An Analysis of Customer Power Profile Events for Non-invasive Energy Meter Error Monitoring

In this paper, a statistical analysis of low voltage customers' load power profiles is carried out aiming to suggest a remote non-invasive energy meter error monitoring technique. The synthesized open access 1 s resolution load power profiles are used for the analysis. A detection procedure for power steps in a sampled load power profile is defined. Power steps are classified into overlapping and non-overlapping. It is shown that the probability distribution function of the differences of power step magnitudes acquired by a meter under test and a reference sum meter is sensitive to the errors of the meter despite the presence of overlapping power steps at other meters in the grid. A noninvasive error monitoring technique is found possible by acquiring, comparing and statistically processing simultaneous power steps at the energy meter under monitoring and reference sum meter.

[1]  Vytautas Daunoras,et al.  A Technique of Synchronization of Distributed Energy Measurement in Low Voltage Electrical Grid , 2018, 2018 IEEE 9th International Workshop on Applied Measurements for Power Systems (AMPS).

[2]  Ye Li,et al.  A Recursive Least Squares Method with Double-Parameter for Online Estimation of Electric Meter Errors , 2019 .

[3]  Noah Pflugradt,et al.  Synthesizing residential load profiles using behavior simulation , 2017 .

[4]  Orhan Kaplan,et al.  The Determination of Load Profiles and Power Consumptions of Home Appliances , 2018 .

[5]  A. Grandjean,et al.  A review and an analysis of the residential electric load curve models , 2012 .

[6]  Short-duration Electrical Power Fluctuations Suppression by Averaging in Low Voltage Distribution Grid , 2019, 2019 2nd International Colloquium on Smart Grid Metrology (SMAGRIMET).

[7]  Davide Della Giustina,et al.  Distributed monitoring system for voltage dip classification over distribution grid , 2016 .

[8]  Saifur Rahman,et al.  Load Profiles of Selected Major Household Appliances and Their Demand Response Opportunities , 2014, IEEE Transactions on Smart Grid.

[9]  Žilvinas Nakutis,et al.  An Analysis of the Systematic Error of a Remote Method for a Wattmeter Adjustment Gain Estimation in Smart Grids , 2018 .

[10]  Bruno Sandrić,et al.  Metrology and quality assurance in internet of things , 2018, 2018 First International Colloquium on Smart Grid Metrology (SmaGriMet).

[11]  Davide Della Giustina,et al.  Time synchronization over heterogeneous network for smart grid application: Design and characterization of a real case , 2016, Ad Hoc Networks.

[12]  Nick Eyre,et al.  The diversity of residential electricity demand – A comparative analysis of metered and simulated data , 2017 .