An Analysis of the Systematic Error of a Remote Method for a Wattmeter Adjustment Gain Estimation in Smart Grids

Robertas Lukočius, Žilvinas Nakutis, Vytautas Daunoras, Ramūnas Deltuva, Pranas Kuzas and Roma Račkienė
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Robertas Lukočius: Department of Electrical Power Systems, Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Studentų str. 48, Kaunas LT-51367, Lithuania
Žilvinas Nakutis: Department of Electronics Engineering, Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Studentų str. 50, Kaunas LT-51368, Lithuania
Vytautas Daunoras: Department of Electronics Engineering, Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Studentų str. 50, Kaunas LT-51368, Lithuania
Ramūnas Deltuva: Department of Electrical Power Systems, Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Studentų str. 48, Kaunas LT-51367, Lithuania
Pranas Kuzas: Department of Electronics Engineering, Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Studentų str. 50, Kaunas LT-51368, Lithuania
Roma Račkienė: Department of Electrical Power Systems, Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Studentų str. 48, Kaunas LT-51367, Lithuania

Energies, 2018, vol. 12, issue 1, 1-26

Abstract: Smart energy meters supporting bidirectional data communication enable novel remote error monitoring applications. This research targets characterization of the systematic worst-case error of the previously published remote watthour meter’s gain estimation method based on the comparison of synchronous measurements by the reference and meter under test. To achieve the research aim a methodology based on global maximization of the systematic error objective function assuming the typical low voltage electrical distribution network operation parameters ranges as defined by the standard recommendations for network design. To cross verify the reliability of the assessed solutions the suggested error analysis methodology was implemented utilizing two stochastic global extremum search techniques (genetic algorithms, pattern search) and the third one utilizing nonlinear programming solver. It was determined that the wattmeter adjustment gain worst-case error does not exceed 0.5% if the remote wattmeter monitored load power factor is larger than 0.1 and a network is designed according to the recommendation of the acceptable voltage drop less than 5%. For a load exhibiting power factor larger than cos φ = 0.9 the worst-case error was found to be less than 0.1%. It is concluded therefore that considering the systematic worst-case error the previously suggested remote wattmeter adjustment gain estimation method is suitable for remote error monitoring of Class 2 and Class 1 wattmeters.

Keywords: watthour meter; gain adjustment; systematic error; genetic algorithms; pattern search; FMINCON; constrained optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
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