Research on Hybrid Maintenance Cost Prediction of Smart Grid Based on Multi-dimensional Information

被引:0
|
作者
Wang, Ying [1 ]
Zhu, Xuemei [1 ]
Ke, Ye [1 ]
Zheng, Chenhong [1 ]
Zhang, Shiming [1 ]
机构
[1] State Grid Fujian Power Econ Res Inst, Fuzhou 350000, Peoples R China
关键词
Multidimensional mixed information; Power grid maintenance; Intelligent maintenance; Grid information; Maintenance cost; Cost forecast;
D O I
10.1007/978-3-031-28787-9_24
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
At present, the change of equipment state is not considered in the prediction of power grid maintenance cost, which leads to inaccurate prediction results. Based on multi-dimensional mixed information, a prediction method of power grid intelligent maintenance cost is proposed. According to the expenses of routine maintenance of various equipment, the intelligent maintenance cost of power grid is divided into routine maintenance and power supply loss cost. The CS algorithm is used to determine the maintenance strategy of power grid equipment, so as to obtain the maximum power grid income under the minimum maintenance cost. The multidimensional mixed information extracted from the daily operation of smart grid determines the maintenance status of equipment in the maintenance strategy. Through the methods of grey prediction and multiple linear regression prediction, the diversified prediction results are output, and then the weighted value of the prediction output results is assigned with the help of the combined prediction model to realize the cost prediction of multi-dimensional indicators. The experimental results show that the intelligent maintenance cost prediction of power grid based on multi-dimensional mixed information can improve the prediction accuracy and contribute to the lean management of power enterprises. Further improve the efficiency and benefit of the multi-dimensional index linkage budget method, promote the digital transformation of power grid enterprises, and provide reference for power supply enterprises.
引用
收藏
页码:313 / 326
页数:14
相关论文
共 50 条
  • [21] Smart Multi-dimensional Gas Chromatography
    Fan, Xudong
    2013 IEEE SENSORS, 2013, : 5 - 7
  • [22] Research on Community Discovery Algorithm Based on Network Structure and Multi-dimensional User Information
    Wang, Liu
    He, Yi
    Mao, Chengjie
    Mao, Dan
    Yang, Zuoxi
    Li, Ying
    COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING, CHINESECSCW 2019, 2019, 1042 : 418 - 428
  • [23] Research on Sensor State Evaluation and Fault Diagnosis based on Multi-dimensional Information Fusion
    Yu, Xiaobo
    OPTOELECTRONIC MATERIALS AND DEVICES (ICOMD 2020), 2021, 11767
  • [24] Research on the knowledge-based multi-dimensional information model of manufacturing capability in CMfg
    Luo, Yongliang
    Zhang, Lin
    Zhang, Kuiping
    Tao, Fei
    ADVANCED MANUFACTURING TECHNOLOGY, PTS 1-4, 2012, 472-475 : 2592 - 2595
  • [25] Efficient Privacy-Preserving Multi-Dimensional Data Aggregation Scheme in Smart Grid
    Ming, Yang
    Zhang, Xuanyi
    Shen, Xiaoqin
    IEEE ACCESS, 2019, 7 : 32907 - 32921
  • [26] Multi-dimensional moving pattern prediction based on multi-dimensional interval T-S fuzzy model
    Sun C.-P.
    Xu Z.-G.
    Sun, Chang-Ping (sunchangping2000@sina.com.cn), 2016, Northeast University (31): : 1569 - 1576
  • [27] Research on multi-dimensional logistics based on the internet of things
    Gan, Quan
    Open Automation and Control Systems Journal, 2015, 7 (01): : 2051 - 2056
  • [28] Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory
    Zhang, Shoujing
    Tong, Fujiao
    Li, Mengdan
    Jin, Shoufeng
    Li, Zhixiong
    ENTROPY, 2021, 23 (05)
  • [29] Multi-dimensional approach for measuring logical couplings to decrease software development and maintenance cost
    Kim, Suntae
    Shim, Bingu
    Kim, Jeong Ah
    ASIA LIFE SCIENCES, 2015, : 549 - 561
  • [30] Research on Dynamic Community Detection Method Based on Multi-dimensional Feature Information of Community Network
    Hu, Kui
    Zhang, Zhenyu
    Li, Xiaoming
    TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2024 WORKSHOPS, RAFDA AND IWTA, 2024, 14658 : 44 - 56