State Estimation of Power System Embedded with FACTS devices and PMUs

  • Authors

    • Balaji Venkateswaran V
    • Neeraj Kumar Sharma
    • Deepali Yadav
    2018-03-11
    https://doi.org/10.14419/ijet.v7i2.6.10567
  • Observability Analysis, Differential Evolution, State Estimation, Bad data analysis, UPFC, PMU

  • In recent days, the power system is incorporated with Flexible AC Transmission System (FACTS) devices for compensation of reactive power to maintain the stability of the system. The stability of the system is highly dependent on the state variables which are the outcomes of a state estimator in the power system. To improve the efficiency of a state estimator, high precision measuring devices such as Phasor Measurement Units (PMUs) are installed in the power system. Hence a state estimator embedded with these compensatory devices and PMUs is necessary for estimation of state variables. The present work has been carried out in three steps. Step 1: Considering the cost of PMUs and the availability of the communication network in the particular location, PMUs are optimally placed in the nodes of the system so that all critical measurements are transmuted into redundant ones using differential evolution (DE) algorithm to perform observability analysis. Step 2: A hybrid state estimation is performed by including the mathematical model of FACTS devices and PMUs. Step 3: It is shown that by installing optimal number of PMUs at desired location, multiple bad data detection and identification capability of residual method is considerably improved. Lastly, numerical simulation with standard IEEE 14 bus system, IEEE 118 bus system and a practical 246 bus system of northern region power grid (NRPG) is presented to confirm the effectiveness of the proposed approach in assessing the estimation of the system state variables.

  • References

    1. [1] Abur A, Expósito AG. Power system state estimation: theory and implementation. Power 2004:327.

      [2] Dy Liacco TE. The role and implementation of state estimation in an energy management system. Int J Electr Power Energy Syst 1990;12:75–9. doi:10.1016/0142-0615(90)90002-S.

      [3] Schweppe F, Wildes J. Power System Static-State Estimation, Part I: Exact Model. IEEE Trans Power Appar Syst 1970;PAS-89:120–5. doi:10.1109/TPAS.1970.292678.

      [4] Schweppe F, Rom D. Power System Static-State Estimation, Part II: Approximate Model. IEEE Trans Power Appar Syst 1970;PAS-89:125–30. doi:10.1109/TPAS.1970.292679.

      [5] Schweppe F. Power System Static-State Estimation, Part III: Implementation. IEEE Trans Power Appar Syst 1970;PAS-89:130–5. doi:10.1109/TPAS.1970.292680.

      [6] Hubbi W, Shirazi F. A line flow only power system state estimator. Electr Power Syst Res 1990;19:229–37. doi:10.1016/0378-7796(90)90036-3.

      [7] Ding Junce, Cai Zexiang. Mixed Measurements State Estimation Based on Wide-Area Measurement System and Analysis. 2005 IEEE/PES Transm. Distrib. Conf. Expo. Asia Pacific, IEEE; 2005, p. 1–5. doi:10.1109/TDC.2005.1546795.

      [8] Moon YH, Park YM, Lee KJ. Observable island identification for state estimation using incidence matrix. Automatica 1988;24:71–5. doi:10.1016/0005-1098(88)90008-8.

      [9] Clements KA. Observability methods and optimal meter placement. Int J Electr Power Energy Syst 1990;12:88–93. doi:10.1016/0142-0615(90)90004-U.

      [10] Boisen MB. Power System Observability With Minimal Phasor Measurement Placement 1993;8:707–15.

      [11] Gou B. Optimal Placement of PMUs by Integer Linear Programming 2008;23:1525–6.

      [12] Hajian M, Ranjbar AM, Amraee T, Shirani AR. Optimal Placement of Phasor Measurement Units : Particle Swarm Optimization Approach n.d.

      [13] Aminifar F, Fotuhi-firuzabad M, Safdarian A. Optimal PMU Placement Based on Probabilistic Cost/Bene fi t Analysis 2012;28:1–2.

      [14] Venkateswaran VB, Kala VSC. Observability analysis and optimal placement of PMU using Differential Evolution algorithm. 2012 Int. Conf. Emerg. Trends Electr. Eng. Energy Manag., IEEE; 2012, p. 205–9. doi:10.1109/ICETEEEM.2012.6494461.

      [15] Chakrabarti S, Kyriakides E. Optimal placement of phasor measurement units for power system observability. IEEE Trans Power Syst 2008;23:1433–40. doi:10.1109/TPWRS.2008.922621.

      [16] Narain G. Hingorani; Laszlo Gyugyi. Understanding FACTS Concepts and Technology. vol. XXXIII. IEEE Press Marketing; 2000. doi:10.1007/s13398-014-0173-7.2.

      [17] Pillay A, Prabhakar Karthikeyan S, Kothari DP. Congestion management in power systems – A review. Int J Electr Power Energy Syst 2015;70:83–90. doi:10.1016/j.ijepes.2015.01.022.

      [18] Xu B, Abur A. State Estimation of Systems With UPFCs Using the Interior Point Method. IEEE Trans Power Syst 2004;19:1635–41. doi:10.1109/TPWRS.2004.831703.

      [19] Rakpenthai C, Premrudeepreechacharn S, Uatrongjit S. Power system with multi-type {FACTS} devices states estimation based on predictor–corrector interior point algorithm. Int J Electr Power EnergySyst2009;31:160–6. doi:http://dx.doi.org/10.1016/j.ijepes.2008.10.010.

      [20] Kim B-H, Kim H, Moon Y-H. State Estimation of Electric Power Systems with FACTS and HVDC Devices. J Int Counc Electr Eng 2011;1:247–51. doi:10.5370/JICEE.2011.1.3.247.

      [21] Chen J, Abur A. Placement of PMUs to Enable Bad Data Detection in State Estimation. IEEE Trans Power Syst 2006;21:1608–15. doi:10.1109/TPWRS.2006.881149.

      [22] Angeles-Camacho EACRF-EHAC. FACTS: Modelling and Simulation in Power Networks. vol. 53. John Wiley & Sons; 2004. doi:10.1017/CBO9781107415324.004.

      [23] Monticelli A, Garcia A. Reliable Bad Data Processing for Real-Time State Estimation. IEEE Trans Power Appar Syst 1983;PAS-102:1126–39. doi:10.1109/TPAS.1983.318053.

      [24] Abdel-Rahim AMM, Padhy NP. Newton-Raphson UPFC model for power flow solution of practical power networks with sparse techniques. 2004 IEEE Int. Conf. Electr. Util. Deregulation, Restruct. Power Technol. Proc., vol. 1, IEEE; n.d., p. 77–83. doi:10.1109/DRPT.2004.1338472.

      [25] Taylor P, Sodhi R, Srivastava SC, Singh SN. Electric Power Components and Systems Phasor-assisted Hybrid State Estimator Phasor-assisted Hybrid State Estimator 2010:37–41. doi:10.1080/15325000903376925.

  • Downloads

  • How to Cite

    Venkateswaran V, B., Kumar Sharma, N., & Yadav, D. (2018). State Estimation of Power System Embedded with FACTS devices and PMUs. International Journal of Engineering & Technology, 7(2.6), 199-205. https://doi.org/10.14419/ijet.v7i2.6.10567