Mathematical methods for main tenance and operation cost prediction based on transfer learning in State Grid

作     者：GUO Yun-peng WANG Dong-fa ZHENG Ying DING Wei-bin GUO Yun-peng;WANG Dong-fa;ZHENG Ying;DING Wei-bin

作者机构：State Grid Zhejiang Electric Power Company Jinhua Power Supply CompanyJinhua 321000China State Grid Zhejiang Electric Power CompanyHangzhou 310018China 

出 版 物：《Applied Mathematics(A Journal of Chinese Universities)》 (高校应用数学学报（英文版）（B辑）)

年 卷 期：2022年第37卷第4期

页      面：598-614页

核心收录：

学科分类：0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 081104[工学-模式识别与智能系统] 0811[工学-控制科学与工程] 0701[理学-数学] 

基　　金：Supported by the program of science and technology of State Grid Zhejiang Electric Power Co. Ltd. named Research and application project of standard cost activity based on machine learning(5211JH1900LZ). 

主　　题：transfer learning LSTM support vector regression activity based costing State Grid 

摘      要：The electric power enterprise is an important basic energy industry for national development,and it is also the first basic industry of the national economy.With the continuous expansion of State Grid,the progressively complex operating conditions,and the increasing scope and frequency of data collection,how to make reasonable use of electrical big data,improve utilization,and provide a theoretical basis for the reliability of State Grid operation,has become a new research hot spot.Since electrical data has the characteristics of large volume,multiple types,low-value density,and fast processing speed,it is a challenge to mine and analyze it deeply,extract valuable information efficiently,and serve for the actual problem.According to the features of these data,this paper uses artificial intelligence methods such as time series and support vector regression to establish a data mining network model for standard cost prediction through transfer learning.The experimental results show that the model in this paper obtains better prediction results on a small sample data set,which verifies the feasibility of the deep transfer model.Compared with activity-based costing and the traditional prediction method,the average absolute error of the proposed method is reduced by 10%,which is effective and superior.