Title: Design of online error monitoring system for capacitive voltage transformer based on LightGBM and PSO

Authors: Pengcheng Li; Zhiyi Qu; Longxiang Wei; Xiujiang Yang

Addresses: Measurement Centre of Guizhou Power Grid Company, Guiyang, Guizhou, China ' Measurement Centre of Guizhou Power Grid Company, Guiyang, Guizhou, China ' Measurement Centre of Guizhou Power Grid Company, Guiyang, Guizhou, China ' Measurement Centre of Guizhou Power Grid Company, Guiyang, Guizhou, China

Abstract: This article introduces a new online error monitoring system for Capacitive Voltage Transformers (CVTs), which uses Light Gradient Boosting Machines (LightGBM) and Particle Swarm Optimisation (PSO). The LightGBM model adopts mutual exclusive feature grouping methods and gradient-based instance selection strategies that can reflect complicated non-linear relationships among CVTs' measurement errors and their influencing factors. The PSO algorithm adds a self-adaptive inertia weight strategy to optimise the weights of each model adequately to get the best possible error estimates. The proposed method achieved higher accuracy of prediction than any other methods under the same condition besides consuming less time and being more robust against noise disturbances while having better extensibility. The proposed online error monitoring system offers a reliable and efficient solution for ensuring the accuracy and stability of electrical energy measurement in power systems, enabling proactive maintenance strategies and enhancing the overall reliability of the power grid.

Keywords: capacitive voltage transformer; online error monitoring; LightGBM; particle swarm optimisation; combined prediction model.

DOI: 10.1504/IJCAT.2025.150334

International Journal of Computer Applications in Technology, 2025 Vol.77 No.3/4, pp.159 - 173

Received: 06 Jul 2024
Accepted: 26 Nov 2024
Published online: 09 Dec 2025 *

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