Research Article
Investment Forecast for Power Grid Technical Renovation Projects Based on Angle of Inclination Correlation and Improved Gray Model
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342721, author={Yue Zhang and Yang Xiao and Lilan Deng and Wenyu Yan}, title={Investment Forecast for Power Grid Technical Renovation Projects Based on Angle of Inclination Correlation and Improved Gray Model}, proceedings={Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17--19, 2023, Beijing, China}, publisher={EAI}, proceedings_a={ICEMME}, year={2024}, month={2}, keywords={investment forecast; angle of inclination correlation; improved gray model; power grid technical renovation projects}, doi={10.4108/eai.17-11-2023.2342721} }- Yue Zhang
Yang Xiao
Lilan Deng
Wenyu Yan
Year: 2024
Investment Forecast for Power Grid Technical Renovation Projects Based on Angle of Inclination Correlation and Improved Gray Model
ICEMME
EAI
DOI: 10.4108/eai.17-11-2023.2342721
Abstract
This paper introduces an innovative method for forecasting investments in power grid technical renovation projects. By employing the Angle of Inclination Correlation and an Enhanced Gray Model, our goal is to enhance investment prediction accuracy in the electric power industry. Using data from 2016-2021, we select key indicators, such as maximum grid load, power supply capacity, line length renovations, electricity sales revenue, installed capacity, line loss rate, unit substation capacity cost, and power supply reliability, to evaluate their impact on technical renovation projects. The Improved Gray Model is then used to forecast 2022 investments. Subsequently, a Markov model is applied to refine predictions and calculate the deviation rate, confirming the method's effectiveness in indicator selection. While this approach holds promise, it is essential to acknowledge the limitations of historical data, which do not meet big data requirements.
