A Snake Optimization Algorithm-Based Power System Inertia Estimation Method Considering the Effects of Transient Frequency and Voltage Changes

Yanzhen Pang, Feng Li (), Haiya Qian, Xiaofeng Liu and Yunting Yao
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Yanzhen Pang: School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Feng Li: School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Haiya Qian: School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Xiaofeng Liu: School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Yunting Yao: School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China

Energies, 2024, vol. 17, issue 17, 1-14

Abstract: Inertia is the measure of a power system’s ability to resist power interference. The accurate estimation and prediction of inertia are crucial for the safe operation of the power system. To obtain the accurate power system inertia provided by generators, this paper proposes an estimation method considering the influence of frequency and voltage characteristics on the power deficit during transients. Specifically, the traditional swing equations-based inertia estimation model is improved by embedding linearized frequency and voltage factors. On this basis, the snake optimization algorithm is utilized to identify the power system inertia constant due to its strong global search ability and fast convergence speed. Finally, the proposed inertia estimation method is validated in four test systems, and the results show the effectiveness of the proposed method.

Keywords: inertia estimation; swing equation; inertia time constant; snake optimization algorithm (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
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