Energy storage system has been adopted in power system to enhance its frequency stability. However, little research has been done on the types, installation locations and capacities configurations of energy storage. This paper proposes a method for determining the locations and capacities of multi type energy storage installations considering frequency stability requirements for a certain system. Firstly, it introduces a combined offshore wind power - thermal power - energy storage output system, along with its frequency stability equivalent model. Secondly, it presents frequency stability requirements. Thirdly, it proposes the optimization problem for configuration of a multi-type energy storages with the objective of minimizing total cost and frequency constraints, and utilizes particle swarm optimization algorithm to solve it. Finally, simulation results with battery energy storage and hydrogen energy storage show the effectiveness of the proposed methods in different scenarios.

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A Method to Multi-type Energy Storage Configuration for an Offshore Wind-Thermal-Output Systems Considering Frequency Security

  • Xuan Ren,
  • Weifang Lin,
  • Jun Yi,
  • Ke Zhang,
  • Weihao Yu,
  • Jinyu Li,
  • Zhe Zhang,
  • Ancheng Xue

摘要

Energy storage system has been adopted in power system to enhance its frequency stability. However, little research has been done on the types, installation locations and capacities configurations of energy storage. This paper proposes a method for determining the locations and capacities of multi type energy storage installations considering frequency stability requirements for a certain system. Firstly, it introduces a combined offshore wind power - thermal power - energy storage output system, along with its frequency stability equivalent model. Secondly, it presents frequency stability requirements. Thirdly, it proposes the optimization problem for configuration of a multi-type energy storages with the objective of minimizing total cost and frequency constraints, and utilizes particle swarm optimization algorithm to solve it. Finally, simulation results with battery energy storage and hydrogen energy storage show the effectiveness of the proposed methods in different scenarios.