JACIII Vol.28 No.3 pp. 528-540
doi: 10.20965/jaciii.2024.p0528

Research Paper:

Study on Master-Slave Game Optimization Operation of Integrated Energy Microgrid Considering PV Output Uncertainty and Shared Energy Storage

Kai Kang*, Yunlong Zhang*, Yijun Miu*, Qi Gao**, Kaiwen Chen**, and Zihan Zeng**

*PowerChina Hubei Electric Engineering Co., Ltd.
No.1 Xinqiao Si Road, East and West Lake District, Wuhan, Hubei 430040, China

**School of Automation, China University of Geosciences
388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China

September 20, 2023
December 21, 2023
May 20, 2024
integrated energy microgrids, shared energy storage, master-slave game, comprehensive electric heating requirements

Integrated energy microgrids and shared energy storage have significant benefits in improving the energy utilization of the system, which is gradually becoming the current research hotspot. And the uncertainty of new energy output also significantly affects the stable and economic operation of integrated energy microgrid. So how to establish a set of integrated energy microgrids optimization operation model considering photovoltaic (PV) output uncertainty and shared energy storage is an urgent problem to be solved nowadays. Firstly, this paper introduces the framework of an integrated energy system microgrid containing a shared energy storage operator (ESO), and analyzes the scheduling method of the upper tier operator within the system as well as the economic benefits at the lower tier user end. Secondly, to address the randomness of PV output, Monte Carlo method is used to generate the scenarios, and then the scenarios are cut down by using the fast antecedent elimination technique. Then, an optimal operation model is established for micro grid operator (MGO) and user aggregator (UA), respectively, and based on the master-slave game relationship, so that the MGO is the leader and the UA is the follower, a Stackelberg game model is proposed to consider the integrated demand response of electricity and heat between the MGO and UA in the context of the participation of ESO in the auxiliary service of the UA. Finally, the proposed model is brought into a typical residential building community for simulation verification, and the results show that the model proposed in this paper can effectively balance the interests of MGOs and UAs, and realize win-win benefits for UA and ESO.

Cite this article as:
K. Kang, Y. Zhang, Y. Miu, Q. Gao, K. Chen, and Z. Zeng, “Study on Master-Slave Game Optimization Operation of Integrated Energy Microgrid Considering PV Output Uncertainty and Shared Energy Storage,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.3, pp. 528-540, 2024.
Data files:
  1. [1] X. Chen, G. Tian, Y. Huang, Y. Yang, J. Li, Y. Wu, and Y. Chi, “New power system development path mechanism design,” Glob. Energy Interconnect., Vol.6, No.2, pp. 166-174, 2023.
  2. [2] Q. Tan, X. Li, W. Fan, H. Wang, and J. Yang, “Some key issues in building a “source network load storage” complementary energy internet in China,” Environ. Sci. Pollut. Res., Vol.30, pp. 83513-83529, 2023.
  3. [3] N. Huang, X. Zhao, Y. Guo, G. Cai, and R. Wang, “Distribution network expansion planning considering a distributed hydrogen-thermal storage system based on photovoltaic development of the Whole County of China,” Energy, Vol.278, Article No.127761, 2023.
  4. [4] P. Li, Z. Wang, W. Yang, H. Liu, Y. Yin, J. Wang, and T. Guo, “Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game,” Energy, Vol.214, Article No.119006, 2021.
  5. [5] L. Ma, N. Liu, J. Zhang, W. Tushar, and C. Yuen, “Energy management for joint operation of CHP and PV prosumers inside a grid-connected microgrid: A game theoretic approach,” IEEE Trans. Ind. Inform., Vol.12, No.5, pp. 1930-1942, 2016.
  6. [6] N. Liu, L. He, X. Yu, and L. Ma, “Multiparty energy management for grid-connected microgrids with heat- and electricity-coupled demand response,” IEEE Trans. Ind. Inform., Vol.14, No.5, pp. 1887-1897, 2017.
  7. [7] W. Huang, N. Zhang, J. Yang, Y. Wang, and C. Kang, “Optimal configuration planning of multi-energy systems considering distributed renewable energy,” IEEE Trans. Smart Grid, Vol.10, No.2, pp. 1452-1464, 2017.
  8. [8] Y. Li, Z. Yang, G. Li, D. Zhao, and W. Tian, “Optimal scheduling of an isolated microgrid with battery storage considering load and renewable generation uncertainties,” IEEE Trans. Ind. Electron., Vol.66, No.2, pp. 1565-1575, 2018.
  9. [9] W. Liu, S. Wang, C. Wei, Y. Li, and J. Guo, “Optimal allocation of battery energy storage in distribution network considering the co-operation of generalized demand side resources,” Proc. of the 43rd Annu. Conf. of the IEEE Ind. Electron. Soc. (IECON 2017), pp. 2793-2798, 2017.
  10. [10] M. Gholami, M. J. Sanjari, and A. Berrada, “Game theoretical approach for critical sizing of energy storage systems for residential prosumers,” J. Energy Storage, Vol.64, Article No.107166, 2023.
  11. [11] N. Liu, X. Yu, C. Wang, and J. Wang, “Energy sharing management for microgrids with PV prosumers: A Stackelberg game approach,” IEEE Trans. Ind. Inform., Vol.13, No.3, pp. 1088-1098, 2017.
  12. [12] Y. Liu, Q. He, X. Shi, Q. Zhang, and X. An, “Energy storage in China: Development progress and business model,” J. Energy Storage, Vol.72, Article No.108240, 2023.
  13. [13] B. El Barkouki, M. Laamim, A. Rochd, J.-W. Chang, A. Benazzouz, M. Ouassaid, M. Kang, and H. Jeong, “An economic dispatch for a shared energy storage system using MILP optimization: A case study of a Moroccan microgrid,” Energies, Vol.16, No.12, Article No.4601, 2023.
  14. [14] B. Li, Q. Yang, and I. Kamwa, “A novel Stackelberg-game-based energy storage sharing scheme under demand charge,” IEEE/CAA J. Automatica Sin., Vol.10, No.2, pp. 462-473, 2023.
  15. [15] S. Jiang, J. Gu, P. Zhang, W. Li, F. Wang, and W. Pei, “Operation optimization model for photovoltaic user group with shared storage and demand response,” Proc. of the 2023 5th Asia Energy and Electr. Eng. Symp. (AEEES), pp. 1508-1513, 2023.
  16. [16] X. Zong and Y. Yuan, “Two-stage robust optimization of regional integrated energy systems considering uncertainties of distributed energy stations,” Front. Energy Res., Vol.11, Article No.1135056, 2023.
  17. [17] M. Xu, W. Li, Z. Feng, W. Bai, L. Jia, and Z. Wei, “Economic dispatch model of high proportional new energy grid-connected consumption considering source load uncertainty,” Energies, Vol.16, No.4, Article No.1696, 2023.
  18. [18] K. Li, J. Zhang, J. Che, F. Wang, H. Ren, and Z. Mi, “Capacity configuration optimization for stand-alone microgrid considering the uncertainties of wind and solar resource,” Proc. of the 2018 IEEE Power & Energy Soc. Innov. Smart Grid Technol. Conf. (ISGT), pp. 1-5, 2018.
  19. [19] W. Wei, L. Ye, Y. Fang, Y. Wang, X. Chen, and Z. Li, “Optimal allocation of energy storage capacity in microgrids considering the uncertainty of renewable energy generation,” Sustainability, Vol.15, No.12, Article No.9544, 2023.
  20. [20] T. P. Abud, A. A. Augusto, M. Z. Fortes, R. S. Maciel, and B. S. M. C. Borba, “State of the art Monte Carlo method applied to power system analysis with distributed generation,” Energies, Vol.16, Issue 1, Article No.394, 2022.
  21. [21] X. Deng and H. Guo, “Existence of the equilibrium solution of a two-stage leaders-followers game,” Mathematics in Economics, Vol.26, No.4, pp. 50-53, 2009.

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Last updated on Jul. 12, 2024