Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine

K. Moloi; B. A. Thango; A. F. Nnnachi; J. A. Jordaan; Y. Hamam

doi:10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221

Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine

K. Moloi
, B. A. Thango
, A. F. Nnnachi
, J. A. Jordaan
, Y. Hamam

Tshwane University of Technology

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

1 Citation (Scopus)

Abstract

The modern electricity society has seen an increase in the integration of renewable energy sources into the power grid. This has significantly improved the electricity supply and sustainability. However, there are technical challenges related to the power quality (PQ) analysis for grid integrated systems. In this paper, we propose a PQ detection technique using the discrete wavelet transform (DWT) and support vector machine (SVM). The DWT analysis technique is used to extract statistical features, which are used as input to train the SVM classifier. The parameters of the SVM are optimised using the harris hawks optimisation (HHO) algorithm. Various scenarios of cases which may affect the quality of network performance are investigated. These events include the voltage sag, voltage swell, notch, transient fault conditions and sudden load increment. The proposed method is validated using the modified practical Eskom network. The presented results show that the proposed scheme correctly classified different cases.

Original language	English
Title of host publication	2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9780738112367
DOIs	https://doi.org/10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221
Publication status	Published - 27 Jan 2021
Externally published	Yes
Event	2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021 - Virtual, Potchefstroom, South Africa Duration: 27 Jan 2021 → 29 Jan 2021

Publication series

Name	2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021

Conference

Conference	2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021
Country/Territory	South Africa
City	Virtual, Potchefstroom
Period	27/01/21 → 29/01/21

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Discrete Wavelet Transform
Power Quality Analysis
Renewable Energy Sources
Support Vector Machine

ASJC Scopus subject areas

Artificial Intelligence
Computer Vision and Pattern Recognition
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Mechanical Engineering

Access to Document

10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221

Cite this

Moloi, K., Thango, B. A., Nnnachi, A. F., Jordaan, J. A., & Hamam, Y. (2021). Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine. In 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021 Article 9377221 (2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221

Moloi, K. ; Thango, B. A. ; Nnnachi, A. F. et al. / Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine. 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021).

@inproceedings{5e5b5ce265974481a5ac2a93000c6e29,

title = "Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine",

abstract = "The modern electricity society has seen an increase in the integration of renewable energy sources into the power grid. This has significantly improved the electricity supply and sustainability. However, there are technical challenges related to the power quality (PQ) analysis for grid integrated systems. In this paper, we propose a PQ detection technique using the discrete wavelet transform (DWT) and support vector machine (SVM). The DWT analysis technique is used to extract statistical features, which are used as input to train the SVM classifier. The parameters of the SVM are optimised using the harris hawks optimisation (HHO) algorithm. Various scenarios of cases which may affect the quality of network performance are investigated. These events include the voltage sag, voltage swell, notch, transient fault conditions and sudden load increment. The proposed method is validated using the modified practical Eskom network. The presented results show that the proposed scheme correctly classified different cases.",

keywords = "Discrete Wavelet Transform, Power Quality Analysis, Renewable Energy Sources, Support Vector Machine",

author = "K. Moloi and Thango, \{B. A.\} and Nnnachi, \{A. F.\} and Jordaan, \{J. A.\} and Y. Hamam",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021 ; Conference date: 27-01-2021 Through 29-01-2021",

year = "2021",

month = jan,

day = "27",

doi = "10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221",

language = "English",

series = "2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021",

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

booktitle = "2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021",

address = "United States",

}

Moloi, K, Thango, BA, Nnnachi, AF, Jordaan, JA & Hamam, Y 2021, Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine. in 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021., 9377221, 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021, Institute of Electrical and Electronics Engineers Inc., 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021, Virtual, Potchefstroom, South Africa, 27/01/21. https://doi.org/10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221

Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine. / Moloi, K.; Thango, B. A.; Nnnachi, A. F. et al.
2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 9377221 (2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021).

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

TY - GEN

T1 - Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine

AU - Moloi, K.

AU - Thango, B. A.

AU - Nnnachi, A. F.

AU - Jordaan, J. A.

AU - Hamam, Y.

PY - 2021/1/27

Y1 - 2021/1/27

N2 - The modern electricity society has seen an increase in the integration of renewable energy sources into the power grid. This has significantly improved the electricity supply and sustainability. However, there are technical challenges related to the power quality (PQ) analysis for grid integrated systems. In this paper, we propose a PQ detection technique using the discrete wavelet transform (DWT) and support vector machine (SVM). The DWT analysis technique is used to extract statistical features, which are used as input to train the SVM classifier. The parameters of the SVM are optimised using the harris hawks optimisation (HHO) algorithm. Various scenarios of cases which may affect the quality of network performance are investigated. These events include the voltage sag, voltage swell, notch, transient fault conditions and sudden load increment. The proposed method is validated using the modified practical Eskom network. The presented results show that the proposed scheme correctly classified different cases.

AB - The modern electricity society has seen an increase in the integration of renewable energy sources into the power grid. This has significantly improved the electricity supply and sustainability. However, there are technical challenges related to the power quality (PQ) analysis for grid integrated systems. In this paper, we propose a PQ detection technique using the discrete wavelet transform (DWT) and support vector machine (SVM). The DWT analysis technique is used to extract statistical features, which are used as input to train the SVM classifier. The parameters of the SVM are optimised using the harris hawks optimisation (HHO) algorithm. Various scenarios of cases which may affect the quality of network performance are investigated. These events include the voltage sag, voltage swell, notch, transient fault conditions and sudden load increment. The proposed method is validated using the modified practical Eskom network. The presented results show that the proposed scheme correctly classified different cases.

KW - Discrete Wavelet Transform

KW - Power Quality Analysis

KW - Renewable Energy Sources

KW - Support Vector Machine

UR - https://www.scopus.com/pages/publications/85103740112

U2 - 10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221

DO - 10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221

M3 - Conference contribution

AN - SCOPUS:85103740112

T3 - 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021

BT - 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021

Y2 - 27 January 2021 through 29 January 2021

ER -

Moloi K, Thango BA, Nnnachi AF, Jordaan JA, Hamam Y. Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine. In 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021. Institute of Electrical and Electronics Engineers Inc. 2021. 9377221. (2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021). doi: 10.1109/SAUPEC/RobMech/PRASA52254.2021.9377221

Power Quality Analysis for A Solar-Grid Integrated System Using Support Vector Machine

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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