Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

Zheng Shi, Lu Yan, Yingying Hu, Yao Wang, Wenping Qin (), Yan Liang, Haibo Zhao, Yongming Jing, Jiaojiao Deng and Zhi Zhang
Additional contact information
Zheng Shi: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
Lu Yan: Yingda Chang’an Insurance Brokers Co., Ltd., Taiyuan 030021, China
Yingying Hu: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
Yao Wang: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
Wenping Qin: Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Yan Liang: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
Haibo Zhao: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
Yongming Jing: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
Jiaojiao Deng: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
Zhi Zhang: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China

Energies, 2024, vol. 17, issue 18, 1-20

Abstract: The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%.

Keywords: microgrid; shared energy storage; optimize scheduling; negotiation price; dual objective (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/18/4614/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/18/4614/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:18:p:4614-:d:1478282

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().