forecasts,” Journal of Energy Storage , vol. 86 , p. 111177 , May 2024.

Y. Wang, J. Chen, Y. Zhao et al ., “Incorporate robust optimization and demand defense for optimal planning of shared rental energy storage in multi-user industrial park,” Energy , vol. 301 , p. 131721 , Aug. 2024 .

A. Georgantas, M. Doumpos, and C. Zopounidis, “Robust optimization approaches for portfolio selection: a comparative analysis,” Annals of Operations Research , vol. 339 , no. 3 , pp. 1205 - 1221 , Jun. 2024 .

Y. Zhang, M. Xiang, and Z. Zheng, “An IGDT-based decision model for industrial users participating in electricity and carbon markets considering differentiated power quality services,” Energy , vol. 315 , p. 134350 , Jan. 2025 .

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