In response to the development needs of high proportion wind power bases in northwest China, northern Shandong and other regions, as well as the strong fluctuation characteristics of wind power, this paper establishes a theoretical analysis model for permanent magnet direct drive wind power bases, analyzes the operating characteristics of the system under wind speed changes and load fluctuations, and establishes a MW level wind power base system simulation model with Matlab/Simulink. The simulation results verify the theoretical analysis. Secondly, based on this, an optimized configuration plan for the capacity operation of the supporting energy storage system during the gradual increase of the proportion of new energy has been formed from the perspectives of system economy and reliability, and it has been solved using particle swarm optimization algorithm. Finally, a case study is conducted on a 100 megawatt level combined power generation system that includes wind power, thermal power, hybrid energy storage, and load.

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Research on Operating Characteristics of Permanent Magnet Direct Drive Wind Power Base and Optimization Configuration Scheme of Energy Storage System

  • Yong Li,
  • Tao Li,
  • Fengjiao Xie,
  • Longlong Zhang,
  • Jiming Chen,
  • Xuhu Ren,
  • Honggang Li,
  • Xiaoning Li

摘要

In response to the development needs of high proportion wind power bases in northwest China, northern Shandong and other regions, as well as the strong fluctuation characteristics of wind power, this paper establishes a theoretical analysis model for permanent magnet direct drive wind power bases, analyzes the operating characteristics of the system under wind speed changes and load fluctuations, and establishes a MW level wind power base system simulation model with Matlab/Simulink. The simulation results verify the theoretical analysis. Secondly, based on this, an optimized configuration plan for the capacity operation of the supporting energy storage system during the gradual increase of the proportion of new energy has been formed from the perspectives of system economy and reliability, and it has been solved using particle swarm optimization algorithm. Finally, a case study is conducted on a 100 megawatt level combined power generation system that includes wind power, thermal power, hybrid energy storage, and load.