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Details

Autor(en) / Beteiligte
Titel
State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data
Ist Teil von
  • International journal of electrical power & energy systems, 2022-05, Vol.137, p.107772, Article 107772
Ort / Verlag
United States: Elsevier Ltd
Erscheinungsjahr
2022
Link zum Volltext
Quelle
Elsevier ScienceDirect Journals Complete
Beschreibungen/Notizen
  • •Results of survey to 10 transmission system operators from 8 countries.•Outline of the most important current challenges handling data in control rooms.•Description of situation with respect to artificial intelligence and machine learning applications.•Differences among utilities based on geographical, political and economic situation.•List of real needs that TSOs would like to have in operation. Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities to monitor the system dynamic performance in real-time at fast time scales. The use of such technologies has unlocked new opportunities to introduce new data driven algorithms for improving the stability assessment and control of the system. Motivated by these challenges, a group of experts have worked together to highlight and establish a baseline set of these common concerns, which can be used as motivation to propose innovative analytics and data-driven solutions. In this document, the results of a survey on 10 transmission system operators around the world are presented and it aims to understand the current practices of the participating companies, in terms of data acquisition, handling, storage, modelling and analytics. The overall objective of this document is to capture the actual needs from the interviewed utilities, thereby laying the groundwork for setting valid assumptions for the development of advanced algorithms in this field.

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