Research Article
Research on Hybrid Maintenance Cost Prediction of Smart Grid Based on Multi-dimensional Information
@INPROCEEDINGS{10.1007/978-3-031-28787-9_24, author={Ying Wang and Xuemei Zhu and Ye Ke and Chenhong Zheng and Shiming Zhang}, title={Research on Hybrid Maintenance Cost Prediction of Smart Grid Based on Multi-dimensional Information}, proceedings={Advanced Hybrid Information Processing. 6th EAI International Conference, ADHIP 2022, Changsha, China, September 29-30, 2022, Proceedings, Part I}, proceedings_a={ADHIP}, year={2023}, month={3}, keywords={Multidimensional mixed information Power grid maintenance Intelligent maintenance Grid information Maintenance cost Cost forecast}, doi={10.1007/978-3-031-28787-9_24} }- Ying Wang
Xuemei Zhu
Ye Ke
Chenhong Zheng
Shiming Zhang
Year: 2023
Research on Hybrid Maintenance Cost Prediction of Smart Grid Based on Multi-dimensional Information
ADHIP
Springer
DOI: 10.1007/978-3-031-28787-9_24
Abstract
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.
