Skip to main content

Phasor Measurement Unit and Its Application in Modern Power Systems

  • Chapter
Emerging Techniques in Power System Analysis

Abstract

The introduction of phasor measurement units (PMUs) in power systems significantly improves the possibilities for monitoring and analyzing power system dynamics. Synchronized measurements make it possible to directly measure phase angles between corresponding phasors in different locations within the power system. Improved monitoring and remedial action capabilities allow network operators to utilize the existing power system in a more efficient way. Improved information allows fast and reliable emergency actions, which reduces the need for relatively high transmission margins required by potential power system disturbances. In this chapter, the applications of PMU in modern power systems are presented. Specifically, the topics touched in this chapter include state estimation, voltage and transient stability, oscillation monitoring, event and fault detection, situation awareness, and model validation. A case study using the Characteristic Ellipsoid method based on the PMU measurements to monitor power system dynamics is presented.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Abur A, Exposito AG (2004) Power system state estimation: theory and implementation. Marcel Dekker, New York

    Google Scholar 

  • Abur A, Magnago FH (1999) Optimal meter placement for maintaining observability during single branch outages. IEEE Trans Power Syst 14(4): 1273–1278

    Article  Google Scholar 

  • Al-Othman AK, Irving MR (2005a) A comparative study of two methods for uncertainty analysis in power system state estimation. IEEE Trans Power Syst 20(2): 1181–1182

    Article  Google Scholar 

  • Al-Othman AK, Irving MR (2005b) Uncertainty modeling in power system state estimation. IEE Proceedings Generation, Transm Distrib 152(2): 233–239

    Article  Google Scholar 

  • Angel AD, Geurts P, Ernst D et al (2007) Estimation of rotor angles of synchronous machines using Artificial Neural Networks and local PMU-based quantities. Neurocomputing 70(16–18): 2668–2678

    Google Scholar 

  • Baldwin TL, Mili L, Boisen MB et al (1993) Power system observability with minimal phasor measurement placement. IEEE Trans Power Syst 8(2): 707–715

    Article  Google Scholar 

  • Balance JW, Bhargava B, Rodriguez GD (2003) Monitoring power system dynamics using phasor measurement technology for power system dynamic security assessment. Proceedings of IEEE Bologna PowerTech Conference, Bologna, 22–26 June 2003

    Google Scholar 

  • Bi TS, Qin XH, Yang QX (2008) A novel hybrid state estimator for including synchronized phasor measurements. Electr Power Syst Res 78(8): 1343–1352

    Article  Google Scholar 

  • Bian X, Qiu J (2006) Adaptive clonal algorithm and its application for optimal PMU placement. Proceedings of IEEE International Conference on Communication, Circuits and Systems, Island of Kos, 21–24 May 2006

    Google Scholar 

  • Brahma S, Girgis AA (2004) Fault location on a transmission line using synchronized voltage measurements. IEEE Trans Power Deliv 19(4): 1619–1622

    Article  Google Scholar 

  • Brahma SM (2006) New fault-location method for a single multiterminal transmission line using synchronized phasor measurements. IEEE Trans Power Deliv 21(3): 1148–1153

    Article  Google Scholar 

  • Brueni DJ, Heath LS (2005) The PMU placement problem. SIAM J on Discr Math 19(3): 744–761

    Article  MATH  MathSciNet  Google Scholar 

  • Burnett ROJ, Butts MM, Cease TW et al (1994) Synchronized phasor measurements of a power system event. IEEE Trans Power Syst 9(3): 1643–1650

    Article  Google Scholar 

  • Cai JY, Huang Z, Hauer J et al (2005) Current status and experience of WAMS implementation in North America. Proceedings of IEEE/PES Transmission and Distribution Conference and Exhibition: Asia Pacific, Dalian, 23–25 August 2005

    Google Scholar 

  • Chakrabarti S, Eliades D, Kyriakides E et al (2007) Measurement uncertainty considerations in optimal sensor deployment for state estimation. Proceedings of IEEE Symposium on Intelligent Signal Processing, Alcala de Henares, 3–5 October 2007

    Google Scholar 

  • Chakrabarti S, Kyriakides E (2008) Optimal placement of phasor measurement units for power system observability. IEEE Trans Power Syst 23(3): 1433–1440

    Article  Google Scholar 

  • Chakrabarti S, Kyriakides E (2009) PMU measurement uncertainty considerations in WLS state estimation. IEEE Trans Power Syst 24(2): 1062–1071

    Article  Google Scholar 

  • Chakrabarti S, Kyriakides E, Bi T (2009a) Measurements get together. IEEE Power Energy Mag 7(1): 41–49

    Article  Google Scholar 

  • Chakrabarti S, Kyriakides E, Eliades DG (2009b) Placement of synchronized measurements for power system observability. IEEE Trans Power Deliv 24(1): 12–19.

    Article  Google Scholar 

  • Chen CS, Liu CW, Jiang JA (2002) A new adaptive PMU based protection scheme for transposed/untransposed parallel transmission lines. IEEE Trans Power Deliv 17(2): 395–404

    Article  Google Scholar 

  • Chen J, Abur A (2005) Improved bad data processing via strategic placement of PMUs. 2005 IEEE Power Engineering Society General Meeting, 12–16 June 2005

    Google Scholar 

  • Corsi S, Taranto GN (2008) A real-time voltage instability identification algorithm based on local phasor measurements.IEEE Trans Power Syst 23(3): 1271–1279

    Article  Google Scholar 

  • Din ESTE, Gilany M, Aziz MMA et al (2005) An PMU double ended fault location scheme for aged power cables. Proceedings of IEEE Power Engineering Society General Meeting, San Francisco, 12–16 June 2005

    Google Scholar 

  • Donnelly M, Ingram M, Carroll JR (2006) Eastern interconnection phasor project. Proceedings of the 39th Annual Hawaii International Conference on System Sciences, Hawaii, 4–7 January 2006

    Google Scholar 

  • El-Amary NH, Mostafa YG, Mansour MM et al (2008) Phasor Measurement Units’ allocation using discrete particle swarm for voltage stability monitoring. 2008 IEEE Canada Electric Power Conference, Vancouver, 6–7 October 2008

    Google Scholar 

  • Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Human Factors 37(1): 32–64

    Article  Google Scholar 

  • Fan C, Du X, Li S et al (2007) An adaptive fault location technique based on PMU for transmission line. 2007 IEEE Power Engineering Society General Meeting, Tempa, 24–28 June 2007

    Google Scholar 

  • Fouad AA, Aboytes F, Carvalho VF et al (1988) Dynamic security assessment practices in North America. IEEE Trans Power Syst 3(3): 1310–1321

    Article  Google Scholar 

  • Gubina F, Strmcnik B (1995) Voltage collapse proximity index determination using voltage phasors approach. IEEE Trans Power Syst 10(2): 788–794

    Article  Google Scholar 

  • IEEE Power Engineering Society. (2006) IEEE Std C37.118TM–2005: IEEE standard for synchrophasors for power systems, New York

    Google Scholar 

  • Jiang JA, Lin YH, Yang JZ et al (2000a) An adaptive PMU based fault detection/location technique for transmission lines Part-II: PMU implementation and performance evaluation. IEEE Trans Power Deliv 15(4): 1136–1146

    Article  Google Scholar 

  • Jiang JA, Yang JZ, Lin YH et al (2000b) An adaptive PMU based fault detection/location technique for transmission lines Part-I: Theory and algorithms. IEEE Trans Power Deliv 15(2): 486–493

    Article  Google Scholar 

  • Jiang W, Vittal V, Heydt GT (2007) A distributed state estimator utilizing synchronized phasor measurements. IEEE Trans Power Syst 22(2): 563–571

    Article  Google Scholar 

  • Jiang W, Vittal V, Heydt GT (2008) Diakoptic state estimation using phasor measurement units. IEEE Trans Power Syst 23(4): 1589–1589

    Google Scholar 

  • Kakimoto N, Sugumi M, Makino T et al (2006) Monitoring of inter-area oscillation mode by synchronized phasor measurement. IEEE Trans Power Syst 21(1): 260–268

    Article  Google Scholar 

  • Kezunovic M, Mrkic J, Perunicic B (1994) An accurate fault location algorithm using synchronized sampling. Electr Power Syst Res 29(3): 161–169

    Article  Google Scholar 

  • Khachiyan LG (1996) Rounding of polytopes in the real number model of computation. Math Oper Res 21(2): 307–320

    Article  MATH  MathSciNet  Google Scholar 

  • Kumar P, Yildirim EA (2005) Minimum-volume enclosing ellipsoids and core sets. J Optim Theory Appl 126(1): 1–21

    Article  MATH  MathSciNet  Google Scholar 

  • Kundur P (1994) Power System Stability And Control. McGraw-Hill, New York

    Google Scholar 

  • Leirbukt A, Gjerde JO, Korba P et al (2006) Wide area monitoring experiences in Norway. Proceedings of Power Systems Conference & Exposition, Atlanta, 29 October-1 November 2006

    Google Scholar 

  • Lien KP, Liu CW, Jiang JA et al (2005) A novel fault location algorithm for multiterminal lines using phasor measurement units. Proceedings of the 37th Annual North American Power Symposium, Ames, 23–25 October 2005

    Google Scholar 

  • Lien KP, Liu CWk, Yu CS et al (2006) Transmission network fault location observability with minimal PMU placement. IEEE Trans Power Deliv 21(3): 1128–1136

    Article  Google Scholar 

  • Lin YH, Liu CW, Chen CS (2004a) A new PMU-based fault detection/location technique for transmission lines with consideration of arcing fault discrimination-Part I: Theory and algorithms. IEEE Trans Power Deliv 19(4): 1587–1593

    Article  Google Scholar 

  • Lin YH, Liu CW, Chen CS (2004b) A new PMU-based fault detection/location technique for transmission lines with consideration of arcing fault discrimination-Part II: Performance evaluation. IEEE Trans Power Deliv 19(4): 1594–1601

    Article  Google Scholar 

  • Lin YH, Liu CW, Yu CS (2002) A new fault locator for three-terminal transmission line-using two-terminal synchronized voltage and current phasors. IEEE Trans Power Deliv 17(2): 452–459

    Article  Google Scholar 

  • Liu CW, Chang CS, Su MC (1998) Neuro-fuzzy networks for voltage security monitoring based on synchronized phasor measurements. IEEE Trans Power Syst 13(2): 326–332

    Article  Google Scholar 

  • Liu CW, Su MC, Tsay SS et al (1999a) Application of a novel fuzzy neural network to real-time transient stability swings prediction based on synchronized phasor measurements. IEEE Trans Power Syst 14(2): 685–692

    Article  Google Scholar 

  • Liu CW, Thorp J (1995) Application of synchronised phasor measurements to realtime transient stability prediction. IEE Proceedings Generation, Transm Distr 142(4): 355–360

    Article  Google Scholar 

  • Liu CW, Tsay SS, Wang YJ (1999b) Neuro-fuzzy approach to real-time transient stability prediction based on synchronized phasor measurements. Electr Power Syst Res 49(2): 123–127

    Article  Google Scholar 

  • Liu G, Venkatasubramanian V (2008) Oscillation monitoring from ambient PMU measurements by frequency domain decomposition. 2008 IEEE International Symposium on Circuits and Syst, Seattle, 18–21 May 2008

    Google Scholar 

  • Liu M, Zhang B, Yao L et al (2008) PMU based voltage stability analysis for transmission corridors. Proceedings of the 3rd International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, Nanjing, 6–9 April 2008

    Google Scholar 

  • Liu Y, Lin F, Chu X (2002) Transient stability prediction based on PMU and FCRBFN. Proceedings of the 5th International Conference on Power System Management and Control, London, 17–19 April 2002

    Google Scholar 

  • Ma J (2008) Advanced techniques for power system stability analysis. PhD Dissertation, The University of Queensland, Brisbane, Australia

    Google Scholar 

  • Ma J, Makarov YV, Miller CH et al (2008) Use multi-dimensional ellipsoid to monitor dynamic behavior of power systems based on PMU measurement. Proceedings of IEEE Power and Energy Society General Meeting—Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, 20–24 July 2008

    Google Scholar 

  • Makarov YV, Miller CH, Nguyen TB (2007) Characteristic ellipsoid method for monitoring power system dynamic behavior using phasor measurements. 2007 iREP Symposium-Bulk Power System Dynamics and Control — VII Revitalizing Operational Reliability, Charleston, 19-24 August 2007

    Google Scholar 

  • Makarov YV, Miller CH, Nguyen TB et al (2008) Monitoring of power system dynamic behavior using characteristic ellipsoid method. The 41th Hawaii International Conference on System Sciences, Hawaii, USA, 7–10 January 2008

    Google Scholar 

  • Martin KE, Benmouyal G, Adamiak MG et al (1998) IEEE standard for synchrophasor for power systems. IEEE Trans Power Deliv 13(1): 73–77

    Article  Google Scholar 

  • Mei K, Rovnyak SM, Ong CM (2008) Clustering-based dynamic event location using wide-area phasor measurements. IEEE Trans Power Syst 23(2): 673–679

    Article  Google Scholar 

  • Meliopoulos APS, Cokkinides GJ, Wasynczuk O et al (2006) PMU data characterization and application to stability monitoring. Proceedings of IEEE Power Engineering Society General Meeting, Piscataway, 18–22 June 2006

    Google Scholar 

  • MiloÅ¡ević B, Begović M (2003a) Nondominated sorting genetic algorithm for optimal phasor measurement placement. IEEE Trans Power Syst 18(1): 69–75

    Article  Google Scholar 

  • MiloÅ¡ević B, Begović M (2003b) Voltage-stability protection and control using a wide-area network of phasor measurements. IEEE Trans Power Syst 18(1): 121–127

    Article  Google Scholar 

  • Monchusi BB, Mitani Y, Changsong L et al (2008) PMU based power system stability analysis. Proceedings of IEEE Region 10 Conference, Hyderabad, 19–21 November 2008

    Google Scholar 

  • NASPI (2009a) North American Synchrophasor Initiative, http://www.naspi.org/. Accessed 22 June 2009

    Google Scholar 

  • NASPI (2009b) Actual and potential phasor data applications. Avilable at: http://www.naspi.org/phasorappstable.pdf. Accessed 22 June 2009

    Google Scholar 

  • Nuqui RF, Phadke AG (2005) Phasor measurement unit placement techniques for complete and incomplete observability. IEEE Trans Power Deliv 20(4): 2381–2388

    Article  Google Scholar 

  • Ota Y, Ukai H, Nakamura K et al (2002) PMU based midterm stability evaluation of wide-area power system. 2002 IEEE/PES Transmission and Distribution Conference and Exhibition: Asia Pacific, Yokohama, 6-10 October 2002

    Google Scholar 

  • Pai MA (1989) Energy Function Analysis for Power System Stability. Kluwer, Boston

    Google Scholar 

  • Peng J, Sun Y, Wang HF (2006) Optimal PMU placement for full network observability using Tabu search algorithm. Electr Power Energy Syst 28(4): 223–231

    Article  Google Scholar 

  • Phadke AG (1993) Synchronized phasor measurements in power systems. IEEE Comput Appl Power 6(2): 10–15

    Article  MathSciNet  Google Scholar 

  • Phadke AG, Thorp JS, Adamiak MG (1983) A new measurement technique for tracking voltage phasors, local system frequency, and rate of change of frequency. IEEE Trans Power App Syst, PAS-102(5): 1025–1038

    Article  Google Scholar 

  • Phadke AG, Thorp JS, Karimi KJ (1986) State estimation with phasor measurements. IEEE Trans Power Syst 1(1): 233–241

    Article  Google Scholar 

  • Radovanovic A (2001) Using the internet in networking of synchronized phasor measurement units. Inte J Electr Power Energy Syst 23(3): 245–250

    Article  MathSciNet  Google Scholar 

  • Rakpenthai C, Premrudeepreechacharn S, Uatrongjit S et al (2007) An optimal PMU placement method against measurement loss and branch outage. IEEE Trans Power Deliv 22(1): 101–107

    Article  Google Scholar 

  • Rasmussen J, Jørgensen P (2006) Synchronized phasor measurements of a power system event in eastern Denmark. IEEE Trans Power Syst 21(1): 278–284

    Article  Google Scholar 

  • Samantaray SR, Tripathy LN, Dash PK (2009) Differential equation-based fault locator for unified power flow controller-based transmission line using synchronised phasor measurements. IET Generation, Trans Distrib 3(1): 86–98

    Article  Google Scholar 

  • Silverman BW, Titterington DM (1980) Minimum covering ellipses. SIAM J Statist Sci Comput 1(4): 401–409

    Article  MATH  MathSciNet  Google Scholar 

  • Smon I, Verbic G, Gubina F (2006) Local voltage-stability index using Tellegen’s theorem. IEEE Trans Power Syst 21(3): 1267–1275

    Article  Google Scholar 

  • Snyder AF, Hadjsaid N, Georges D et al (1998) Inter-area oscillation damping with power system stabilizers and synchronized phasor measurements. Proceedings of International Conference on Power System Technology, Beijing, 18–21 August 1998

    Google Scholar 

  • Sobajic DJ, Pao YH (1989) Artificial Neural-Net based dynamic security assessment for electric power systems. IEEE Trans Power Syst 4(1): 220–228

    Article  Google Scholar 

  • Sun K, Likhate S, Vittal V et al (2007) An online dynamic security assessment scheme using phasor measurements and decision trees. IEEE Trans Power Syst 22(4): 1935–1943

    Article  Google Scholar 

  • Sun P, Freund RM (2004) Computation of minimum-volume covering ellipsoids. Oper Res 52(5): 690–706

    Article  MATH  MathSciNet  Google Scholar 

  • Taylor CW, Erickson DC, Martin KE et al (2005) WACS-wide-area stability and voltage control system: R & D and online demonstration. Proceedings of the IEEE 93(5): 892–906

    Article  Google Scholar 

  • Thorp JS, Phadke AG, Karimi KJ (1985) Real time voltage-phasor measurements for static state estimation. IEEE Trans Power App Syst, PAS-104(11): 3098–3106

    Article  Google Scholar 

  • Tiwari A, Ajjarapu V (2007) Event identification and contingency assessment for voltage stability via PMU. Proceedings of the 39th North American Power Symposium, Las Cruces, 30 September–2 October 2007

    Google Scholar 

  • Trudnowski DJ, Johnson JM, Hauer JF (1999) Making Prony analysis more accurate using multiple signals. IEEE Trans Power Syst 14(1): 226–231

    Article  Google Scholar 

  • Uhlen K, Warland L, Gjerde JO et al (2008) Monitoring amplitude, frequency and damping of power system oscillations with PMU measurements. 2008 IEEE Power and Energy Society General Meeting—Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, 20–24 July 2008

    Google Scholar 

  • Verbic G, Gubina F (2000) A new concept of protection against voltage collapse based on local phasors. Proceedings of International Conference on Power System Technology, Perth, 4–7 December 2000

    Google Scholar 

  • Verbic G, Gubina F (2004) A new concept of voltage-collapse protection based on local phasors. IEEE Trans Power Deliv 19(2): 576–581

    Article  Google Scholar 

  • Vu K, Begovic MM, Novosel D et al (1999) Use of local measurements to estimate voltage-stability margin. IEEE Trans Power Syst 14(3): 1029–1035

    Article  Google Scholar 

  • Wang C, Dou CX, Li XB (2007) A WAMS/PMU-based fault location technique. Electr Power Syst Res 77(8): 936–945

    Article  Google Scholar 

  • Wang L, Wang X, Morison K (1997) Quantitative search of transient stability limits using EEAC. Proceedings of IEEE PES Summer Meeting, Berlin, 20–24 July 1997

    Google Scholar 

  • Wang YJ, Liu CW, Liu YH (2005) A PMU based special protection scheme: A case study of Taiwan power system. Int J Electr Power Energy Syst 27(3): 215–223

    Article  Google Scholar 

  • Xu B, Abur A (2004) Observability analysis and measurement placement for systems with PMUs. Proceedings of IEEE PES Power Systems Conference and Exposition, New York, 10–13 October 2004

    Google Scholar 

  • Xu B, Abur A (2005) Optimal placement of phasor measurement units for state estimation. PSERC, Final Project Report

    Google Scholar 

  • Xue Y, Custem TV, Ribbens-Pavella M (1989) Extended equal area criterion justifications, generalizations, applications. IEEE Trans Power Syst 4(1): 44–52

    Article  Google Scholar 

  • Xue Y, Yu Y, Li J et al (1998) A new tool for dynamic security assessment of power systems. Control Eng Pract (6): 1511–1516

    Google Scholar 

  • Yu CS, Liu CW, Yu SL et al (2001) A new PMU-based fault location algorithm for series compensated lines. IEEE Power Eng Rev 21(11): 58–58

    Article  Google Scholar 

  • Yu CS, Liu CW, Yu SL et al (2002) A new PMU based fault location algorithm for series compensated lines. IEEE Trans Power Deliv 17(1): 33–46

    MathSciNet  Google Scholar 

  • Zhao L, Abur A (2005) Multiarea state estimation using synchronized phasor measurements. IEEE Trans Power Syst 20(2): 611–617

    Article  Google Scholar 

  • Zhou M, Centeno VA, Thorp JS et al (2006) An alternative for including phasor measurements in state estimators. IEEE Trans Power Syst 21(4): 1930–1937

    Article  Google Scholar 

  • Zivanovic R, Cairns C (1996) Implementation of PMU technology in state estimation: An overview. Proceedings of the 4th IEEE AFRICON Conference, Stellenbosch, 25-27 September 1996

    Google Scholar 

Download references

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Higher Education Press, Beijing and Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Ma, J., Makarov, Y., Dong, Z. (2010). Phasor Measurement Unit and Its Application in Modern Power Systems. In: Emerging Techniques in Power System Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04282-9_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04282-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04281-2

  • Online ISBN: 978-3-642-04282-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics