Research on optimization method and system of power display data based on digital twin
- DOI
- 10.2991/978-94-6463-552-2_12How to use a DOI?
- Keywords
- digital twin; Power display data; Optimization method; System
- Abstract
With the development of science and technology and the progress of society, the electric power industry is gradually changing to the direction of intelligence and automation. In this process, a large amount of power data is generated and processed and analyzed. The data includes not only real-time data on electricity production, transmission and consumption, but also historical data, forecast data, and data derived from analysis through various algorithms. However, how to effectively display these power data so that people can intuitively and vividly understand and grasp them has always been a difficult problem facing the power industry. Traditional power data display methods, such as tables, charts, trend charts, etc., can reflect some characteristics of power data to a certain extent, but there are some inherent limitations, resulting in low efficiency in dealing with power business.
- Copyright
- © 2024 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 - Dan Li AU - Tong Wu AU - Zhihan Lang PY - 2024 DA - 2024/10/27 TI - Research on optimization method and system of power display data based on digital twin BT - Proceedings of the 4th International Conference on Management Science and Software Engineering (ICMSSE 2024) PB - Atlantis Press SP - 118 EP - 129 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-552-2_12 DO - 10.2991/978-94-6463-552-2_12 ID - Li2024 ER -