Advertisement

A Real-Time Intelligent Microcontroller-Based Harmonic Computing with Smart Phone Connectivity

  • Haripriya H. KulkarniEmail author
  • D. G. Bharadwaj
  • Dipti B. Yeolekar
  • Sheetal B. Mhetre
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 394)

Abstract

Increased use of nonlinear loads injects current harmonics in electrical distribution networks and creates new problems of power quality in the power system. In today’s competitive electrical market, electric utilities strive to supply consumers with reliable and pure sinusoidal electric power that does not represent a damaging threat to their equipment. In the restructured power system, prices of the power are associated to power quality. Hence, it is very important to monitor and ensure power quality. This paper presents an innovative way of real-time harmonic computing using intelligent microcontroller and its assessment with automatic meter reading (AMR) on smart phone. During preparation of this paper, fifty site visits are done covering the nonlinear loads like IT industries, steel industries, paper industries, workshops, etc. It is observed that the current harmonics generated are beyond the tolerable limits. Readings are taken at consumer end with the help of standard power analyzer for a period of 24 h. It is also observed that a good number of researchers have worked on harmonic studies in the power system network; however, their work does not fit into the framework of the standards applicable. The developed solution has the capacity to identify the normal and abnormal presence of harmonics with color code. Through this color coding technique, an unskilled worker can easily identify the objectionable presence of harmonics. The computing results are observed to be satisfactory and promising. It creates awareness in the utility for measurement and control of harmonics which in turn helps to improve the power quality.

Keywords

Automatic meter reading (AMR) Analog to digital converter (ADC) Central monitoring station (CMS) Data acquisition system (DAQ) Data concentrator unit (DCU) Global system for mobile communication (GSM) Optical fiber cable (OFC) Power line carrier communication (PLCC) Random access memory (RAM) Remote terminal units (RTU) Total harmonic distortion (THD) ZigBee 

Notes

Acknowledgments

The project work is being carried out in Bharati Vidyapeeth Deemed University COE, Pune. The authors wish to thank the authorities of BVDUCOE, Pune and PES’s Modern College of Engineering for granting permission to publish the work. Special thanks to MSEDCL and MSETCL for collection of data at consumer end.

References

  1. 1.
    Vlahinic S, Brnobic D, Stojkovic N. Indices for harmonic distortion monitoring of power distribution systems. In: IEEE Proceedings on instrumentation and measurement technology conference, IMTC;2009. p. 1771–7.Google Scholar
  2. 2.
    Khalifa T, Naik K, Nayak A. A survey of communication protocols for automatic meter reading applications. IEEE Commun Surv Tutorials (2011);13(2):168–82.Google Scholar
  3. 3.
    Yuan SJ. Remote, wireless automatic meter reading system based on GPRS. In: 2011 IEEE third international conference on communication software and networks, Xian;2011. p. 667–69.Google Scholar
  4. 4.
    Mahmood A, Aamir M, Anis MI. Design and implementation of AMR smart grid system. In: IEEE electric power conference, Canada;2008. p. 1–6.Google Scholar
  5. 5.
    IEEE recommended practices & requirements for harmonic controlling electric power system, standard 519-1992.Google Scholar
  6. 6.
    Cuk V, Cobben JFG. Analysis of harmonics current based on field measurements. IEEE Conf Gener Transm Distrib. 2013;7(12):1391–400.Google Scholar
  7. 7.
    Ferrigno L, Paciello V, Pietrosanto A. Visual sensors for remote metering in public network. In: IEEE international conference on instrumentation and measurement technology; 2011. p. 1–6.Google Scholar
  8. 8.
    Wasi-ur-Rahman M, Rahman MT, Khan TH, Kabir SML, Design of an intelligent SMS based remote metering system. In: IEEE Proceedings on information and automation;2009. p. 152–9.Google Scholar
  9. 9.
    Fung CC, Wong KP, Wong KW, Goh OS. Intelligent meters for improved system operation and customer relationship management. In: IEEE Proceedings on power system technology;2002. p. 1758–62.Google Scholar
  10. 10.
    Xu Z, Chen ZD, Nie H. Handheld computers: smartphone centric wireless applications. Microwave Mag, IEEE Microwave Theory Tech Soc. 2014;15(2):36–44.Google Scholar
  11. 11.
    Punithavati R, Duraiswamy K. An optimized solution for mobile computing environment. IEEE Int Conf Comput, Commun Networking. 2008;1:1–10.Google Scholar
  12. 12.
    Tian G, Fang L. A new mobile spatial information system grid computing model based on mobile agent. IEEE Int Conf Commun Mob Comput. 2014;2:596–600.Google Scholar
  13. 13.
    Nhan NQ, Vo MT, Nguyen TD. Improving the performance of data collecting system for electricity meter reading using wireless sensor network. IEEE Int Conf Adv Technol Commun. 2012;1:241–6.Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • Haripriya H. Kulkarni
    • 1
    Email author
  • D. G. Bharadwaj
    • 1
  • Dipti B. Yeolekar
    • 1
  • Sheetal B. Mhetre
    • 1
  1. 1.B.V.D.U.C.O.EPuneIndia

Personalised recommendations