Azam Bagheri

Post doc at Electric Power Engineering

Azam Bagheri is a postdoc in the research group Electrical Machines and Power Electronics, division Electric Power Engineering, focusing her research on developing mathematical methods for on-line parameter estimation. Azam is involved in a project related to Remote sensing for active online parameter estimation in digital power grids. The aim of her research is to conduct analytical methods for estimating the frequency dependent impedance in both steady-state and transient conditions. The research will consider the application of the estimated impedance to improve the control of power-electronic based converters and consequently increasing the stability and the reliability of the whole power system.

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Showing 7 publications


Estimation of frequency-dependent impedances in power grids by deep lstm autoencoder and random forest

Azam Bagheri, Massimo Bongiorno, Irene Yu-Hua Gu et al
Energies. Vol. 14 (13)
Journal article

A Novel Model for Emotion Detection from Facial Muscles Activity

Elahe Bagheri, Azam Bagheri, Pablo G. Esteban et al
Advances in Intelligent Systems and Computing. Vol. 1093, p. 237-249
Paper in proceeding

Susceptibility of LED street lamps to voltage dips

S. Sakar, Azam Bagheri, S. Ronnberg et al
Lighting Research and Technology. Vol. 52 (8), p. 1040-1056
Journal article

A Novel DTC-based Control Method of Flywheel System to Improve Fault-Ride Through Capability of the Microgrids

Mehdi Ghasemi, Azam Bagheri, Massimo Bongiorno
Other conference contribution

A novel application of flywheel system to enhance fault-ride-through of the microgrids

Mehdi Ghasemi, Azam Bagheri, Massimo Bongiorno et al
NEIS 2019 - Conference on Sustainable Energy Supply and Energy Storage Systems, p. 146-151
Paper in proceeding

A Robust Transform-Domain Deep Convolutional Network for Voltage Dip Classification

Azam Bagheri, Irene Yu-Hua Gu, Math Bollen et al
IEEE Transactions on Power Delivery. Vol. 33 (6), p. 2794-2802
Journal article

Big data from smart grids

Azam Bagheri, Mathias Bollen, Irene Yu-Hua Gu
IEEE PES Innovative smart grid technologies, Europe Conf. (ISGT Europe 2017). Vol. 2018-January, p. 1-5
Paper in proceeding

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