A normalized Haar wavelet transformation based firefly optimization algorithm for power transmission line fault detection problems

ABSTRACT

Through transmission lines (TLs), an electric power transmission system has been able to transmit power from generating stations to consumers. During transmission, various kinds of malfunctions take place and they are termed as a fault. Although fault is undesirable, it is unavoidable event hampering the smooth functioning of the power system. In power transmission systems, and a large number of voltage and current signal, distortions take place due to faults. Faults occur in power TL causing power supply interruption. Several fault detection techniques have been presented by researchers to detect a fault in TL. However, the time required to locate the fault remained higher and the power loss rate (PLR) was not reduced. To overcome these issues and identify faults in electrical power TL, Haar wavelet feature extraction-based firefly optimized fault detection (HWFE-FFOFD) method has been introduced. The power TL signal sample has been taken as an input. Zero-mean normalization is the pre-processing approach that converts the transmission signal sample into a specified range. To extort features (i.e. voltages and current values) with higher accuracy, the normalized signal has been given to Haar Wavelet Transform. Then, the extracted features at different time instants have been given to the firefly optimized fault detection (FFOFD) algorithm. In the FFOFD algorithm, extracted features have been considered as firefly populations. The FFOFD algorithm functions with the flashing behavior of a firefly. At last, the firefly position has been updated and ranked according to light intensity to detect a fault in electrical power TL. In this manner, the fault detection time (FDT) gets reduced using HWFE-FFOFD method. HWFE-FFOFD method is evaluated in FEA, FDT, and PLR. From the experimental results obtained, it can be confirmed that the HWFE-FFOFD method has been able to enhance accuracy by 14% and minimize time by 26% and PLR by 62% when compared to conventional methods.

KEYWORDS:

• Electric power transmission system
• fault
• haar wavelet
• firefly
• flashing behavior
• fault detection

Nomenclature

${\mu }_T$	=	Mean
${\sigma }_T$	=	Standard Deviation
$N_i$	=	Normalized Series
$\mathit{\phi }\left(\mathit{t}\right)$	=	Haar Mother Wavelet Function
$\mathrm{\varnothing }\left(\mathit{t}\right)$	=	Scaling Function
$x_L\left(\mathit{N}\right)$	=	Low Frequency
$x_H\left(\mathit{N}\right)$	=	High Frequency
$W_c$	=	Wavelet Coefficient
$\mathit{T}$	=	Threshold
$\mathit{LI}$	=	Light Intensity
$\mathit{Att}$	=	Attractiveness
$r_{\mathit{ab}}$	=	Distance Between $a^{\mathit{th}}$ And $b^{\mathit{th}}$Fireflies
$\mathit{d}$	=	Distance Between Two Fireflies
$L_o$	=	Actual Light Intensity
γ	=	Light Absorption Coefficient
$\mathit{s}$	=	Number of Fireflies
$\mathit{R}$	=	Random Number
${\alpha }_t$	=	Parameter Controlling Size
${\in }_t$	=	Vector Drawn
$P_g$	=	Power Generated
$P_r$	=	Power Received

Abbreviations

TL	=	Transmission Line
PLR	=	Power Loss Rate
HWFE-FFOFD	=	Haar Wavelet Feature Extraction-based FireFly Optimized Fault Detection
FFOFD	=	Fire Fly Optimized Fault Detection
FDT	=	Fault Detection Time
RFDD	=	Robust Fault Detection as well as Discrimination
ANN	=	Artificial Neural Network
WAMS	=	Wide Area Measurement Systems
AANN	=	Auto Associative Neural Networks
ANFIS	=	Adaptive Neuro-Fuzzy Inference Systems
FEA	=	Feature Extraction Accuracy
RGA	=	Relation Guiding Algorithm
PMUs	=	Phasor Measurement Units
HPF	=	High Pass Filter
LPF	=	Low Pass Filter
OF	=	Optimized Fault

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Iyappan Murugesan

Iyappan Murugesan did his B.E in Electrical and Electronics Engineering in 2007 and completed his Master degree in 2010 and is specialized in Embedded System Technologies. He was awarded Doctorate in Electrical Engineering domain in 2021. He is currently Assistant Professor in the Electrical and Electronics Engineering department of NPR College of Engineering and Technology. Earlier, he worked as a member in the Electrical and Electronics Engineering department of M.Kumarasamy College of Engineering (Autonomous), Karur from June 2019 to Aug. 2020. Well before that, he worked as a member in the Electrical and Electronics Engineeringdepartment of V.S.B. Engineering College, Karur from Apr. 2017 to June 2019. He started his teaching career from RVS College of Engineering and Technology, Coimbatore from Nov. 2011 to Nov. 2016. In his earlier days, he worked as a Graduate Apprentice Trainee at Dharmapuri Electricity Distribution Circle, TANGEDCO Ltd, Dharmapuri from Aug. 2010 to Aug. 2011. He is specialized in Embedded Systems, Power Systems Optimization, Power Converters, Electric Drives and Control and Soft Computing. On the whole, he has ten years of teaching and one year of industrial experience. He has published articles in seven Scopus indexed journals and presented papers in three international conferences, five national conferences and filed one patent in the field of Electrical Engineering.

Prabhakar Gunasekaran

Prabhakar Gunasekaran is currently working as an Assistant Professor in the Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai – 15 (A Govt. Aided Autonomous Institution Affiliated to Anna University) Tamilnadu, India. He obtained his B.E degree in Electronics & Communication Engineering from Arulmigu Kalasalingam College of Engineering, Krishnankoil, under Anna University, Chennai in the year of2009, and his M.Tech. Degree in the specialization of Embedded Systems from Hindustan University, Chennai in the year 2011. He obtained his Ph.D. degree in the year 2018 under the faculty of Electrical Engineering, at Anna University, Chennai. He is a recognized Ph. D Supervisor of Anna University, Chennai, under the Faculty of Electrical Engineering, and also guiding 5 Ph.D. scholars. He has published more than 35 research articles around the world including reputed journal transactions like IET, Springer, Taylor & Francis, and Elsevier.

Suresh Muthusamy

Suresh Muthusamy received B.E. degree in Electrical and Electronics Engineering, M.E. degree in Power Electronics and Drives during the year 2009 and 2011 from Anna University, Chennai and Anna University, Coimbatore respectively. He then completed Ph.D. degree in Electrical Engineering from Anna University, Chennai during the year 2023 in the area of Hybrid renewable energy systems. He worked as Assistant Professor in the Department of Electrical and Electronics Engineering at Kongu Engineering College (Autonomous), Perundurai, Erode, during the period June 2011 to January 2020. From January 2020 onwards, he has been working as Assistant Professor Senior Grade in the Department of Electronics and Communication Engineering at Kongu Engineering College (Autonomous), Perundurai, Erode. He published more than 100 research articles in well reputed and refereed international journals from Elsevier, Springer, Taylor & Francis, Wiley, SAGE publishers, ASME, ASTM International, MDPI, CRC Press, etc and indexed in SCI, SCIE, ESCI, Scopus and Web of Science with good impact factors. He also presented several research articles in national & international conferences and also serving as the reviewer, editor for about 75 international journals including IET Renewable Power Generation, IET Journal of Engineering, etc. To his credit, he has filed and published 28 Indian patents in IPR website, governed by Ministry of Commerce and Industry, Government of India. His areas of interests include hybrid renewable energy systems, power electronic converters, hybrid electric vehicles, and battery management systems.

Ponarun Ramamoorthi

Ponarun Ramamoorthi received B.E. degree in Electrical and Electronics Engineering and M.E. degree in Power Electronics and Drives during the year 2009 and 2011 from Anna University, Chennai. He is currently working towards the Ph.D degree in Electrical Engineering at Anna University, Chennai in the area of power electronics applications to power systems. Also, he is working as Assistant Professor in the Department of Electrical and Electronics Engineering at Theni Kammavar Sangam College of Technology, Theni, Tamil Nadu, India. His area of interest includes renewable energy power generation, battery management systems and power electronic converters. He published several research articles in well reputed journals with good impact factors and also serving as the reviewer for 2 international journals.