State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data

Segundo Sevilla, Felix Rafael y Liu, Yanli y Barocio, Emilio y Korba, Petr y Andrade, Manuel y Bellizio, Federica y Bos, Jorrit y Chaudhuri, Balarko y Chavez, Hector y Cremer, Jochen y Eriksson, Robert y Hamon, Camille y Herrera, Miguel y Huijsman, Marnick y Ingram, Michael y Klaar, Danny y Krishnan, Venkat y Mola, Jorge y Netto, Marcos y Paolone, Mario y Papadopoulos, Panagiotis y Ramirez, Miguel y Rueda, Jose y Sattinger, Walter y Terzija, Vladimir y Tindemans, Simon y Trigueros, Alberto y Wang, Yajun y Zhao, Junbo (2022) State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data. International journal of electrical power & energy systems, 137. p. 107772. ISSN 0142-0615

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Resumen

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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