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Comparative study of exponential composition algorithm under dynamic conditions

Publication Type : Conference Paper

Publisher : Proceedings of 2017 IEEE International Conference on Technological Advancements in Power and Energy: Exploring Energy Solutions for an Intelligent Power Grid, TAP Energy 2017

Source : Proceedings of 2017 IEEE International Conference on Technological Advancements in Power and Energy: Exploring Energy Solutions for an Intelligent Power Grid, TAP Energy 2017, Institute of Electrical and Electronics Engineers Inc., p.1-6 (2018)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050164934&doi=10.1109%2fTAPENERGY.2017.8397273&partnerID=40&md5=116d5a802af9dae7096289248bbede67

ISBN : 9781538640210

Keywords : Air conditioning, Comparative studies, Different operating conditions, Dynamic condition, Electric power systems, Electric power transmission networks, Elevators, harmonics, MATLAB, Matlab/Simulink software, power electronic devices, Power quality, Shunt active power filters, Variable frequency drives, Variable speed drives

Campus : Coimbatore

School : School of Engineering

Department : Electrical and Electronics

Year : 2018

Abstract : Majority of the industrial and commercial loads such as power converters, variable frequency drives, air conditioners, escalators, elevators, etc. incorporate a large number of power electronic devices. These loads introduce dynamic harmonic current, imbalance in the current and varying reactive power demand in the three phase AC mains supply. This paper presents a comparison of four shunt active filtering algorithms. The control algorithms are simulated and analyzed using the MATLAB/Simulink software under different operating conditions. © 2017 IEEE.

Cite this Research Publication : S. Sindhu, Dr. Sindhu M. R., and Nambiar, T. N. P., “Comparative study of exponential composition algorithm under dynamic conditions”, in Proceedings of 2017 IEEE International Conference on Technological Advancements in Power and Energy: Exploring Energy Solutions for an Intelligent Power Grid, TAP Energy 2017, 2018, pp. 1-6.

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