Simulation study on low frequency load shedding strategy of large power grid considering wind power participation in frequency modulation

Feng Sun; Zengyao Tian; Xinwei Li; Xiaoheng Zhang; Shaowu Liu; Mingze Sun; Peng Ye; Tianyue Li

doi:10.1117/12.2624815

13 December 2021 Simulation study on low frequency load shedding strategy of large power grid considering wind power participation in frequency modulation

Feng Sun, Zengyao Tian, Xinwei Li, Xiaoheng Zhang, Shaowu Liu, Mingze Sun, Peng Ye, Tianyue Li

Author Affiliations +

Proceedings Volume 12087, International Conference on Electronic Information Engineering and Computer Technology (EIECT 2021); 1208702 (2021) https://doi.org/10.1117/12.2624815
Event: International Conference on Electronic Information Engineering and Computer Technology (EIECT 2021), 2021, Kunming, China

Abstract

Large-scale wind turbine participation in the system primary frequency regulation will have a greater impact on the development and implementation of low-frequency load shedding strategies for the grid, and to explore the effect under different proportions of wind power, model of wind power participating in frequency regulation is introduced first, then the principle of under-frequency load shedding strategy in power system is expounded, and finally build large grid model in power system simulation software, and combining with the actual power grid operation are simulated, the simulation results show that considering wind power in power grid frequency regulation of under-frequency load shedding strategy, including load removal is less obvious, that wind power to participate in the frequency regulation of under-frequency reduction with a positive impact.

Citation Download Citation

Feng Sun, Zengyao Tian, Xinwei Li, Xiaoheng Zhang, Shaowu Liu, Mingze Sun, Peng Ye, and Tianyue Li "Simulation study on low frequency load shedding strategy of large power grid considering wind power participation in frequency modulation", Proc. SPIE 12087, International Conference on Electronic Information Engineering and Computer Technology (EIECT 2021), 1208702 (13 December 2021); https://doi.org/10.1117/12.2624815

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