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Classification of measurement-based approaches to load model identification

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
PL
Klasyfikacja urządzeń pomiarowych z uwzględnieniem identyfikacji obciążenia
Języki publikacji
EN
Abstrakty
EN
The paper briefly describes existing methods for processing measuring data of voltage, active and reactive power with a view to identify the mathematical model of substation load for calculating steady-state power system conditions. The authors proposed a classification of methods, described its key features and made a bibliographic list of works for each group.
PL
W artykule przedstawiono przegląd metod przetwarzania danych pomiarowych pomiaru napięcia, mocy czynnej i biernej z uwzględnieniem matematycznego modelu obciążenia podstacji w systemie energetycznym. Autorzy proponują klasyfikację i przedstawiają bibliografię dla każdej z grup.
Rocznik
Strony
64--68
Opis fizyczny
Bibliogr., 54., tab.
Twórcy
  • Automated Power Systems Department of Ural Federal University, Russia
  • System Operator of the United Power System, Russia
  • HP Inc, USA
Bibliografia
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  • [2] Cirgré Working Group C4.605: Modelling and Aggregation of Loads in Flexible Power Networks, IEEE Transactions on Power Systems, Feb. 2004.
  • [3] D. Han, J. Ma, R. He, Z. Dong: A Real Application of Measurement-Based Load Modeling in Large-Scale Power Grids and its Validation, IEEE Transactions on Power Systems, vol. 24, no. 4, pp. 1756-1764, Nov. 2009.
  • [4] U. Orji et al.: Load Modeling For Power System Requirement and Capability Assessment, IEEE Transactions on Power Systems, vol. 30, no. 3, pp. 1415-1423, May 2015.
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  • [6] Bibliography on load models for power flow and dynamic performance simulation, IEEE Transactions on Power Systems, vol. 10, no. 1, pp. 523-538, Feb. 1995.
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  • [22] Barzegkar-Ntovom G.A., Ceylan O., Papadopoulos T.A., Fatih Yetkin E.: Generic dynamic load modelling using cluster analisis, 2018 53rd International Universities Power Engineering Conference (UPEC), Glasgow, 2018, pp. 1-6.
  • [23] Kontis E.O., Papadopoulos T.A., Chrysochos A.I., Papagiannis G.K.: Measurement-Based Dynamic Load Modeling Using the Vector Fitting Technique, IEEE Transactions on Power Systems, vol. 33, no. 1, pp. 338-351, Jan. 2018.
  • [24] Kontis E.O. et al.: Development of measurement-based load models for the dynamic simulation of distribution grids, 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Torino, 2017, pp. 1-6.
  • [25] Yamashita K., Asada M., Yoshimura K.: A development of dynamic load model parameter derivation method, 2009 IEEE Power & Energy Society General Meeting, Calgary, AB, 2009, pp. 1-8.
  • [26] Ma Jin, He Renmu, Hill D.J. : Composite load modeling via measurement approach, 2006 IEEE Power Engineering Society General Meeting, Montreal, Que., 2006, pp. 1 pp.-.
  • [27] Kim Jae-Kyeong et al.: Fast and Reliable Estimation of Composite Load Model Parameters Using Analytical Similarity of Parameter Sensitivity, 2016 IEEE Power and Energy Society General Meeting (PESGM), Boston, MA, 2016, pp. 1-1.
  • [28] Mansour Eshragh-Niay Jahromi, Mohammad Taghi Ameli: Measurement-based modelling of composite load using genetic algorithm, Electric Power Systems Research, vol. 158, pp. 82-91, May 2018.
  • [29] V. Vignesh, S. Chakrabarti and S. C. Srivastava: Power system load modelling under large and small disturbances using phasor measurement units data, ET Generation, Transmission & Distribution, vol. 9, no. 12, pp. 1316-1323, 4 9 2015.
  • [30] Li Y., Chiang H.-., Choi B.-., Chen Y.-., Huang D.-., Lauby M.G.: Representative static load models for transient stability analysis: development and examination, IET Generation, Transmission & Distribution,vol. 1, no. 3, pp. 422-431, May 2007.
  • [31] Zhang R., Xu Y., Dong Z.Y., Wong K.P.: Measurementbased dynamic load modelling using time-domain simulation and parallel-evolutionary search, IET Generation, Transmission & Distribution, vol. 10, no. 15, pp. 3893-3900, 17 11 2016.
  • [32] Choi Byoung-Kon et al.,: Measurement-Based Dynamic Load Models: Derivation, Comparison, and Validation, IEEE Transactions on Power Systems, vol. 21, no. 3, pp. 1276-1283, Aug. 2006.
  • [33] Pandey T.S., Srivastava A.K., Markham P., Patel M.: Online Estimation of Steady-State Load Models Considering Data Anomalies, IEEE Transactions on Industry Applications, vol. 54, no. 1, pp. 712-721, Jan.-Feb. 2018.
  • [34] Pandey T.S., Srivastava A.K., Markham P., Bhatt N., Patel M.: Data-driven parameter estimation of steady-state load models, 2016 IEEE International Conference on Power Electronics, Trivandrum, 2016, pp. 1-5.
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  • [37] Kontis E.O., Papadopoulos T.A., Syed M.H., Guillo-Sansano E., Burt G.M., Papagiannis G.K.: Artificial-Intelligence Method for the Derivation of Generic Aggregated Dynamic Equivalent Models, IEEE Transactions on Power Systems, vol. 34, no. 4, pp. 2947-2956, July 2019.
  • [38] Zhu Y., Milanovic, J.V.: Automatic Identification of Power System Load Models Based on Field Measurements, IEEE Transactions on Power Systems, vol. 33, no. 3, pp. 3162-3171, May 2018.
  • [39] Fu C. et al.: Bayesian Estimation on Load Model Coefficients of ZIP and Induction Motor Model, 2019 IEEE Power & Energy Society General Meeting (PESGM), Atlanta, GA, USA, 2019, pp. 1-5.
  • [40] Metallinos K.S., Papadopoulos T.A., Charalambous C.A.: Derivation and evaluation of generic measurement-based dynamic load models, Electric Power Systems Research, vol. 140, pp. 193-200, Nov 2016.
  • [41] Papadopoulos T.A., Barzegkar-Ntovom G.A., Nikolaidis V.C., Papadopoulos P.N., Burt G.M.: Online parameter identification and generic modeling derivation of a dynamic load model in distribution grids, 2017 IEEE Manchester PowerTech, Manchester, 2017, pp. 1-6.
  • [42] del Pilar Rios A., Agbossou K., Cardenas A.: Taylor series approximation of ZIP model for on-line estimation of residential loads’ parameters, 2017 IEEE International Conference on Industrial Technology (ICIT), Toronto, ON, 2017, pp. 632-637.
  • [43] Yu S., Zhang S., Zhang X.: A two-step method for online parameter identification of a simplified composite load model, 2016 IEEE Innovative Smart Grid Technologies - Asia (ISGTAsia), Melbourne, VIC, 2016, pp. 1025-1030.
  • [44] Byoung-Kon C., Hsiao Dong C., Yinhong L., Yung Tien C., Der Hua H., Mark G.L.: Development of Composite Load Models of Power Systems using On-line Measurement Data, Journal of Electrical Engineering and Technology, vol. 1, pp. 161-169, Jun 2006.
  • [45] Rouhani A., Abur A.: Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model, IEEE Transactions on Smart Grid,vol. 7, no. 3, pp. 1530-1536, May 2016.
  • [46] Hasan K.N., Milanovic J.V., Turner P., Turnham V.: A stepby- step data processing guideline for load model development based on field measurements, 2015 IEEE Eindhoven PowerTech, Eindhoven, 2015, pp. 1-6.
  • [47] Wang Z., Wang J.: Time-Varying Stochastic Assessment of Conservation Voltage Reduction Based on Load Modeling, IEEE Transactions on Power Systems, vol. 29, no. 5, pp. 2321- 2328, Sept. 2014.
  • [48] Soo-Hyoung L., Seo-Eun S., Sung-Moo L, Jong-Man C., Kyung-Bin S., Jung-Wook P.: Kalman-Filter Based Static Load Modeling of Real Power System Using K-EMS Data, Journal of Electrical Engineering and Technology, vol. 7, no. 3, pp. 304-311, May 2012.
  • [49] Baone C.A., Veda S., Pan Y., Premerlani W., Dai J., Johnson A.: Measurement based static load model identification, 2015 IEEE Power & Energy Society General Meeting, Denver, CO, 2015, pp. 1-5.
  • [50] Tang X., Hasan K.N., Milanovic J.V., Bailey K., Stott S.J.: Estimation and Validation of Characteristic Load Profile Through Smart Grid Trials in a Medium Voltage Distribution Network, IEEE Transactions on Power Systems, vol. 33, no. 2, pp. 1848- 1859, March 2018.
  • [51] Marchgraber J., Xypolytou E., Lupandina I., Gawlik W., Stifter M.: Measurement-based determination of static load models in a low voltage grid, 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Ljubljana, 2016, pp. 1-6.
  • [52] Zhang X., Grijalva S., Reno M.J.: A time-variant load model based on smart meter data mining, 2014 IEEE PES General Meeting, National Harbor, MD, 2014, pp. 1-5.
  • [53] Kazaki A.G., Papadopoulos T.A.: Cluster analysis of university campus smart meter data, 2018 53rd International Universities Power Engineering Conference (UPEC), Glasgow, 2018, pp. 1-6.
  • [54] Tavlintsev A.S., Suvorov A.A., Gusev S.A., Staymova E.D., Zicmane I., Berzina K.: Search for the single-type load schedules of the power facility, 2018 IEEE 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), Riga, Latvia, 2018, pp. 1-5.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-48b72e0d-f900-4da7-a1ce-66c76b237679
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