Research on the Path of Smart Grid Data Assetization
- DOI
- 10.2991/978-94-6463-102-9_50How to use a DOI?
- Keywords
- Smart Grid; Data Assetization; Data Value-added; Value Assessment; Exchange Model
- Abstract
With the advancement of the digital strategic transformation of power enterprise, how to efficiently use massive smart grid data to serve society and benefit enterprises has become a hot spot in industry research. By transforming data resources into effective data assets, more comprehensive analysis, more accurate prediction, and more valuable decision support can be implemented, which would maximize the data value and benefit appreciation. This article reviews the current situation and challenges of smart grid data assetization, and proposes the realizing path of smart grid data assetization based on the nature of smart grid data and its value-added method. The value assessment and transaction of smart grid data assets are the key links in the path. This article also presents the implementation method of the evaluation system and exchange model of smart grid data assets, which helps boost revenue for the power industry.
- Copyright
- © 2023 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 - Wen Chen AU - Jigang Zhang AU - Liangzheng Wu AU - Zeyuan Yu PY - 2022 DA - 2022/12/29 TI - Research on the Path of Smart Grid Data Assetization BT - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022) PB - Atlantis Press SP - 466 EP - 480 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-102-9_50 DO - 10.2991/978-94-6463-102-9_50 ID - Chen2022 ER -