Title: Short-term load forecasting technique for power system based on grey correlation analysis and factor analysis

Authors: Xiaoguo Zhang

Addresses: School of Mathematics and Physics, Henan University of Urban Construction, Pingdingshan, 467036, China

Abstract: Aiming at the problem that traditional load forecasting techniques cannot achieve higher forecasting accuracy, a short-term load forecasting technique for power systems based on grey correlation analysis and factor analysis is proposed. Grey correlation analysis is introduced to determine the key load factors, and the forecasting circuit is designed by combining the data from the grid visualisation system. Secondly, the main influencing factors are extracted to form a composite factor by dimensionality reduction through factor analysis. Experiments show that the model performs well in predicting different date types and zone. The difference between the model predicted and true values was less than 0.6%. The results show that the load forecasting technique proposed in the study has high accuracy and stability, which provides a strong support for the stable operation and planning of the power system.

Keywords: power system; short-term load forecasting; STLF; grey correlation analysis; GCA; factor analysis; grid visualisation management.

DOI: 10.1504/IJPT.2025.147115

International Journal of Powertrains, 2025 Vol.14 No.1, pp.78 - 96

Received: 21 Jan 2025
Accepted: 27 Apr 2025
Published online: 10 Jul 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article