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

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.

A Contemplation on Electricity Meters In-Service Surveillance Assisted by Remote Error Monitoring

“…Electrical power losses depend on the power delivered to the consumer and characteristics of connecting lines. Distribution grid lines connecting a consumer and his/her meter are fixed and the range of systematic error [s min , s max ] due to power losses usually can be estimated in advance considering parameters of lines [19]. For a particular meter the REM systematic error s E is constant but it is only known that it is within the range [s min , s max ].…”

Online Monitoring Method of Medium Voltage Energy Meter Based on Load Characteristic

“…The electric energy metering device can realize the collection, measurement, storage, and transmission of electric energy, and is closely related to the settlement of users' electricity bills and power market transactions. However, due to the influence of non-standard working conditions such as on-site harmonics, the electric energy meter will produce certain measurement errors [1][2] . The power grid company mainly controls the misalignment of energy meters through offline methods such as periodic rotation and field tests.…”

A Newly Designed Method for On-Line Error Estimation of Smart Meter

“…But, it requires a large number of statistical samples. Ukočius et al [5] adopted the global maximization of the system error objective function to estimate the meter's error. Two random global extremum search techniques (genetic algorithm & pattern search) and nonlinear programming solver were used to further validate the reliability of the evaluated solution.…”