Localization of Pilferage of Energy Using PLC Signals for an Unbalanced Distribution System

Dj. Taniguevelane^1, and Dr. K. N. Srinivas²

¹Research Scholar, B. S. Abdur Rahman Crescent University, Vandalur, Chennai, India

²Electrical and Electronics Department, B. S. Abdur Rahman Crescent University, Vandalur, Chennai, India

Cite this paper:
Dj. Taniguevelane and Dr. K. N. Srinivas. Localization of Pilferage of Energy Using PLC Signals for an Unbalanced Distribution System. International Transaction of Electrical and Computer Engineers System. 2017; 4(1):39-48. doi: 10.12691/iteces-4-1-5

Abstract

Energy theft is a widespread problem results in loss to the utilities and affects the financial viability of utilities. Hence utilities strive for minimization of theft by carrying out various reform projects. Smart meters, AMI and Theft localization algorithms are some of the tools which will enable them to meet the challenge. Many techniques/algorithms are available for theft localization and each of them requires distinct data such as Historic consumption patterns, Network parameter etc. The effectiveness of theft localization depends on the accuracy of input data. The network parameter data of the service line of the consumers is one of the data required for some of the theft localization algorithms which itself is difficult to measure due to the fact that those are laid underground or inside the buildings. This paper analyses some of the theft detection algorithms and its limitations for applying to the LT distribution network and proposes an algorithm to localize the theft using the distance measurement feature of the PLC signals used in smart meters in addition to the communication function. This paper also analyses the effectiveness of the theft localization using the network data obtained with the proposed algorithm.

Keywords:
pilferage of energy localization non-technical losses smart meters AMI PLC

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References:

[1]	Miriam Golden and Brian Min, “Theft and Loss of Electricity in an Indian State”, Working paper, IGC International Growth Centre, 2012.
[2]	Thomas B. Smith, “Electricity theft: a comparative analysis,” Energy Policy, vol. 32, no. 18, pp. 2067-2076, 2004.
[3]	Shantanu Dixit, Girish Sant,SubodhWagle and N. Sreekumar,”HT Energy Audit: The Crucial Starting Point for Curbing Revenue Loss” Prayas Occasional Report, February 2002.
[4]	M. Anas, N. Javid, A. Mahmood, S. M. Raza, U. Qasim, A. Khan, “Minimizing Electricity Theft using Smart Meters in AMI”, arXiv, 11 August 2012.
[5]	K. N. Srinivas and D. Taniguevelane, “Analysis of Smart meter data forEnergy Pilferage localization Techniques”, IEEE International Conference on Standards for Smart Grid Ecosystem, 6-7 March 2014, Bangalore.
[6]	V. J. Hodge and J. Austin “A survey of outlier detection methodologies” Artificial Intelligence Review, vol. 22, pp. 85-126, 2004.
[7]	A.I. Abdullateef, M.J. E. Salami, M.A. Musse, A.M. Aibinu, and M.A. Onasany, “Electricity Theft Prediction on Low Voltage Distribution System Using Autoregressive Techniques”, International Journal of Research in Engineering and Technology (IJRET) Vol.1, No.5, 2012 pp. 250-254.
[8]	Anas M, Javaid N, Mahmood A, Raza SM, Qasim U, Khan ZA., “Minimizing electricity theft using smart meters”, in AMI; 2012.
[9]	Tung-Shen Zhan, Shi-Jaw Chen, Chih-Cheng Kao, Chao-Lin Kuo, Jian-Liun Chen, Chia-Hung Lin, “Non-Technical loss and power blackout detection under advanced metering infrastructure using a cooperative game based inference mechanism”, IET Generation, Transmission & Distribution, 2016, Vol.10, Iss. 4, pp. 873-882.
[10]	Alvaro A. Cardenas University of Texas,Dallas. Saurabh Amin, MIT. Galina Schwartz, Roy Dong, Shankar Sastry, University of California, Berkeley. “A Game Theory Model for Electricity Theft Detection and Privacy-Aware Control in AMI Systems”, IEEE 50th Annual Allerton Conference Communication, Control, and Computing (Allerton), 2012.
[11]	A. Pasdar, S. Mirzakuchaki, “A Solution to Remote Detecting of Illegal Electricity Usage Based on Smart Metering”, 2nd IEEE International Workshop on Soft Computing Applications, 21-23 August, 2007.
[12]	SamWeckx, Carlos Gonzalez, JeroenTant, Tom De Rybel, Johan Driesen, “Parameter Identification of Unknown Radial Grids for Theft Detection”, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), October 14-17, 2012.
[13]	Frank Van Den Bergh, Petr Kadurek, Sjef Cobben and Wilkling, “Electricity Theft Localization based on Smart Metering”, CIRED 21st International Conference on Electricity Distribution, paper no. 1267.
[14]	Shih-Che Huan, Yuan-Liang Lo, and Chan-Nan Lu, “Non-Technical Loss Detection Using State Estimation and Analysis of Variance”, IEEET ransactions on Power Systems, Vol.28. No.3, August 2013.
[15]	TomasoErseghe, Francesco Lorenzon, Stefano Tomasin, AlessandroCostabeber and Paolo Tenti, “Distance Measurement over PLC for Dynamic Grid Mapping of Smart Micro Grids” IEEE SmartGridComm, 2011.
[16]	Tomaso Erseghe, Stefano Tomasin and Alberto Vigato, “Topology Estimation for Smart Micro Grids via Power line Communications”, IEEE Transactions on Signal Processing, Vol.61, No.13, July 1, 2013.
[17]	Vijay Arya and Balakrishnan Narayanaswamy, “Loss localisation in smart distribution networks”, 2014 Sixth International Conference on Communication Systems and Networks (COMSNETS), 6-10 Jan. 2014.
[18]	Muhammad Tariq, H. Vincent Poor, “Electricity Theft Detection and Localization in Grid-tied Microgrids”, IEEE Transactions on Smart Grid, Volume: PP, Issue: 99, 25 August 2016.
[19]	Luís Marques; Nuno Silva; Ismael Miranda; Eduardo Rodriges; Helder Leite, “Detection and localisation of non-technical losses in low voltage distribution networks”, Conference on Power Generation, Transmission, Distribution and Energy Conversion, Nov, 2016.
[20]	Yuchen Zhou, Xiaodao Chen, Albert Y. Zomaya, Lizhe Wang and Shiyan Hu, “A Dynamic Programming Algorithm for Leveraging Probabilistic Detection of Energy Theft in Smart Home”, IEEE Transactions on Emerging Topics in Computing,Vol.3, Dec’15.
[21]	K. N. Srinivas and D. Taniguevelane, “Deduction of Pilferage of Energy using PLC signals”, International Journal of Applied Engineering Research, Vol. 10, No. 9, 2015.