Suttichai PREMRUDEEPREECHACHARN, Naret SUYAROJ, Neville Robert WATSON

Transient state estimation with the Bergeron transmission line model

Transient state estimation (TSE) was used to determine the state values that have no measurement equipmentplaced in an electric power system with transient phenomena. Previous papers used the PI model for TSE with a shorttransmission line, but longer lines require the development of algorithms that include the distributed parameters oftransmission lines with the Bergeron model. The test system was a 10-bus power system. The simulated transient wascaused by a fault event, resulting in different persistent voltage drops that ranged from 10% to 90% at selected buses.In addition, noises were applied to evaluate the algorithm, which was de ned to be normally distributed. Noise at 1%,2%, and 3% was added to all measurements. The results showed that the developed TSE provided good estimation atthe locations that had no measurement equipment for distributed transmission lines.

PDF

___

[1]Rakpenthai C, Premrudeepreechacharn S, Uatrongjit S, Watson NR. An improved PMUs placement method forpower system state estimation. In: International Power Engineering Conference; 29 November{2 December 2005;Singapore. pp. 1-4.
[2]Rakpenthai C, Premrudeepreechacharn S, Uatrongjit S, Watson NR. Measurement placement for power systemstate estimation by decomposition technique. In: IEEE International Conference on Harmonics and Quality ofPower; 12{15 September 2004; Lake Placid, NY, USA. pp. 414-418.
[3]Kulanthaisamy A, Vairamani R, Karunamurthi NK, Koodalsamy C. A multi-objective PMU placement methodconsidering observability and measurement redundancy using ABC algorithm. Adv Electr Comp Eng 2014; 14:117-128.
[4]Yu KKC, Watson NR. An approximate method for transient state estimation. IEEE T Power Deliver 2007; 22:1680-1687.
[5]Watson NR, Yu KKC. Transient state estimation. In: 13th International Conference on Harmonics and Quality ofPower; 28 September{1 October 2008; Wollongong, Australia. pp. 1-6.
[6]Farzanehrafat A, Watson NR. Power quality state estimator for smart distribution grids. IEEE T Power Syst 2013;28: 2183-2191.
[7]Monzani RC, Prado AJ, Kurokawa S, Bovolato LF, Filho JP. Using a low complexity numeric routine for solvingelectromagnetic transient simulations. In: Katsikis VN, editor. MATLAB - A Fundamental Tool for Scienti cComputing and Engineering Applications - Volume 3. Rijeka, Croatia: InTech, 2012. pp. 463-484.
[8]Junzhang O, Zhonghui Z. The research of fault location of transmission line based on Bergeron model. In: Inter-national Conference on Advanced Computer Theory and Engineering; 20{22 August 2010; Chengdu, China. pp.300-304.
[9]Zhong Y, Kang XN, Jiao ZB. A novel distance protection algorithm for long-distance transmission lines. In: IETInternational Conference on Developments in Power System Protection; 31 March{3 April 2014; Denmark. pp. 1-5.
[10]Mamis MS, Kaygusuz A, Koksal M. State variable distributed-parameter representation of transmission line fortransient simulations. Turk J Elec Eng & Comp Sci 2010; 18: 31-42.
[11]Costa ECM, Kurokawa S, Pissolato J, Prado AJ. Efficient procedure to evaluate electromagnetic transients onthree-phase transmission lines. IET Gener Transm Dis 2010; 4: 1069-1081.
[12]Macias JAR, Exposito AG, Soler AB. A comparison of techniques for state-space transient analysis of transmissionlines. IEEE T Power Deliver 2005; 20: 894-903.
[13]Semlyen A, Abdel-Rahman M. A state variable approach for the calculation of switching transients on a powertransmission line. IEEE T Circ Syst 1982; 29: 624-633.
[14]Garcia N, Acha E. Transmission line model with frequency dependency and propagation effects: A model orderreduction and state-space approach. In: IEEE 2008 Power and Energy Society General Meeting; 20{24 June 2008;USA. pp. 1-7.
[15]Kurokawa S, Yamanaka FNR, Prado AJ, Pissolato J. Using state-space techniques to represent frequency dependentsingle-phase lines directly in time domain. In: IEEE/PES Transmission and Distribution Conference and Exposition:Latin America; 13{15 August 2008; Bogota, Colombia. pp. 1-5.
[16]Watson NR, Arrillaga J. Power Systems Electromagnetic Transients Simulation. IET Power and Energy Series, No.39. 1st ed. London, UK: Institution of Electrical Engineers, 2003.
[17]Dommel HW. Digital computer solution of electromagnetic transients in single-and multiphase networks. IEEE TPower Ap Syst 1969; 88: 388-399.
[18]Abur A, Ozgun O, Magnago FH. Accurate modelling and simulation of transmission line transients using frequencydependent modal transformations. In: IEEE Power Engineering Society Winter Meeting; 2001; Columbus, OH,USA. pp. 1443-1448.
[19]Mamis MS, Arkan M, Keles C. Transmission lines fault location using transient signal spectrum. Int J Elect Power2013; 53: 714-718.
[20]Dursun B, Aydin F, Zontul M, Sener S. Modeling and estimating of load demand of electricity generated fromhydroelectric power plants in Turkey using machine learning methods. Adv Electr Comp Eng 2014; 14: 121-132.
[21]Li XR, Zhao Z. Measures of performance for evaluation of estimators and lters. In: SPIE Conference on Signaland Data Processing of Small Targets; November 2001; San Diego, CA, USA. pp. 1-12.
[22]Pignati M, Zanni L, Sarri S, Cherkaoui R, Boudec JYL, Paolone M. A pre-estimation ltering process of bad datafor linear power systems state estimators using PMUs. In: Power Systems Computation Conference; 18{22 August2014; Wroclaw, Poland. pp. 1-8.
[23]Shi D, Tylavsky DJ, Logic N. An adaptive method for detection and correction of errors in PMU measurements.IEEE T Smart Grid 2012; 3: 1575-1583.