A MINING FRAMEWORK TO DETECT NON-TECHNICAL LOSSES IN POWER UTILITIES

Félix Biscarri, Iñigo Monedero, Carlos León, Juan I. Guerrero, Jesús Biscarri, Rocío Millán

2009

Abstract

This paper deals with the characterization of customers in power companies in order to detect consumption Non-Technical Losses (NTL). A new framework is presented, to find relevant knowledge about the particular characteristics of the electric power customers. The authors uses two innovative statistical estimators to weigh variability and trend of the customer consumption. The final classification model is presented by a rule set, based on discovering association rules in the data. The work is illustrated by a case study considering a real data base.

References

  1. Biscarri, F., Monedero, I., León, C., Guerrero, J., Biscarri, J., and Millán, R. (June 12-16, Barcelona, Spain, 2008). A data mining method based on the variability of the customers consumption. In 10th International conference on Enterprise Information Systems ICEIS2008.
  2. Cabral, J., Pinto, J., Gontijo, E. M., and Reis, J. (2004). Fraud detection in electrical energy consumers using rough sets. In 2004 IEEE International Conference on Systems, Man and Cybernetics. IEEE press.
  3. Cabral, J., Pinto, J., Linares, K., and Pinto, A. (2006). Methodology for fraud detection using rough sets. In 2006 IEEE International Conference on Granular Computing. IEEE press.
  4. Cabral, J., Pinto, J., Martins, E., and Pinto, A. (April 21- 24, 2008). Fraud detection in high voltage electricity consumers using data mining. In IEEE Transmision and Distribution Conference and Exposition T&D. IEEE/PES.
  5. Filho, J. and als (The Hague, The Netherlands, 2004.). Fraud identification in electricity company costumers using decision tree. In IEEE International Conference on Systems, Man and Cibernetics. IEEE/PES.
  6. Galván, J., Elices, E., noz, A. M., Czernichow, T., and SanzBobi, M. (Nov. 2-6, 1998). System for detection of abnormalities and fraud in customer consumption. In 12th Conference on Electric Power Supply Industry. IEEE/PES.
  7. Jiang, R., Tagiris, H., Lachsz, A., and Jeffrey, M. (Oct. 6-10, 2002). Wavelet based features extraction and multiple classifiers for electricity fraud detection. In Transmission and Distribution Conference and Exhibition 2002: Asia pacific. IEEE/PES.
  8. K.S.Yap, Hussien, Z., and Mohamad, A. (April 2-4, Phuket, Thailand, 2007). Abnormalities and fraud electric meter detection using hybrid support vector machine and genetic algorithm. In Proceeding of the Third IASTED International Conference Advances in Computer Science and Technology. IASTED PRESS.
  9. Sforna, M. (England, 2000). Data mining in power company customer database. In Electric Power Systems Reseach, 55, 201-209. Elsevier Press.
  10. Witthen, I. and Frank, E. (2000). Data Mining-Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, Academic Press, New York and San Mateo, CA.
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Paper Citation


in Harvard Style

Biscarri F., Monedero I., León C., Guerrero J., Biscarri J. and Millán R. (2009). A MINING FRAMEWORK TO DETECT NON-TECHNICAL LOSSES IN POWER UTILITIES . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-85-2, pages 97-102. DOI: 10.5220/0001953300970102


in Bibtex Style

@conference{iceis09,
author={Félix Biscarri and Iñigo Monedero and Carlos León and Juan I. Guerrero and Jesús Biscarri and Rocío Millán},
title={A MINING FRAMEWORK TO DETECT NON-TECHNICAL LOSSES IN POWER UTILITIES},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2009},
pages={97-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001953300970102},
isbn={978-989-8111-85-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A MINING FRAMEWORK TO DETECT NON-TECHNICAL LOSSES IN POWER UTILITIES
SN - 978-989-8111-85-2
AU - Biscarri F.
AU - Monedero I.
AU - León C.
AU - Guerrero J.
AU - Biscarri J.
AU - Millán R.
PY - 2009
SP - 97
EP - 102
DO - 10.5220/0001953300970102