Skip to main content
Log in

A Fast Online Voltage Instability Detection in Power Transmission System Using Wide-Area Measurements

  • Research paper
  • Published:
Iranian Journal of Science and Technology, Transactions of Electrical Engineering Aims and scope Submit manuscript

Abstract

Monitoring voltage stability in real time is a pressing issue for large complex power systems. In this work, reactive power losses calculated from synchrophasor measurements are used to develop a novel voltage instability detection index named SQLVIDI. The proposed index is fast enough to be used for real-time monitoring of voltage stability and for dispatching mitigating control actions in time. The prowess of the proposed index has been tested rigorously on New England 39 bus test system and IEEE 118 bus test system by running time-based simulations. The index successfully detects the impending long-term voltage instability in a timely manner. This timely detection of voltage instability ensure system operator to take preventive control actions to minimize the operational risk. Simulation results show’s that proposed index is simple, reliable, computationally inexpensive and therefore suitable for online real-time detection applications in power systems.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Abbreviations

\(\Psi\) :

Smoothening function

\(Q_{\mathrm{loss}}\) :

Reactive power loss

CQL:

Consecutive reactive Power loss deviation

CQLB:

Reactive power loss deviation from baseload

FACTS:

Flexible AC transmission system

HVDC:

High Voltage DC

OLTC:

On-load tap changer

OXL:

Over-excitation limiter

PMU:

Phasor measurement unit

PSAT:

Power system analysis toolbox

QLVID:

Reactive power loss-based voltage instability detector

QLVIDI:

Reactive power loss-based voltage instability detection index

SQLVIDI:

Smoothed reactive power loss-based voltage instability detection index

STATCOM:

Static Compensator

WAMS:

Wide-area monitoring system

References

  • Abiri E, Rashidi F, Niknam T (2015) An optimal PMU placement method for power system observability under various contingencies. Int Trans Electr Eng Syst 25:589–606

    Article  Google Scholar 

  • Atputharajah A, Saha TK (2009) Power system blackouts: literature review. In: Proceedings in ICIIS, pp 460–465

  • Balamourougan V, Sidhu TS, Sachdev MS (2004) Technique for online prediction of voltage collapse. IEE Proc Gener Transm Distrib 151(4):454–460

    Article  Google Scholar 

  • Carson W (1994) Taylor, power system voltage stability. Mc.Graw-Hill, Singapore

    Google Scholar 

  • Chappa HK, Thakur T, Kazemtabrizi B (2016) A new voltage instability detection index based on real-time synchronophasor measurements. In: International conference on environment and electrical engineering, Florence

  • Chappa HK, Thakur T, Srivastava SC (2015) Reactive power loss based voltage instability detection using synchrophasor technology. In: IEEE PES Asia-Pacific power and energy engineering conference (APPEEC), Brisbane, QLD, pp 1–5

  • Chappa H, Thakur T (2017) Online voltage instability detection in power transmission system. Indian Patent Publication, Application No. 201721014432 A

  • Chen H et al (2017) Widearea measurement-based voltage stability sensitivity and its application in voltage control. Int J Elect Power Energy Syst 88:87–98

    Article  Google Scholar 

  • Cleveland WS (1979) Robust locally weighted regression and smoothing scatterplots. J Am Stat Assoc 74(368):829–836

    Article  MathSciNet  MATH  Google Scholar 

  • Committee Power System Relaying (2014) An overview of the IEEE standard C37.118.2: synchrophasor data transfer for power systems. IEEE Trans Smart Grid 5(4):1980–1984

    Article  Google Scholar 

  • Gadiraju KVR, Kolwalkar A, Gurrala G (2013) Systems and methods for predicting power system instability. U.S 0154614 A1. http://www.freepatentsonline.com/y2013/0154614.html. Accessed 15 Jan 2015

  • Glavic M, Hajian M, Rosehart W, Van Cutsem T (2011) Receding-horizon multi-step optimization to correct nonviable or unstable transmission voltages. IEEE Trans Power Syst 26(3):1641–1650

    Article  Google Scholar 

  • Kamel M, Karrar A, Eltom A (2017) Development and application of a new voltage stability index for on-line monitoring and shedding. IEEE Trans Power Syst 99:1231–1241

    Google Scholar 

  • Kessel P, Glavitsch H (1986) Estimating the voltage stability of a power system. IEE Trans Power Deliv 1(3):346–354

    Article  Google Scholar 

  • Khoshkhoo H, Shahrtash SM (2014) Fast online dynamic voltage instability prediction and voltage stability classification. IET Gener Transm Distrib 8(5):957–965

    Article  Google Scholar 

  • Kim D (2007) System and method for calculating voltage stability risk-index in power system using time series data. U.S 7236898 B2. http://www.freepatentsonline.com/y2005/0256922.html. Accessed 13 Feb 2015

  • Kundur P (1994) Power system stability and control. Mc.Graw-Hill, New York

    Google Scholar 

  • Lachs WR, Sutanto D (1992) Voltage instability in interconnected power systems: a simulation approach. IEEE Trans Power Syst 7(2):753–761

    Article  Google Scholar 

  • Larsson M, Karlsson D (2003) Coordinated system protection scheme against voltage collapse using heuristic search and predictive control. IEEE Trans Power Syst 18(3):1001–1006

    Article  Google Scholar 

  • Lee DHA (2016) Voltage stability assessment using equivalent nodal analysis. IEEE Trans Power Syst 31(1):454–463

    Article  Google Scholar 

  • Lee BH, Lee KY (1991) A study on voltage collapse mechanism in electric power systems. IEEE Trans Power Syst 6(3):966–973

    Article  Google Scholar 

  • Lim JM, DeMarco CL (2016) SVD-based voltage stability assessment from phasor measurement unit data. IEEE Trans Power Syst 31(4):2557–2565

    Article  Google Scholar 

  • Machowski J, Bialek JW, Bumby J (2008) Power system dynamics. Wiley, New York

    Google Scholar 

  • Milano F (2005) An open source power system analysis toolbox. IEEE Trans Power Syst 20(3):1199–1206

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Moghavvemi M, Omar FM (1998) Technique for contingency monitoring and voltage collapse prediction. IEE Proc Gener Transm Distrib 145(3):634–640

    Article  Google Scholar 

  • Musirin I, Khawa T, Rahman A (2002) Novel fast voltage stability index (FVSI) for voltage stability analysis in power transmission system. In: Proceedings of the student conference on research and development proceedings, pp 265–268

  • Naik SD, Khedkar MK, Bhat SS (2015) Effect of line contingency on static voltage stability and maximum loadability in large multi bus power system. Int J Electr Power Energy Syst 67:448–452

    Article  Google Scholar 

  • Ordacgi Filho JM (2010) Brazilian blackout 2009: blackout watch. https://www.pacw.org/fileadmin/doc/MarchIssue2010/Brazilian_Blackout_march_2010.pdf. Accessed July 2016

  • Power System Relaying Committee (2011) C37.118.1-2011. IEEE standard for synchrophasor measurements for power systems. IEEE Standards

  • Prabhakar P, Kumar A (2016) Voltage stability boundary and margin enhancement with FACTS and HVDC. Int J Electr Power Energy Syst 82:429–438

    Article  Google Scholar 

  • Project Group Turkey (2015) Report on blackout in Turkey on 31st March 2015. In: European network of transmission system operators for electricity

  • Rampurkar V, Pentayya P, Mangalvedekar HA, Kazi F (2016) Cascading failure analysis for indian power grid. IEEE Trans Smart Grid 7(4):1951–1960

    Article  Google Scholar 

  • Rashidi F, Abiri E, Niknam T, Salehi MR (2015) Optimal placement of PMUs with limited number of channels for complete topological observability of power systems under various contingencies. Int J Electr Power Energy Syst 67:125–137

    Article  Google Scholar 

  • Saha Roy BK, Sinha AK, Pradhan AK (2012) An optimal PMU placement technique for power system observability. Int J Electr Power Energy Syst 42:71–77

    Article  Google Scholar 

  • Salehizadeh MR, Rahimi-Kian A, Hausken K (2015a) A leader–follower game on congestion management in power systems. In: Game theoretic analysis of congestion, safety and security. Springer, New York, pp 81–112

    Chapter  Google Scholar 

  • Salehizadeh MR, Rahimi-Kian A, Oloomi Buygi M (2015b) A multi-attribute congestion driven approach for evaluation of power generation plans. Int Trans Electr Energy Syst 25(3):482–497

    Article  Google Scholar 

  • Salehizadeh MR, Rahimi-Kian A, Oloomi-Buygi M (2015c) Security-based multi-objective congestion management for emission reduction in power system. Int J Electr Power Energy Syst 65:124–135

    Article  Google Scholar 

  • Sharma P, Kumar A (2016) Thevenin’s equivalent based P–Q–V voltage stability region visualization and enhancement with FACTS and HVDC. Int J Electr Power Energy Syst 80:119–127

    Article  Google Scholar 

  • Smith WH, Wang L, Kundur P (2007) Training for blackouts [In My View]. IEEE Power Energy Mag 5(3):112–109

    Article  Google Scholar 

  • Sode-Yome A, Mithulananthan N, Lee KY (2007) A comprehensive comparison of FACTS devices for enhancing static voltage stability. In: IEEE proceedings of power engineering society general meeting, Tampa, FL, pp 1–8

  • Sodhe R, Srivastava SC, Singh SN (2012) A simple scheme for wide area detection of impending voltage instability. IEEE Trans Smart Grid 3(2):818–827

    Article  Google Scholar 

  • Sodhi R, Srivastava SC, Singh SN (2010) Optimal PMU placement method for complete topological and numerical observability of power system. Electr Power Syst Res 80:1154–1159

    Article  Google Scholar 

  • Srayashi K, Dheeman C, Sourav P (2015) V–Q sensitivity-based index for assessment of dynamic voltage stability of power systems. IET Gener Transm Distrib 9(7):677–685

    Article  Google Scholar 

  • Taylor CW, Erickson DC (1997) Recording and analyzing the July 2 cascading outage [Western USA power system]. IEEE Comput Appl Power 10(1):26–30

    Article  Google Scholar 

  • Tobon Villa JE, Gutierrez REC, Ramirez JM (2014) Voltage collapse detection based on local measurements. Int J Electr Power Syst Res 107:77–84

    Article  Google Scholar 

  • Vournas C, Van Cutsem T (2008) Local identification of voltage emergency situations. IEEE Trans Power Syst 23(3):1239–1248

    Article  Google Scholar 

  • Wang Y, Li W, Lu J (2009) A new node voltage stability index based on local phasors. Electr Power Syst Res 79(1):265–271

    Article  Google Scholar 

  • Wen JY, Wu QH, Turner DR, Cheng SJ, Fitch J (2004) Optimal coordinated voltage control for power system voltage stability. IEEE Trans Power Syst 19(2):1115–1122

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank Dr. S. C. Srivastava, IIT Kanpur, for providing the laboratory facility to develop this index.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hemanthakumar Chappa.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chappa, H., Thakur, T. A Fast Online Voltage Instability Detection in Power Transmission System Using Wide-Area Measurements. Iran J Sci Technol Trans Electr Eng 43 (Suppl 1), 427–438 (2019). https://doi.org/10.1007/s40998-018-0120-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40998-018-0120-2

Keywords

Navigation