On-line Voltage Instability Prediction using an Artificial Neural Network
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.

synchronized phasor measurements

emergency control

voltage stability

Voltage instability prediction

artificial neural networks

Författare

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

2019 IEEE Milan PowerTech, PowerTech 2019

8810808

IEEE PES Powertech 2019
Milano, Italy,

Avancerad visualisering av spänningsstabilitetsgränser och systemskydd baserat på realtidsmätningar

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

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

Drivkrafter

Hållbar utveckling

Ämneskategorier

Annan teknik

Elektroteknik och elektronik

Annan elektroteknik och elektronik

Styrkeområden

Energi

DOI

10.1109/PTC.2019.8810808

Mer information

Senast uppdaterat

2020-07-30