Hannes Hagmar

Doctoral Student at Electric Power Engineering

Hannes Hagmar is a PhD student at the division of Electric Power Engineering. In his research he develops a new system with the aim to decrease the transmission reliability margins in the transmission grid. This is achieved by using real-time measurements and developing enhanced system protection schemes and visualization of voltage stability limits. The project is conducted in cooperation with Svenska Kraftnät with support from RISE Research Institute of Sweden.

Source: chalmers.se
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Showing 10 publications

2022

Deep Reinforcement Learning for Long-Term Voltage Stability Control

Hannes Hagmar, Anh Tuan Le, Robert Eriksson
11th Bulk Power Systems Dynamics and Control Symposium (IREP 2022)
Paper in proceeding
2022

Impact of static and dynamic load models on security margin estimation methods

Hannes Hagmar, Anh Tuan Le, Robert Eriksson
Electric Power Systems Research. Vol. 202
Journal article
2021

Real-time Security Margin Control Using Deep Reinforcement Learning

Hannes Hagmar, Robert Eriksson, Anh Tuan Le
Preprint
2021

Voltage Instability Prediction Using a Deep Recurrent Neural Network

Hannes Hagmar, Lang Tong, Robert Eriksson et al
IEEE Transactions on Power Systems. Vol. 36 (1), p. 17-27
Journal article
2020

Fast dynamic voltage security marginestimation: concept and development

Hannes Hagmar, Robert Eriksson, Anh Tuan Le
IET Smart Grid. Vol. 3 (4), p. 470-478
Journal article
2019

Integration Aspects of Full Converter Wind Turbines and the Impact on Long-term Voltage Stability

Hannes Hagmar, Anh Tuan Le, Ola Carlson et al
IEEE PES General Meeting
Paper in proceeding
2019

On-line Voltage Instability Prediction using an Artificial Neural Network

Hannes Hagmar, Anh Tuan Le, Ola Carlson et al
2019 IEEE Milan PowerTech, PowerTech 2019
Paper in proceeding
2019

A Survey of Voltage Stability Indicators Based on Local Synchronized Phasor Measurements

Hannes Hagmar, Anh Tuan Le, Ola Carlson et al
2018 North American Power Symposium (NAPS)
Paper in proceeding

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Showing 2 research projects

2021–2022

Machine Learning-based Real-Time Optimal Control for Sustainable and Secure Power Systems

Hannes Hagmar Power grids and Components
Anh Tuan Le Power grids and Components
Swedish national grid
Energiforsk AB

2017–2021

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

Anh Tuan Le Electric Power Engineering
Hannes Hagmar Electric Power Engineering
Ola Carlson Electric Power Engineering
Swedish national grid
Swedish Energy Agency

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