Skip to main content

Linguistic Representation of Power System Signals

  • Chapter
  • First Online:
Electricity Distribution

Part of the book series: Energy Systems ((ENERGY))

Abstract

This chapter presents an Attribute Grammar capable of modelling power system signals. Primitive pattern selection, linguistic representation, and pattern grammar formulation are the sub problems of tackled. The recognition of power system waveforms and to the measurement of its parameters is proven to easily be handled using syntactic pattern recognition techniques. Attribute grammars are used as the model for the pattern grammar because of their descriptive power, which is due to their ability to handle syntactic as well as semantic information. In order the functionality of the proposed system to be tested, a software implementation has been developed using waveforms and data provided by the Independent Power Transmission Operator (IPTO) in Greece. The proposed methodology will be applied to the implementation of an efficient protective relay that would efficiently prevent safety problems and economic losses caused by faults presented in power systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Saha MM, Rosolowski E, Izykowski J, Artificial Intelligent Application to Power System Protection, Proceedings of the Eleventh National Power Systems Conference (NPSC`2000), Bangalore, New Delhi, Allied Publishers 2000, 2:797-600, 2000.

    Google Scholar 

  2. Jinglin Xu,Uwe Meyer-Baese, Real Time Digital Signal Processing in Power Systems using FPGAs: An Analysis of Time-Varying Waveform Distortions and Power Disturbances, April 3, 2011, ISBN-13: 978-3844321722.

    Google Scholar 

  3. Earley J, An efficient context-free parsing algorithm, Communications of the ACM, 13(2) 94-102, 1970. doi:http://doi.acm.org/10.1147/362007.362037.

  4. Dimopoulos AC, Pavlatos C, Papakonstantinou G, A platform for the automatic generation of attribute evaluation hardware systems, Computer Languages, Systems & Structures, 36(2):203-222, 2010.

    Google Scholar 

  5. Xilinx Inc., www.xilinx.com.

  6. Aho V, Ullman JD, The Theory of Parsing, Translation, and Compiling, Vol. I: Parsing of Series in Automatic Computation, Prentice Hall, Englewood Cliffs, New Jersey, 1972.

    Google Scholar 

  7. Younger DH, Recognition and parsing of context-free languages in n 3, Information and Control, 10:189-208, 1967.

    Google Scholar 

  8. Graham SL, Harrison MA, Ruzzo WL, An improved context-free recognizer, ACM Trans. Program. Lang. Syst., 2(3):417-462, 1980.

    Google Scholar 

  9. Stolcke A, An efficient probabilistic context-free parsing algorithm that computes prefix probabilities, Computational Linguistics, 21(2):167-201, 1997.

    Google Scholar 

  10. Chiang Y, Fu K, Parallel parsing algorithms and VLSI implementations for syntactic pattern recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, 6:302-314, 1984.

    Google Scholar 

  11. Cheng HD, Fu K, Algorithm partition and parallel recognition of general contextfree languages using fixed-size VLSI architecture, Pattern Recognition, 19(7):361-372, 1986.

    Google Scholar 

  12. Ciressan A, Sanchez E, Rajman M, Chappelier JC, An fpga-based coprocessor for the parsing of context-free grammars, Proceedings of the 2000 IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM ’00), IEEE Computer Society, Washington, DC, USA, pp. 236-247, 2000.

    Google Scholar 

  13. Bordim J, Ito Y, Nakano K, Accelerating the CKY parsing using FPGAs, IEICE Transactions Information & Systems, E-86D(7):803-810, 2003.

    Google Scholar 

  14. Pavlatos C, Panagopoulos I, Papakonstantinou G, A programmable pipelined coprocessor for parsing applications, in: Workshop on Application Specific Processors (WASP) CODES, Stockholm, 2004.

    Google Scholar 

  15. Pavlatos C, Dimopoulos AC, Koulouris A, Andronikos T, Panagopoulos I, Papakonstantinou G, Efficient reconfigurable embedded parsers, Comput. Lang. Syst. Struct., 37(2):196-217, 2009.

    Google Scholar 

  16. Trahanias P, Skordalakis E., Syntactic pattern recognition of the ECG. IEEE Transantions on Pattern Analysis and Machine Intelligence (PAMI), vol. 12, no. 7, July.

    Google Scholar 

  17. http://www.admie.gr/nc/en/home/.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C. Pavlatos .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Pavlatos, C., Vita, V. (2016). Linguistic Representation of Power System Signals. In: Karampelas, P., Ekonomou, L. (eds) Electricity Distribution. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49434-9_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-49434-9_12

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49432-5

  • Online ISBN: 978-3-662-49434-9

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics