Journal of Modern Power Systems and Clean Energy

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Home > Archive>Volume 12, Issue 2, 2024 >359-370. DOI:10.35833/MPCE.2023.000345
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Optimal Operation with Dynamic Partitioning Strategy for Centralized Shared Energy Storage Station with Integration of Large-scale Renewable Energy
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Affiliation:

1.Beijing Future Technology Innovation Centre for Electrochemical Energy Storage System Integration, North China University of Technology, Beijing 100144, China;2.State Grid Fujian Electric Power Research Institute, Fuzhou 350007, China

Fund Project:

This work was supported by the National Natural Science Foundation of China “Game control-based planning and simulation modelling of coupled optical storage hydrogen production system” (No. 52277211).

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    Abstract:

    As renewable energy continues to be integrated into the grid, energy storage has become a vital technique supporting power system development. To effectively promote the efficiency and economics of energy storage, centralized shared energy storage (SES) station with multiple energy storage batteries is developed to enable energy trading among a group of entities. In this paper, we propose the optimal operation with dynamic partitioning strategy for the centralized SES station, considering the day-ahead demands of large-scale renewable energy power plants. We implement a multi-entity cooperative optimization operation model based on Nash bargaining theory. This model is decomposed into two subproblems: the operation profit maximization problem with energy trading and the leasing payment bargaining problem. The distributed alternating direction multiplier method (ADMM) is employed to address the subproblems separately. Simulations reveal that the optimal operation with a dynamic partitioning strategy improves the tracking of planned output of renewable energy entities, enhances the actual utilization rate of energy storage, and increases the profits of each participating entity. The results confirm the practicality and effectiveness of the strategy.

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History
  • Received:May 23,2023
  • Revised:August 31,2023
  • Online: March 27,2024

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