On-line Voltage Instability Prediction using an Artificial Neural Network (ACCEPTED for presentation)
Paper in proceedings, 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

Author

Hannes Hagmar

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Anh Tuan Le

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Ola Carlson

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Robert Eriksson

Swedish national grid

IEEE PES Powertech 2019
Milano, Italy,

Advanced visualization of voltage stability limit and system protection based on real-time measurement

Swedish Energy Agency, 2016-06-01 -- 2020-12-31.

Swedish national grid, 2016-06-01 -- 2020-12-31.

Driving Forces

Sustainable development

Subject Categories

Other Engineering and Technologies

Electrical Engineering, Electronic Engineering, Information Engineering

Other Electrical Engineering, Electronic Engineering, Information Engineering

Areas of Advance

Energy

More information

Created

3/16/2019