Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM

Md Mujahid Irfan; S. M.Suhail Hussain

doi:10.1109/GlobConET56651.2023.10150073

Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM

Md Mujahid Irfan^*
, S. M.Suhail Hussain

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Distribution static compensator (DSTATCOM) is a shunt custom power device that is often used to address power quality issues in distribution systems. The control scheme of the DSTATCOM plays a vital role in managing the reactive power by injecting current to stabilize voltage at the point of common coupling. This work presents Deep Learning (DL) based novel control technique for the grid interactive hybrid PV-Wind system to mitigate the harmonics caused by non-linear loads. The harmonic analysis of the proposed system is tested and compared before and after compensation. The results obtained for the proposed control technique for the hybrid system clearly projects its efficiency in the improvement of power quality. Total harmonic distortion (THD) obtained by the proposed control technique for the hybrid system is much lesser compared to PV and Wind isolated systems.

Original language	English
Title of host publication	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350331790
DOIs	https://doi.org/10.1109/GlobConET56651.2023.10150073
State	Published - 2023
Event	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023 - London, United Kingdom Duration: 19 May 2023 → 21 May 2023

Publication series

Name	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

Conference

Conference	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023
Country/Territory	United Kingdom
City	London
Period	19/05/23 → 21/05/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

DSTATCOM and Non-linear loads
Deep learning
Hybrid system
Solar PV
Wind

ASJC Scopus subject areas

Artificial Intelligence
Computer Vision and Pattern Recognition
Information Systems and Management
Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Safety, Risk, Reliability and Quality
Control and Optimization

Access to Document

10.1109/GlobConET56651.2023.10150073

Cite this

Irfan, M. M., & Hussain, S. M. S. (2023). Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM. In 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023 (2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobConET56651.2023.10150073

Irfan, Md Mujahid ; Hussain, S. M.Suhail. / Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM. 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023).

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title = "Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM",

abstract = "Distribution static compensator (DSTATCOM) is a shunt custom power device that is often used to address power quality issues in distribution systems. The control scheme of the DSTATCOM plays a vital role in managing the reactive power by injecting current to stabilize voltage at the point of common coupling. This work presents Deep Learning (DL) based novel control technique for the grid interactive hybrid PV-Wind system to mitigate the harmonics caused by non-linear loads. The harmonic analysis of the proposed system is tested and compared before and after compensation. The results obtained for the proposed control technique for the hybrid system clearly projects its efficiency in the improvement of power quality. Total harmonic distortion (THD) obtained by the proposed control technique for the hybrid system is much lesser compared to PV and Wind isolated systems.",

keywords = "DSTATCOM and Non-linear loads, Deep learning, Hybrid system, Solar PV, Wind",

author = "Irfan, \{Md Mujahid\} and Hussain, \{S. M.Suhail\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023 ; Conference date: 19-05-2023 Through 21-05-2023",

year = "2023",

doi = "10.1109/GlobConET56651.2023.10150073",

language = "English",

series = "2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Irfan, MM & Hussain, SMS 2023, Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM. in 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023, London, United Kingdom, 19/05/23. https://doi.org/10.1109/GlobConET56651.2023.10150073

Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM. / Irfan, Md Mujahid; Hussain, S. M.Suhail.
2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM

AU - Irfan, Md Mujahid

AU - Hussain, S. M.Suhail

PY - 2023

Y1 - 2023

N2 - Distribution static compensator (DSTATCOM) is a shunt custom power device that is often used to address power quality issues in distribution systems. The control scheme of the DSTATCOM plays a vital role in managing the reactive power by injecting current to stabilize voltage at the point of common coupling. This work presents Deep Learning (DL) based novel control technique for the grid interactive hybrid PV-Wind system to mitigate the harmonics caused by non-linear loads. The harmonic analysis of the proposed system is tested and compared before and after compensation. The results obtained for the proposed control technique for the hybrid system clearly projects its efficiency in the improvement of power quality. Total harmonic distortion (THD) obtained by the proposed control technique for the hybrid system is much lesser compared to PV and Wind isolated systems.

AB - Distribution static compensator (DSTATCOM) is a shunt custom power device that is often used to address power quality issues in distribution systems. The control scheme of the DSTATCOM plays a vital role in managing the reactive power by injecting current to stabilize voltage at the point of common coupling. This work presents Deep Learning (DL) based novel control technique for the grid interactive hybrid PV-Wind system to mitigate the harmonics caused by non-linear loads. The harmonic analysis of the proposed system is tested and compared before and after compensation. The results obtained for the proposed control technique for the hybrid system clearly projects its efficiency in the improvement of power quality. Total harmonic distortion (THD) obtained by the proposed control technique for the hybrid system is much lesser compared to PV and Wind isolated systems.

KW - DSTATCOM and Non-linear loads

KW - Deep learning

KW - Hybrid system

KW - Solar PV

KW - Wind

UR - https://www.scopus.com/pages/publications/85164255797

U2 - 10.1109/GlobConET56651.2023.10150073

DO - 10.1109/GlobConET56651.2023.10150073

M3 - Conference contribution

AN - SCOPUS:85164255797

T3 - 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

BT - 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

Y2 - 19 May 2023 through 21 May 2023

ER -

Irfan MM, Hussain SMS. Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM. In 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023). doi: 10.1109/GlobConET56651.2023.10150073

Harmonic Mitigation in PV-Wind Hybrid System with Non-Linear Loads using Deep Learning Algorithm Controlled DSTATCOM

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this