Improving state estimation in smart distribution grid using synchrophasor technology: a comparison study

• Autorzy: Richter M. , Komarnicki P. , Hauer I.

Identyfikatory

DOI

10.24425/123657

• Języki publikacji: EN

Abstrakty

EN

Both the growing number of dispersed generation plants and storage systems and the new roles and functions on the demand side (e.g. demand side management) are making the operation (monitoring and control) of electrical grids more complex, especially in distribution. This paper demonstrates how to integrate phasor measurements so that state estimation in a distribution grid profits optimally from the high accuracy of PMUs. Different measurement configurations consisting of conventional and synchronous mea- surement units, each with different fault tolerances for the quality of the calculated system state achieved, are analyzed and compared. Weighted least squares (WLS) algorithms for conventional, linear and hybrid state estimation provide the mathematical method used in this paper. A case study of an 18-bus test grid with real measured PMU data from a 110 kV distribution grid demonstrates the improving of the system’s state variable’s quality by using synchrophasors. The increased requirements, which are the prerequisite for the use of PMUs in the distribution grid, are identified by extensively analyzing the inaccuracy of measurement and subsequently employed to weight the measured quantities.

Słowa kluczowe

EN

accuracy analysis; case study; distribution grid state estimation; phasor measurement units; weighted least squares

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2018
• Tom: Vol. 67, nr 3
• Strony: 469--–483
• Opis fizyczny: Bibliogr 49 poz., tab., wz.

Twórcy

autor

Richter M.

• Fraunhofer Institute for Factory Operation and Automation, Germany

autor

Komarnicki P.

• Fraunhofer Institute for Factory Operation and Automation, Germany

autor

Hauer I.

• Otto von Guericke University Magdeburg, Germany

Bibliografia

• [1] Deutsche Energie-AgenturGmbH(dena), dena-Studie Systemdienstleistungen 2030. Sicherheit und Zuverlässigkeit einer Stromversorgung mit hohem Anteil Erneuerbarer Energien, dena, Berlin, Germany (2014).
• [2] Stötzer M., Hauer I., Richter M., Styczynski Z.A., Potential of Demand Side Integration to maximize use of Renewable Energy Sources in Germany, Applied Energy, vol. 146, pp. 344–352 (2015).
• [3] Pedersen R., Findrik M., Sloth C., Schwefel H.-P., Network condition based adaptive control and its application to power balancing in electrical grids, Sustainable Energy, Grids and Networks, vol. 10, pp. 118–127 (2017).
• [4] Christakou K., A unified control strategy for active distribution networks via demand response and distributed energy storage systems, Sustainable Energy, Grids and Networks, vol. 6, pp. 1–6 (2016).
• [5] Bundesministerium fürWirtschaft und Energie, SECVER – Sicherheit und Zuverlässigkeit von Verteilnetzen auf dem Weg zu einem Energieversorgungssystem von morgen, Otto-von-Guericke-Universität Magdeburg, 2013, (online), available: http://www.secver.de., accessed May 2015.
• [6] Wache M., Application of Phasor Measurment Units in Distribution Networks, in Proc. of 22nd International Conference on Electricity Distribution, Stockholm, Sweden (2013).
• [7] Rinaldi S., Giustina D.D., Ferrari P., Flammini A., Distributed monitoring system for voltage dip classification over distribution grid, Sustainable Energy, Grids and Networks, vol. 6, pp. 70–80 (2016).
• [8] Phadke A., Martin K., Novosel D., Karlsson D., Long W., Smart Grid Applications of Wide-Area Measurements, Madison, WI: University of Wisconsin-Madison (2013).
• [9] Korres G.N., Manousakis N.M., A state estimator including conventional and synchronizes phasor measurements, Computers and Electrical Engineering, vol. 38, pp. 294–305 (2012).
• [10] Bi T.S., Qin X.H., Yang Q.X., A novel hybrid state estimator for including synchronized phasor measurements, Electric Power System Research, vol. 78, pp. 1342–1352 (2007).
• [11] Glavic M., Cutsem T.V., Tracking network state from combined SCADA and synchronized phasor measurements, in Proc. of 2013 IREP Symposium, Rethymnon, Greece (2013).
• [12] Das K., Seetharam D.P., Reddi R.K., Sinha K.A., Real-time Hybrid State Estimation Incorporating SCADA and PMU Measurements, in Proc. of 2012 IEEE ISGT Europe, Berlin, Germany (2012).
• [13] Sexauer J., Javanbakht P., Mohagheghi S., Phasor Measurement Units for the Distribution Grid: Necessity and Benefits, in Proc. of Innovative Smart Grid Technologies (ISGT), Washington D.C. (2013).
• [14] Hurtgen M., Maun J.-C., Advantages of power system state estimation using Phasor Measurement Units, in Proc. of 16th PSCC, Glasgow, Scotland (2008).
• [15] Nuqui R.F., Phadke A.G., Phasor Measurement Unit Placement Techniques for Complete and Incomplete Observability, IEEE Trans. on Power Delivery, vol. 20, no. 4, pp. 2381–2388 (2005).
• [16] Raposo A.A.M., Rodrigues A.B., da Silva M.G., Optimal meter placement algorithm for state estimation in power distribution networks, Electric Power Systems Research, vol. 147, pp. 22–30 (2017).
• [17] Liu J., Tang J., Ponci F., Monti A., Muscas C., Pegoraro P.A., Trade-Offs in PMU Deployment for State Estimation in Active Distribution Grids, IEEE Transactions on Smart Grid, vol. 3, pp. 915–924 (2012).
• [18] Richter M., Wolter M., Naumann A., Komarnicki P., Practical Experiences on PMU-based Linear State Estimation in Distribution Grids, in Proc. of 2016 IEEE PES General Meeting, Boston, MA (2016).
• [19] Melo I.D., Pereira J.L.R., Variz A.M., Garcia P.A.N., Harmonic state estimation for distribution networks using phasor measurement units, Electric Power Systems Research (2017).
• [20] Macii D., Barchi G., Schenato L., On the Role of Phasor Measurement Units for Distribution System State Estimation, in Prof. of 2014 IEEEWorkshop on Environmental Energy and Structural Monitoring Systems (EESMS), Naples, FL (2014).
• [21] Kahunzire A.E., Awodele K.O., Improving Distribution Network State Estimation by means of Phasor Measurement Units, in Proc. of 49th UPEC, Cluj-Napoca, Romania (2014).
• [22] Zanni L., Colangelo D., Cherkaoui R., Paolone M., Impact of Synchrophasor Measurement Types and Uncertainties on the Accuracy of Distribution System Linear State Estimators, in Proc. of 2015 PowerTech, Eindhoven, Netherlands (2015).
• [23] McCamish B., Kulkarni J., Ke Z., Harpool S., Huo C., Brekken T., Cotilla-Sanchez E., Zhang J., von Jouanne A., Yokochi A., A rapid PMU-based load composition and PMU estimation method, Electric Power Systems Research, Bd. 143, pp. 44–52 (2017).
• [24] Stewart E.M., von Meier A., Phasor Measurements for Distribution System Applications, in Smart Grid Handbook, Wiley, pp. 1–10 (2016).
• [25] Pignati M., Popovic M., Barreto S., Cherkaoui R., Dario Flores G., Mohiuddin M., Paolone M., Romano P., Sarri S., Tesfay T., Tomozei D.-C., Zanni L., Real-time state estimation of the EPFL- campus medium-voltage grid by using PMUs, in Proc. of 2015 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, Washington DC, USA (2015).
• [26] Power Sensors Ltd., Synchrophasors for Distribution, Microgrid: PQube3 MicroPMU, PSL, Alameda, CA, USA.
• [27] Gurbiel M., Komarnicki P., Styczynski Z.A., Kereit M., Blumschein J., Buchholz B.M., Usage of phasor measurement units for industrial applications, in Proc. of. 2011 IEEE Power and Energy Society General Meeting, Detroit, MI, USA (2011).
• [28] Göl M., Abur A., A Hybrid State Estimator for Systems with limited Number of PMUs, IEEE Transactions on Power Systems, pp. 1511–1517, (2015).
• [29] Jiang W., Vittal V., Heydt G.T., A Distributed State Estimator Utilizing Synchronized Phasor Measurements, IEEE Transactions on Power Systems, vol. 22, no. 2, pp. 563–571 (2007).
• [30] Powalko M., Komarnicki P., Rudion K., Styczynski Z.A., Enhancing virtual power plant observability with PMUs, in 2010 5th International Conference on Critical Infrastructure (CRIS), Beijing, China (2010).
• [31] International Electrotechnical Commission (IEC), IEC 61869 – Instrument transformers, IEC, (2007).
• [32] Ritz Messwandler GmbH & Co., Hochspannungs-Messwandler, Hamburg, Germany: Ritz Messwandler GmbH & Co. (1998).
• [33] Pfiffner Instrument Transformers Ltd., Combined instrument transformers EJOF (24-170) kV, Hirschtal, Switzerland: Pfiffner Instrument Transformers Ltd. (2015).
• [34] Allan D.W., Ashby N., Hodge C.C., The Science of Timekeeping – Application Note 1289, Hewlett-Packard (1997).
• [35] Arbiter Systems, Datasheet Model 1133A Power Sentinel (TM), Paso Robles, CA: Arbiter Systems, Inc.
• [36] Meinberg Funkuhren GmbH und Co. KG, Technische Daten GPS161xHS GPS-Empfänger, Bad Pyrmont, Germany: Meinberg Funkuhren GmbH und Co. KG (2009).
• [37] Jaschinsky M., Netzfrequenz.info, (online), available: www.netzfrequenz.info, accessed December 2015.
• [38] Siemens AG, Digitaler Störschreiber SIMEAS-R PMU Handbuch, Siemens AG (2012).
• [39] Frigo G., Narduzzi C., Colangelo D., Pignati M., Paolone M., Definition and assessment of reference values for PMU calibration in static and transient conditions, in Proc. of 7th IEEE International Workshop on Applied Measurements for Power Systems, Aachen, Germany (2016).
• [40] Komarnicki P., Dzienis C., Styczynski Z.A., Blumschein J., Centeno V., Practical Experience with PMU System Testing and Calibration Requirements, in Proc. of 2008 IEEE Power and Energy Society General Meeting, Pittsburgh, PA, USA (2008).
• [41] Richter M., PMU-basierte Zustandsabschaetzung in Smart Distribution (Dissertation), Otto von Guericke University Magdeburg: Res Electricae Magdeburgenses (2016).
• [42] Baltensperger R., Loosli A., Sauvain H., Zima M., Andersson G., Nuqui R., An Implementation of two-stage Hybrid State Estimation with limited Number of PMU, 10th IET International Conference on Developments in Power System Protection (DPSP 2010), Managing the Change, Manchester, UK (2010).
• [43] IEEE Power and Energy Society, IEEE Std C37.118.1-2011 for Synchrophasor Measurements for Power Systems, IEEE Standards Association, New York, NY (2011).
• [44] Korres G.N., Manousakis N.M., A state estimator including conventional and synchronized phasor measurements, Computers and Electrical Engineering, vol. 38, no. 2, pp. 294–305 (2012).
• [45] Vide P.S.C., Barbosa F.P.M., Ferreira I.M., Combined use of SCADA and PMU Measurements for Power System State Estimator Performance Enhancement, in Proc. of 2011 3rd International Youth Conference on Energetics (IYCE), Leiria, Portugal (2011).
• [46] Xia N., Gooi H.B., Chen S.X., Wang M.Q., Redundancy based PMU placement in state estimation, Sustainable Energy, Grids and Networks, vol. 2, pp. 23–31 (2015).
• [47] Komarnicki P., Golub I., Styczynski Z.A., Dzienis C., Blumschein J., PMU placement method based on decoupled newton power flow and sensitivity analysis, in 2007 9th International Conference on Electrical Power Quality and Utilisation (EPQU), Barcelona, Spain (2007).
• [48] Majidi M., Etezadi-Amoli M., Livani H., Fadali M.S., Distribution system state estimation using sparsified voltage profile, Electric Power Systems Research, vol. 136, pp. 69–78 (2016).
• [49] Evangelopoulos V.A., Georgilakis P.S., Hatziargyriou N.D., Optimal operation of smart distribution networks: A review of models, methods and future research, Electric Power Systems Research, vol. 140, pp. 95–106 (2016).

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).