Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 11, Issue 1


Published
on

February 27, 2025


Pages


DOI

Article

Power supply stability analysis of power networks considering load-risk-emergency multi-source data

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Authors

Li Junhui Affiliation:
Nanning Power Supply Bureau, Guangxi Power Grid Co., LTD, China
, Wang Yu Affiliation:
Nanning Power Supply Bureau, Guangxi Power Grid Co., LTD, China
, Mo Liangyuan Affiliation:
Nanning Power Supply Bureau, Guangxi Power Grid Co., LTD, China
, Wei Zongchun Affiliation:
Nanning Power Supply Bureau, Guangxi Power Grid Co., LTD, China
, Yang Jing Affiliation:
Nanning Power Supply Bureau, Guangxi Power Grid Co., LTD, China
and Luo Hui Affiliation:
Nanning Power Supply Bureau, Guangxi Power Grid Co., LTD, China


Abstract

Power supply stability analysis is an important research content of power system planning, design, and operation. It provides a theoretical basis for ensuring the safe, reliable, and stable operation of power systems, to meet the needs of power users, and has important practical significance. The traditional analysis method based on a single data source makes it difficult to accurately describe the various factors affecting the stability of the power supply, and the increase of nonlinear load reduces the stability of the system. In this paper, a power supply stability analysis method based on the comprehensive consideration of load-risk-emergency multi-source data is proposed. Based on load-side Fourier analysis, the power supply stability of the system is analyzed and evaluated by a repeated control model, which lays a foundation for further research on the influence of load-risk-emergency multiple factors on the power supply stability of the grid.


Keywords

Harmonics, stability, multi-data, nonlinear load, power system, 93C95


Citation

Junhui, L., Yu, W., Liangyuan, M., Zongchun, W., Jing, Y., & Hui, L. (2026). Power supply stability analysis of power networks considering load-risk-emergency multi-source data. Applied Mathematics and Nonlinear Sciences, 11(1). https://doi.org/10.2478/amns-2025-0144

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