@inproceedings{5e2c8518da9e43b29d6aad023fd0d461,
title = "Review of Power Spatio-Temporal Big Data Technologies, Applications, and Challenges",
abstract = "The spatio-temporal big data of the power grid has experienced explosive growth, especially the development of various power sensors, smart devices, communication devices, and real-time processing hardware, which has led to unprecedented opportunities and challenges in this field. This paper firstly introduces Power Spatio-Temporal Big Data (PSTBD) technologies based on the characteristics of grid spatio-temporal big data, followed by a comprehensive survey of relevant articles analysis in this field. Then we compare the difference between traditional power grid and PSTBD platform, and focus on the key technologies of current PSTBD and corresponding typical applications. Finally, the development direction and challenges of PSTBD are given. Through data analysis and technical discussion, we provided technical supports and decision supports for relevant practitioners in PSTBD field.",
keywords = "Big data, Power grid, Security control, Sensors, Spatio-temporal",
author = "Ying Ma and Chao Huang and Yu Sun and Guang Zhao and Yunjie Lei",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage, SpaCCS 2019 ; Conference date: 14-07-2019 Through 17-07-2019",
year = "2019",
doi = "10.1007/978-3-030-24900-7\_16",
language = "英语",
isbn = "9783030248994",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "197--206",
editor = "Guojun Wang and Jun Feng and Bhuiyan, \{Md Zakirul Alam\} and Rongxing Lu",
booktitle = "Security, Privacy, and Anonymity in Computation, Communication, and Storage - SpaCCS 2019 International Workshops, Proceedings",
address = "德国",
}