Transmission Technical Project Investment Forecasting Under the High-dimension Small Sample Conditions

• Published in: IOP conference series. Materials Science and Engineering Vol. 768; no. 6; pp. 62065 - 62070
• Main Authors: Wang, Mianbin, Qi, Xia, Geng, Pengyun, An, Lei, Wang, Jianjun
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.03.2020
• Subjects: Economic forecasting; Electric power grids; Electricity distribution; Mathematical models; Principal components analysis; Transformations
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/768/6/062065

The electricity market will realize the separation of transmission and distribution, in the new environment, the main profit model of the power grid company will be dominated by transmission and distribution services, it will require the grid company to control its investment and cost accuracy. As a routine maintenance work to ensure the safe and stable transportation of electric energy, the grid technical transformation project has a great impact of the grid operation cost. Due to the lack of the history data, it is difficult to forecast the project's investment, and the current investment always relies on experience. It needs to construct a quantitative forecasting model to make scientific and objective predictions of investment in technological transformation projects. In this paper, the principal component analysis (PCA) is employed to analysed the history data, then the main factors are obtained, which are used as input variables into SVM models. Finally, from a case study of a certain grid company, the proposed PCASVM forecasting model has better performance on the grid technology transformation project investment prediction, it confirms the effectiveness of the proposed method.