Kwame Nkrumah University of
Science & Technology, Kumasi, Ghana
Electricity Theft Detection by Monitoring of Consumption Data
A presentation by
Daniel Odoom(PG5080218)
Project Supervised by
Dr. Francis Effah
Dr. Emmanuel Frimpong
Kwame Nkrumah University of
Science & Technology, Kumasi, Ghana
PRESENTATION OUTLINE
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Background
Problem Definition
Aim and Objectives
Methodology
Anticipated Results
Project Timelines
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Background
 Developing countries, including Ghana, are grappling with a high rate
of electricity theft which affects income of utility companies [1].
 The infrastructure deployed by these utility companies to detect and
control electricity theft has deficiencies which results in an immense
loss of revenue [1]. A World Bank report in 2009 indicated that up to
50% of electricity in developing countries is acquired via energy theft
[2].
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Background Cont’d
 An exercise conducted by the Electricity Company of Ghana (now
Power Distribution Company) revealed that 11,890 out of
250,616 electricity meters inspected had been tampered
with[11].
 The main causes of electricity theft in Ghana include;
• High electricity prices
• Poor quality of power supplied
• Collision between utility workers and consumers
• Poor enforcement of the law against electricity theft and
• PURC not fighting for the interest of consumers.
 Other factors are attitudinal, ignorance of the implication of
stealing power, unemployment, and poverty [1].
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Background Cont’d
 Some of the most common methods used for stealing power include;
• Bypassing the meter
• Inverting the meter
• Placing straps behind the meter
• Switching meters etc. [5]
 Options put in place to combat this menace include;
• Physical inspection
• The use Smart Meters
• Power theft control via plc system
• Monitoring of consumer load profiles [7][9]
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Problem definition
Finding the gap…..
 The table below gives a comparison of the anti theft options[5][9].
Power theft controlling options Cost
Efficiency
Reliability
Data comparison technique
Moderate
High
Building of extra infrastructure High
High
High
Physical Inspection
Low
Low
Low
Use of Smart Meter
High
High
High
Low
Table 1
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Aim and Objectives
 Aim
• To develop a technique for electricity theft detection using
consumption data.
 Objectives
• To obtain consumer consumption data and segregate them into
genuine consumer data and fraudulent consumer data
• To develop a technique for detecting electricity theft
• To compare developed technique to already existing approaches
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Methodology
• Outline activities to undertake to fit project plan
• Comprehensive review of power theft detection
techniques.
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Project timeline
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Anticipated Results
 Effective technique for detecting electricity theft
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Reference
[1]
Yakubu, O., Babu, N. C. and Osei, A. (2018). Electricity Theft: Analysis of the Underlying Contributory
Factors in Ghana, https://www.sciencedirect.com/science /article/pii/S0301421518306232, Accessed 1-07-2019.
[2]
Lazaropoulos, A. G. (2018). Detection of Energy Theft in Overhead Low-Voltage Power Grids – The Hook
Style Energy Theft in the Smart Grid Era, School of Electrical and Computer Engineering / National Technical
University of Athens /9 Iroon Polytechniou Street / Zografou, GR 15780, 2.
[3]
Yakubu, O. and Babu, N. C. (2017). Type and Nature of Electricity Theft: A Case Study Of Ghana,
International Journal of Mechanical Engineering and Technology (IJMET), 171.
[4]
Sardar, S. and Ahmad, S. (2015). Detecting And Minimizing Electricity Theft: A Review,
https://www.researchgate.net/publication/308207798, 2-6.
[5]
Seger, K. A. and Icove, D. J. (1988). Power Theft: The Silent Crime, FBI Law Enforcement Bulletin, 21.
[6]
Nunoo, S. and Attachie, J. C. (2011). A Methodology for The Design of an Electricity Theft Monitoring
System, Journal of Theoretical and Applied Information Technology,Little Lion Scientific R and D, Islamabad
Pakistan, 112-115.
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Reference cont’d
[7]
Konstantinos, B. and Georgios, S. (2019). Efficient Power Theft Detection for Residential Consumers Using
Mean Shift Data Mining Knowledge Discovery Process, International Journal of Artificial Intelligence and
Applications (IJAIA), Vol.10, No.1, 70.
[8]
Depuru, S. S. S. R (2012). Modeling, Detection and Prevention of Electricity Theft for Enhanced
Performance and Security of Power Grid, Unpublished PhD. Project, The University of Toledo, 9.
[9]
Saikiran, B. and Hariharan, R. (2014). Review of methods of power theft in Power System, International
Journal of Scientific & Engineering Research, Volume 5, 276-279.
[10] Oteng-Adjei, J. (2019). Power Markets & Economics, Unpublished MPHIL Lecture Notes, 9.
[11] Annon.
(2019).
A
Sustainable
Approach
in
Curbing
Electricity
Theft,
https://thebftonline.com/2019/features/a-sustainable-approach-in-curbing-electricity-theft/, Accessed 1-07-2019.
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THANK YOU
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