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EarlyWarn - Proactive detection and early warning of incipient power system faults


The EarlyWarn project addresses the need for improved real-time monitoring and state assessment in the transmission and distribution grid. The project will develop models for prediction and identification of incipient component failures and system instabilities, exploiting recent advances in machine learning and Big Data technology to continuously and in real-time monitor and analyze large streams of grid sensor data from synchrophasors and power quality analyzers. The project will bring together expertise in power systems and ICT from SINTEF and NTNU, as well as from grid operators at both transmission and distribution level. The consortium partners are continuosly collecting the sensor data that will drive the development of algorithms and tools, thus ensuring real-life relevance and value of the research. The project will contribute to the long-term plan for science and education through the education of two PhDs cooperating on cross-disciplinary and strategically important topics.

Project leader: Christian André Andresen

Started: 2017

Ends: 2021

Category: Teknisk-industrielle institutter

Sector: Instituttsektor

Budget: 6334000


Address: Trondheim