A Method of Determining an Electric Energy Meter Maximum Uncertainty
This paper proposes the adoption of the estimator of the standard deviation as a quality measurement of the test. The uncertainty type A can anticipate and adopt its value a priori. Imposition of any noise during the test should be within the revalue valu
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bstract. This paper proposes the adoption of the estimator of the standard deviation as a quality measurement of the test. The uncertainty type A can anticipate and adopt its value a priori. Imposition of any noise during the test should be within the revalue value of smax. Knowing the characteristics of smax as a function of time, it is possible to determine the minimum duration of the test while maintaining the required uncertainty. Keywords: energy meter testing, accuracy of energy meter, repeatability of measurements, standard deviation, measurement uncertainty.
1
Introduction
For many years, there has been, in principle, the compatibility of views on this, in which measuring points (also called points of a load meter) energy meters, both inductive and electronic (static) [1], should be checked. The standards and regulations [2-4] specified the tables describing the maximum permissible errors counters for individual measurement points during type approval and verification of the meter. It is very important to provide the required reproducibility of the test during testing both using energy meter test system [5], as well as portable testers [6]. The best indicator of the repeatability is uncertainty. An exemplary scheme of the testing system is shown in Figure 1.
Fig. 1. An exemplary scheme of the testing system James J. (Jong Hyuk) Park et al. (eds.), Multimedia and Ubiquitous Engineering, Lecture Notes in Electrical Engineering 308, DOI: 10.1007/978-3-642-54900-7_57, © Springer-Verlag Berlin Heidelberg 2014
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P. Mróz, A. Olencki, and A. Bukowiec
Typically it consists of: • the controller of the system, • a source of the reference signals, • the tested energy meter (DTU). The controller of the system is a PC computer with dedicated software. It could be also implemented as dedicated hardware controller [7-9]. There can be considered several models for control algorithm, like finite state machines [10, 11], Petri nets [12, 13], or UML state machines [14, 15]. The source of the reference signals is a three phase power calibrator. There is used Calmet C300 three and single phase power and energy calibrator [16] in our testing system. the tested energy meter (DTU) is a device under test. Conducted researches have been worked out with use of LUMEL EM03 energy meter [17].
2
Determination of Uncertainty
The expanded percentage uncertainty U for a directly measured error of the energy meter (DUT), when the uncertainties of type A and type B are taken into consideration, results from:
U = k ⋅ uC ,
(1)
where k is the coverage factor and uC is the combined standard uncertainty:
uC = k ⋅ u A2 + u B2 ,
(2)
The standard uncertainty of type A – uA is calculated from the observed scatter of the DUT's errors in the measurements series for each test point and may be expressed as the estimation of standard deviation:
uA = s =
(
)
2 1 n Ei − E n − 1 i =1 ,
(3)
where n is a number of measurements for each test point, Ei is the error percentage [3] in relation to the measurement value for the ith measur
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