Research on Investment Prediction Technology of Distribution Network of 110kV and Below Based on Grey Model Optimization

With the rapid development of the economy, the scale of power grid construction has increased, but at the same time, it is also facing problems such as obsolete power grid equipment and line damage, so it is very important for the sustainable development of power grid enterprises to carry out reasonable technical transformation of the power grid and ensure the reliable operation of the power grid system. However, in the power grid technical transformation investment decision-making, mainly rely on the power grid company professional and technical personnel from the past historical experience, select a few theoretically and power grid technical transformation investment related indicators, through a simple regression analysis to obtain the technical transformation investment prediction value, such a decision-making method is difficult to meet the actual demand, so in-depth analysis of the main influencing factors of investment capacity, to adopt an accurate and reasonable investment forecast model, is the key to the current power grid technical transformation investment forecast. Therefore, this paper proposes a technology for predicting the investment of power grid technical transformation project based on Markov optimization gray model parameters, and verifies that the prediction accuracy of the proposed algorithm is improved by 5.21% compared with the traditional gray GM(1,N) prediction model, which is significantly improved

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Publication Details

Journal
Advances in computer and materials science research.
Published
2025-03-07
DOI
https://doi.org/10.70114/acmsr.2025.2.1.p274
Primary Topic
Power Systems and Technologies
Type
article
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article

Research on Investment Prediction Technology of Distribution Network of 110kV and Below Based on Grey Model Optimization

Jianqing Li, Fan Yang, Yue Tang, Shili Liu
Advances in computer and materials science research.
Power Systems and Technologies
article

Research on Investment Prediction Technology of Distribution Network of 110kV and Below Based on Grey Model Optimization

Jianqing Li, Fan Yang, Yue Tang, Shili Liu
article en

Abstract

With the rapid development of the economy, the scale of power grid construction has increased, but at the same time, it is also facing problems such as obsolete power grid equipment and line damage, so it is very important for the sustainable development of power grid enterprises to carry out reasonable technical transformation of the power grid and ensure the reliable operation of the power grid system. However, in the power grid technical transformation investment decision-making, mainly rely on the power grid company professional and technical personnel from the past historical experience, select a few theoretically and power grid technical transformation investment related indicators, through a simple regression analysis to obtain the technical transformation investment prediction value, such a decision-making method is difficult to meet the actual demand, so in-depth analysis of the main influencing factors of investment capacity, to adopt an accurate and reasonable investment forecast model, is the key to the current power grid technical transformation investment forecast. Therefore, this paper proposes a technology for predicting the investment of power grid technical transformation project based on Markov optimization gray model parameters, and verifies that the prediction accuracy of the proposed algorithm is improved by 5.21% compared with the traditional gray GM(1,N) prediction model, which is significantly improved

Advances in computer and materials science research.Vol. 2(1)
Openalex Percentile: Top 97%
Power Systems and Technologies
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