On-line Voltage Instability Prediction using an Artificial Neural Network (ACCEPTED for presentation)
Paper i proceeding, 2019

In this paper, a predictive method to detect voltage instability using an artificial neural network is presented. The proposed method allows transmission  system operators to predict long-term voltage instability far before the system voltage stability has been degraded, allowing swift and cost-effective control actions. The predictor is tested and trained on the Nordic32 test system for a wide range of different contingencies. The predictor proves to be accurate in providing early warnings of impending voltage instability, allowing 96.3 % of all test cases being correctly classified only seconds after a contingency. The method is proposed to be used as an effective tool for supplementary voltage instability detection for transmission system operators.

voltage stability

emergency control

synchronized phasor measurements

artificial neural networks

Voltage instability prediction


Hannes Hagmar

Chalmers, Elektroteknik, Elkraftteknik, Elnät och komponenter

Anh Tuan Le

Chalmers, Elektroteknik, Elkraftteknik, Elnät och komponenter

Ola Carlson

Chalmers, Elektroteknik, Elkraftteknik, Elnät och komponenter

Robert Eriksson

Svenska kraftnät

IEEE PES Powertech 2019
Milano, Italy,

Avancerad visualisering av spänningsstabilitetsgränser och systemskydd baserat på realtidsmätningar

Svenska kraftnät, 2016-06-01 -- 2020-12-31.

Energimyndigheten, 2016-06-01 -- 2020-12-31.


Hållbar utveckling


Annan teknik

Elektroteknik och elektronik

Annan elektroteknik och elektronik



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