Research on Optimization Methods for Physical Asset Management of Distribution Networks
- DOI
- 10.2991/978-94-6463-780-9_24How to use a DOI?
- Keywords
- Distribution network; physical asset management; fault classification; repair cost prediction; interval regression; resource optimization
- Abstract
With the expansion and increasing complexity of distribution networks, physical asset management faces challenges like frequent faults and uncertain repair costs. This paper proposes an optimization method combining improved clustering analysis and interval regression to address these issues. Clustering historical fault data identifies patterns in fault types, while interval regression predicts repair cost ranges, providing upper and lower bounds for resource planning. Case studies demonstrate that the proposed method improves fault classification, accurately forecasts repair costs, and optimizes resource allocation. The findings support cost-effective, efficient asset management, offering theoretical and practical value for power grid enterprises.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Mingli Wang AU - Qin Qiu AU - Jiuming Wang AU - Chao Liu PY - 2025 DA - 2025/07/03 TI - Research on Optimization Methods for Physical Asset Management of Distribution Networks BT - Proceedings of the 2025 International Conference on Engineering Management and Safety Engineering (EMSE 2025) PB - Atlantis Press SP - 244 EP - 254 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-780-9_24 DO - 10.2991/978-94-6463-780-9_24 ID - Wang2025 ER -