1
Electric Energy Metering developments at the
smart grid: technology, accuracy,
standardization, and verification
N. Calamaro, V. Elkonin, Y. Beck and D. Shmilovitz
Abstract— The technology of electric energy digital meters has
significantly evolved during the last two decades. At parallel,
smart grid technology has set new technological environments and
challenges to the digital energy metering: renewable energy plants
with their converters, insert distortion reactive energy to the
active energy measurement, and challenge reactive energy
accurate measurement. This paper shows that some meters are
not sensitive to harmonics at reactive power measurement, and
some are sensitive to linear reactive loads (i.e. capacitors,
inductors) but not to non-linear reactive loads. Accurate and
correct energy measurement is a key factor at the smart grid: at
the billing management procedure, and at energy management.
They are the back-bone of the grid industry. This review paper
demonstrate how several branches of science and technology,
coincide and work in coordination (i) the regulator rules have
relatively not modified significantly over the years. Much wider
technology must oblige today to the regulator's rules. (ii) The
smart grid technology has reopened scientific areas of research
due to new problems: electric energy transport theory. New areas
require updating the standardization: power quality and PV
converters, new metering technologies such as information
security, and data concentrators performing processing on energy
quantities. (iii) The meter digital technology which encounters the
new grid technology problems. (iv)The standards are progressing
fast alongside the technological innovations. This paper attempts
to present a new point of view, one that makes sense, and
awareness of the presented issues including measurement, theory
and standards issues. Many issues differentiating between digital
meters two decades ago and smart meter are allocated by this
research group from field test findings. This paper outlines them.
Index Terms—AMI – Advanced Metering Infrastructure, A/D –
Analog to Digital, PV – Photovoltaic, THD – Total Harmonic
Distortion.
I.
T
INTRODUCTION
THE great interest in Smart Grid in the last few years has
opened new research areas and renewed interest in the
This research was supported in part by the ISG (Israeli Smart Grid)
Consortium, administrated by the Office of the Chief Scientist of Israeli
ministry of industry and Trade and Labour.
Manuscript received October 10, 2013.
N. Calamaro is with the Israeli Electric Company, Israel (e-mail: netzah@
iec.ac.il) and with School of Electrical Engineering, Tel-Aviv University.
PhD. Vladimir Elkonin is Metering National Division chief metrology
officer (email: vladimiral@iec.co.il).
Y. Beck is with the Electrical Engineering Faculty, Holon Institute of
Technolgy, Holon, Israel, (phone: +972-3-502-6837; fax: +972-3-502-6837;
e-mail: beck@hit.ac.il).
D. Shmilovitz is with the Physical Electronics Department, Faculty of
engineering, Tel Aviv University, Tel Aviv, Israel, (e-mail:
shmilo@eng.tau.ac.il).
fields of power systems and energy transport theories. One
major concern in advanced metering systems is the verification
that the measured energy is accurate and correct. Correct at the
measurement point – the meter display, and at two additional
points: (a) direct meter reading, where communication to meter
is direct using a cable. While location is at measurement point
energy quantities are processed by a software module. (b)
Remote meter reading far away from them meter. Electricity
regulating authorities in the world are supervising the
electricity companies. These authorities usually define simple
single major regulation which requires correctness of the
consumption report. This regulation has remained relatively
unchanged during the years. The digital metering technology
and working environment of the meters, on the other hand has
evolved and generates problems requiring attention and
solutions.
This work group has worked at two directions: the electric
company personal worked on methodology, standardization.
The Tel-Aviv university school of electrical engineering, and
power systems division at faculty of electrical engineering at
HIT, worked on scientific formulas and relevant standards
allocation. The issues reflecting smart grid technology and
directly affecting energy digital meters are listed herein: (i)
growth of number of involved metering components- Two
decades ago meter reading personal were manually reading the
energy registers of a few energy measured quantities. These
registers are displayed at the digital meter display. Then
consumption reports, load profile, and electricity event logs
were directly read from the meter as textual reports. Now-days
this information is being read remotely and processed by
Advanced Metering Infrastructure (AMI) software. The energy
quantities reported at this endpoint must be accurate and
correct. (ii) Growth of measured and computed energy
parameters. The number of energy quantities, has enlarged
from 4 {active, reactive} X {import, export} measured
quantities, to about 120 computed energy quantities, as defined
in standard IEC 62056‎[1]. Reasons for that growth are
explained later on. The growth is mainly, but not only, due to
new tariff computations. (iii) Longer time periods for
accumulation of energy measurements- Early Standards, such
as IEC 62052-11‎[2], IEC 62053-{21-23}‎[3],‎[4]‎[5] require
instantaneous energy accuracy. Current meters provide the
energy consumption trend, named load profile. The load profile
figure must be accurate for periods as large as 4 months, in
quanta of 5-15 minutes periods. (iv) The effect of renewable
energy plants power quality, on meters accuracy- It has been
2
found that there is measurements inaccuracy caused by
cascaded contribution of: (a) converters producing more
reactive power than allowed by the power quality standards.
That happens to specific PV converters of many model types.
Statistically: about one 6th of converters per problematic PV
converter model type. (b) Energy meters have approximate
energy formulas, which are not consistent in the presence of
harmonics. This issue is handled, by existing standards, which
are not commonly enforced as for today ‎[6], ‎[7]. (v) Effect of
reactive energy tariff policy. The idea of reactive tariff is to
charge different tariff on reactive power, rather than just
penalize on low power factor. For energy measurement usually
periodic averaged theories‎[8]-[13] are implemented and not
instantaneous theories. Focusing on periodic averaged theories,
there are two major groups of energy transport
formulas/theories: frequency domain ‎[9] and time
domain ‎[8].in this paper it is presented that a common time
domain reactive energy formula, is only approximate.
Inaccuracy is invoked at a multi-harmonic high THD
environment. For 99.9% of customers the accuracy is
sufficient, within meter spec. For 0.1% of operation
environments, inaccuracy requires tagging the meters
according to precision of formula. (vi) Sensitivity of reactive
energy measurement expressed only by power factor multiplier
meaning capacitive and inductive loads. Many digital meters
are
sensitive
to
reactive
energy
generated
by
capacitive/inductive loads, but not on harmonics related
distortion power. That is not necessarily a problem, but policy
must be agreed. (vii) Wider energy measurement range/scale
for renewable energy measurement. The exported energy is
measured at much wider energy scale than the imported
energy. That is not a trivial technological issue for
implementation at a single digital meter: (viii) Inaccuracy
inserted due to measurement transformer distortion. (ix)
Inaccuracy inserted at power quality measurement capability
of the meter. (x) Inaccuracy caused by insufficient meter
sampling rate. (xi) Inaccuracy insert through multipliers:
configurable and non-configurable: Tariff multipliers,
conversion from energy to pulses and other multipliers.
These above mentioned points of inaccuracies require potential
update of power quality, metering and of PV standards. It's a
cyclic effect: the inaccuracy should affect standards upgrade,
and after issues of inaccuracy are handled the new metering
technology, they serve the grid at new ways.
Two decades ago the translation of the regulator's theme:
maintaining accurate consumption reports would include only a
single technical term. That term is measurement accuracy. The
accuracy verification methodology, included a single lab
professionalization in meterlogy and certification of the meter
type, according to standards IEC 62052-11, IEC62053-{21, 22,
23}. Now days, two additional terms are required due to the
new issues presented above: (1) energy correctness, (2) and
multi-layered verification scheme of energy measurement
accuracy and correctness. Simple make-sense definitions of
these two new terms are required and provided in this paper.
For addressing these issues relatively newer standards are
being referred to for extending our knowledge: (i) EN 50470-
{1, 3} ‎[14]‎[15] – a standard system recommended by IEC
smart grid standardization road map.
(ii) IEC62056 ‎[1],
known also as DLMS\COSEM. From that standard, energy
computed quantities, correctness may be derived as it specifies
meter design spec. (iii) IEEE 1459, DIN 40110 – which define
legitimate standard formulas for active and reactive power and
energy metering. This paper initially presents how the puzzle
of: regulator, technology, standardization, testing – is
constructed. Then we specify with sufficient detail the issues
raised above and their matching standards and technological
solutions.
II.
FROM A REGULATOR'S RULE TO SCIENTIFIC
DEFINITIONS
Step #1: The regulator single major rule is maintaining correct
and accurate consumption report. In order to transform the
problem to a scientific and standardization issue we define a
minimal set of equivalent definitions. The significance of
minimization is that it is easier to get consensus on a minimal
set of definitions. First of all it is accepted that the regulator's
rule has remained fixed at past and present. What has enlarged
is the amount of technology modules covered by that rule. Fig.
1 demonstrates that theme and specifies that initially there was
only the digital meter, and gradually additional technologies
were added. In the past the only technology was the meter. At
present addition of direct meter reading software,
communication media, including potential information security
modules, and finally remote meter reading and processing
software are introduced.
Fig. 1: enlargement of scope to be enforced by regulator's rule.
Step #2: three definitions are set that together form the rule of
correct/accurate consumption report, meaning the definitions
are equivalent to the rule. The three definitions are shown at
Fig. 2. Their essence in short: if all energy measured quantities
are kept accurate, and all energy computed quantities based on
the measurements are maintained correct, then the
consumption report shall be accurate and correct.
Measurement, correctness of computations and accuracy of
measurements, are scientific definitions. The third used
definition is, multi-layered verification scheme. It doesn't
appear on the same space as accuracy and correctness. Without
verification of the accurate and correct, it is still one step
missing from the consumption report rule. This definition is a
practical method of maintaining variables accuracy and
correctness as will be presented ahead. Practically, a single
3
layer verification scheme cannot be maintained at the smart
grid.
Step #3: The method of verifying that metering system is in
accordance with the definitions is by using standards, and the
work of allocation of specific standards is a non-negligible
task. The standards are shown in Fig. 2 from the definitions to
applying them on the meter for verification. Standards have
several advantages as basis for verification. Naming a few
advantages: (i) It is a design specification, the regulated spec,
independent of specific meter type. (ii) Standards are usually
straightforward to follow. (iii) They're a good defense line
against claims of inaccurate tariff metering against utility
companies.
Fig. 2: translation of the regulator single major rule through a minimal set of
three variable definitions, and standards to a meter acceptable testing scheme.
This section has demonstrated how a practical problem is
turned into something that may be verified over the meter. It is
not an arbitrary choice. It's really minimal and the defined
items are orthogonal and create a scientific/technological
ground.
III.
EFFECT OF SMART GRID ON METERING EQUIPMENT
DIMENTIONSIONALITY AND ENERGY CORRECTNESS
A. General
After discussing what is required in order for a meter to
generate correct reports, we next specify effects of the smart
grid on dimensions growth of properties of the metering
equipment. Dimension growth means more complexity and
additional issues to handle. This section describes dimensions
related to accuracy and correctness.
Fig. 3: enlargement of energy variable space: a digital meter a decade ago and
at present. Past: 4 energy variables were read from display. Present: a
consumption report consisting of 120 tariff computed energy computed
quantities. Red = high tariff, yellow – medium tariff, green – low tariff.
The 120 energy computed quantities arrive from the following
sources: (i) tariff computed, (ii) multipliers for load profile
(trend) – from pulse count to energy, (iii) calibration
multipliers – accessible and not accessible for meter software
configuration. (Fig. 4 displays a typical consumption report
presented at graphically enlightening format). It splits the entire
group of energy quantities into sub groups: (1) the gray left
group includes the 4 basic measured quantities. These
quantities existed two decades ago in digital meters. (2) The
red group implies high tariff, the yellow implies medium tariff,
and the green implies low tariff. (3) There are 3 computable
quantities per each tariff: rate register for that tariff, maximum
demand and cumulative maximum demand (as referred to in
IEC 62056). (iv) There are groups of quantities named selfreads. These quantities are a snapshot of the same groups of
quantities from current meter reading displayed in Fig. 4. They
are presented as non-displayed folders in Fig. 4. The snapshots
are taken at the 1st of each month. Each self-read duplicates the
count of energy quantities. At the consumption report of Fig. 4,
there are: a current reading and 4 self-reads. (v) Finally for the
bellow example there are energy active-import readings per
power phase.
B. Dimension #1: growth of number of energy standard
quantities
Two decades ago there were four basic measured quantities by
the meter: {active energy, reactive energy} X {import, export}.
There are about 120 energy quantities constructed by
mathematical manipulation of the basic measured energy
quantities. The number of quantities varies from one meter
model to another. It is sufficient that one meter has a duality:
{import, export} to double the number of variables. What is
important is the definition and specifications of the computed
variables and that it's standardized according to IEC 62056.
The number of quantities at his standard is roughly a 120.
Taking more differentiating attributes specified by IEC 62056,
and the count is duplicated. So it is observed that the number of
energy quantities grown drastically and the dimension of
energy quantities, has enlarged due to smart grid technology
Fig. 4: a consumption report split into sub-groups of common attribute. The
sub group titles are provided.
C. Dimension
#2:
growth
software/hardware components
of
number
of
4
Two decades ago there was a digital display as presented at
Fig. 5 at the inner-most circle. Then a direct meter reading
through a laptop of Hand Held Unit was added (shown in the
2nd inner circle in Fig. 5). Then remote metering software was
added (external circle). The external layer actually consists of
additional layers: potential information security layer,
communication modules, and data concentrators. The
technology as observed has enlarged, and it all has to abide to
the regulator rule.
Fig. 5: enlargement of metering modules space: Past: digital display. Present:
addition of direct meter reading and remote meter reading and processing.
The enlargement of technology, demonstrates that much more
meter verification is required, and not only accuracy. This
reinforces justification of usages of multi-layered verification
scheme.
D. Dimension #3: growth of energy accumulation time.
Past verification of measured energy quantities required
instantaneous values in time frames such as about 1min per
test. In Fig. 6 a presentation of consumption report and load
profile. Energy accuracy and correctness is measured at large
integration period: (i) through self-reads. 4 self reads, means 4
months backwards. (ii) Through load-profile. Energy should
be reported accurately during long integration periods. Each
integration period is of 5min-30min, and accumulatively load
profile may last backwards for several months.
Fig. 6: enlargement of energy integration period: Past: instantaneous. Present:
consumption report dating 4 months backward, and 4 months load profile
report.
E. Standardization response To dimensionality
IEC 62056 (DLMS/COSEM) is a standard which addresses all
dimensionality issues of through: (i) energy quantities
enlargement, (ii) software modules enlargement, (iii)
integration time period enlargement, there is a clear standard:.
This standard clearly specifies three issues. The Issues are: (i)
upper layer communication protocol, supporting all lower level
standard protocols. (ii) Uniform design specification of a
digital revenue meter architecture and functionality. (iii)
Testability of functionality. The latter term is specified at
standard by two methods: testability as implied from the meter
design specification defined by the standard. This means that
testability tests all specify functionality. For example: the
standard defines maximum demand, then this maximum
demand correct functionality tests are invented. The 2 nd method
is a true testability standard. Recently DLMS/COSEM
organization the one in charge of maintenance of IEC 62056(,
published a standard document named CTT – Compliance Test
Tool. This document includes for the first time testability of
meter functionality. It does not exactly overlap the tests
implied by design spec, but it is close enough. Up to recently,
accredited labs and major customers of meters, satisfied with
inaccuracy/ meterologoy standards. It is evident herein that the
weight of energy quantities correctness, in a similar form to
inaccuracy, is at least equal to or more important to energy
quantities inaccuracy. Correctness is the majority of
consumption report and of load profile.
IV.
PHYSICAL INACCURACY EFFECTS GENERATED BY
SMART GRID
A. Distortion power accounted as active power
Next a series of two physical potential inaccuracy phenomena
inserted due to the combination of renewable energy plants and
an approximate energy formula are described. They were
measured by the Israeli Electric Company Metering
Development Lab, but there are also other references ‎[8].
The first problem arises since active energy formulas are
approximate, and combined with the effect that harmonics are
insert by renewable energy plants.
Problem description: Two PV identical converters located at
the same sight. Each has two meters of different type. An
energy gap was measured between the meters. Statistics in
Israel is approximately one every 6 converters, and it is specific
converters and not a specific converter type. Meaning a
specific type is ok for 5/6 of times, and one every 6 converters
of that type are not ok. The Israeli Electric Company Metering
Development Lab has conducted a research, on energy
difference between various meters and the origin and reasons
for this difference. This research is beyond scope of this paper,
and is briefly described next:
(1) Fig. 7 displays a measurement of a PV converter
generating 4% energy difference between various meters.
Measurement was performed with SATEC EM720 meter
and power quality monitor.
5
dips than non-problematic point. That indicates that converter
with energy difference is much noisier.
The absolute accurate formulas are presented at (1) ‎[8], and
IEEE1459, DIN 40110 for the frequency domain section of (1):
T
N
0
n 1
P   v(t )i(t )dt  Vn I n cos(n )
(a)
Voltage spectrum
(1)
(b) Current spectrum
Fig. 7: Recording of a PV DC→AC converter. A zoom-in of harmonics is
generated for convenience. Additional harmonics at current spectrum, testify
on harmonics generated by the converter. That's a harmonic generated load
(HGL).
(2) Simple experiments using pairs of meters models evident
that problem is located at meter and not at some voltage
drop along electric path:
(a) Test #1: allocate 2 different meter models to 2 PV
converters at same point, from same model. An energy
difference is obtained. Replace then to 2 meters of
identical model. Energy difference is eliminated.
Conclusion: had problem been outside meter as
energy drop along hidden path between 2 converters,
meter equalization wouldn't have eliminated the
difference. Result of test #1 indicates a problem also
internal to meter.
(b) Test #2: referring to problem description, the problem
is also related to specific PV converter. That
hypothesis is confirmed with results of Fig. 7 and
additional results to be explained herein.
(c) Test #3: Replacing meters of same type at all the
locations where phenomena exists and eliminated with
identical meter doesn't stop eliminating problem. That
indicates that there is no some distribution among
same model type, affecting the energy difference.
(3) Collecting recorded power quality data on two identical
converters, one with an energy difference, and another
without, is displayed at Fig. 8.
Where:
are Fourier coefficients of voltage and current
waveforms accordingly, and  n is relative phase between
harmonic voltage and current waveforms at the nth harmonic.
IEEE 1459 and DIN 40110 should be roughly considered as
very similar. For comparative discussion we refer to‎[8]. Both
formulas presented at (1) are periodic averaged: one is time
domain and the other is frequency domain.
We provide two technological examples common to meters
without spectral computations that are approximate:
P  VRMS I RMS
(2)
The other approximate formula for active energy is:
T
P  V1 I1 cos(1 )   v1 (t )i1 (t )dt
(3)
0
Where
v1 (t ), i1 (t ) are prime harmonic, voltage and current
waveforms accordingly. Formula (2) is an absolute formula for
apparent power. The approximation there is that reactive
distortion power from voltage-current cross-product harmonics
is considered as active. Eq. (2) is producing higher energy then.
Problem is demonstrated graphically at Fig. 9:
(a)
Fig. 8: above – a converter without energy difference between meter different
models, bellow – a converter with energy difference. Notice different scale.
Measurement with SATEC EM720 meter+ Power quality monitor
Problematic PV converter point is with more frequency
variation, rapid voltage changes, voltage unbalance, voltage
(b)
Fig. 9: (a) distortion power is generated spuriously in time at PV converter. (b)
While measured by various meters, distortion power is mistakenly considered
as active power at meter X, and something in between for meter Y.
6
N

Q   Vn I n sin(n ) 
n 1


T
Q   v(t )i (t  T )dt 
4 
0

Fig. 10 simplifies power diagram ignoring non distortion
reactive power:
S
D
P
Fig. 10: apparent (S), active (P) and distortion reactive (D) powers vector
diagram. The navy blue represent wrong power measured somewhere between
S and P.
Problem is common to meter with a Hall element current
measurement probe ‎[16], or formula (2) is used for keeping
computation simple. For a pure sine formula is accurate. What
is sometimes named instantaneous at literature is RMS. A Hall
element is shown at Fig. 11:
While the upper formula in (4) is accurate in the absolute
sense, the lower formula is only an approximation, in the case
of low THD scenario. This fact is known in ‎[8], but mentioned
only briefly. For exact reactive power measurement the
following formula applies:
Formula (3) is an approximation taking into account only the
primary harmonic. Formula (3) provides a lower bound of
actual active energy, since it does not consider higher order
harmonics of the active energy. There are additional works ‎[8]
with similar conclusion of meter inaccuracy. There other
causes are mentioned. An additional reference on meter
differences at energy measurement under harmonics is ‎[17]. A
legitimate question might rise: there is an entire standard IEC
62053-22 handling active energy. So if that problem really
existed, it would have been detected, often. The testing by
standard IEC 62053-22, the majority of tests are operated using
only single harmonic stimuli, and no formula is provided. The
tests focus is accuracy with a variable:
. Meaning active
energy accuracy is for linear loads, with capacitive or inductive
elements.
T
N
Q   n0T  vn (t )in (t 
n 1
Where
Fig. 11: Hall element measurement probe, measuring signal RMS
(4)
0
T
)dt
4n
(5)
vn (t ), in (t ) are nth order harmonic, voltage and current
waveforms accordingly. An elaborate mathematical-physical
proof that (5) is correct, is beyond the scope of the current
paper, and requires knowledge of electric power transport
theories‎[8]. However, a very intuitive explanation of (5)
correctness is provided next:
(i)
Reactive energy is independent or orthogonal to active
energy. That constrain lies at the heart of (4):
P  QTotal
or
S 2  P 2  QTotal 2 , where
(ii)
(iii)
S  VRMS I RMS
(6)
Two formulas of (6) can be shown mathematically to
be equivalent to (4) and to orthogonality in power
space.
In harmonics space, orthogonality of active and
reactive power means that each power has different
harmonics.
Orthogonality of P, Q means for the prime harmonic a
90◦ phase shift between voltage and current
waveforms, but for higher order harmonics that
doesn't mean: ⁄ . Higher order harmonics reproduce
90◦ at ⁄
. Fig. 12 demonstrates the issue.
B. Inaccurate reactive power computation
Reactive energy inaccuracy is more common to current meters
then supposed initially. Roughly it exists in many class1, 2
accuracy meters, and it doesn't exist in class0.5 meters, with
exceptions. It comes due to the fact that energy meters are
designed to be sensitive to reactive energy resulting from
capacitive and inductive linear loads, but not from harmonics.
Sensitivity to harmonics is obtained using a Fourier Transform.
That functionality exists usually at more expensive meters.
There are two reactive energy formulas: frequency domain and
time domain as follows:
Fig. 12: location of 90◦ phase shift at various harmonic orders. Harmonic
orders are top to bottom: 1st, 3rd, 5th, 7th,9th. Bottom yellow waveform is sum
of harmonics. Figure generated by PSL harmonics simulator.
7
(iv)
If (iii) is not a convincing intuition, then equivalence
to (4), the frequency domain formula, is obtained only
with (5). And (4) means (6) which is orthogonality.
Again, a relevant issue may be raised. If there is an entire
standard handling reactive energy accuracy, then usages of
inaccurate formula by meter types should have been detected.
Reactive standard IEC62053-23 again puts emphasis on tests
with pure sine waveforms and power factor variation. Namely,
reactive energy measurement with single harmonic and linear
loads: capacitive or inductive. More recent standards EN
50470-1, 3 introduce a more realistic electric environment.
These standards are enforced/ recommended by IEC smart grid
standardization roadmap. Standards IEEE 1459 and DIN 40110
are handling exactly the issues of inaccurate measurements.
Finally, parallel work to the one presented here were performed
by the National German institute for science and technology for
the field of metrology and physical safety engineering PTB,
and at academy‎[17] and there they arrive to same conclusions,
including relation to the above standards.
Fig. 14: soft magnet has a narrow hysteresis loop
The objective is to generate as much possible an identical loop
segment for positive waveform section as the negative. These
two solutions conclude the issue of inaccuracy caused by
transformers. There are other causes for transformer inaccuracy
such as saturation, beyond the scope of this paper.
D. Power quality monitoring inaccuracy issues
C. Inaccuracy
transformers
inserted
by
measurement
Measurement transformers introduce waveform distortion
through phase shift and amplitude, and harmonics insertion.
Usage of an 0.2% accurate meter with 1% inaccuracy of
transformer is useless. Advanced meters include transformer
compensation at least through amplitude and phase, for some
of the harmonics. Calibration of the metering system implies
compensation of the transformer at the meter configuration.
Some advanced meters, include smart transformers. They
include auto-calibration mechanism similar to the one defined
above. Metering system accuracy verification includes the
transformer, and a calibration procedure should be defined.
So the first solution to the distortion problem is compensation
and auto compensation is implemented at the smart
transformer. At that case the technology brings a solution,
enabling then accurate energy measurement and power quality
monitoring along the grid. The technology improves metering
and the improvement enables usage at the grid.
Fig. 13 displays a scheme of a measurement transformer and a
hysteresis loop. The transformer distorts the waveform by the
positive waveform being transferred different then the negative
waveform section.
(a)
(b)
Fig. 13: (a) a measurement transformer (b) hysteresis loop as cause of
waveform distortion.
Another solution to the problem of the transformer distorting
the waveforms is soft magnet as demonstrated at Fig 14.
High performance meters class0.2s include sometimes a power
quality module according to standard EN 50160‎[18]. There is a
very detailed and very important testability and architecture
design specification of that module. The standard is IEC
61000-4-30am2‎[19]. It is beyond the scope of this paper, and is
reminded here for knowledge. An excellent test document in
complete matching to the standard is "Power Standard
Laboratories (PSL)" certification test procedure. Test may be
directly extracted from IEC 61000-4-30am2. A power quality
module significantly enlarges the amount of accuracy issues.
E. Inaccuracy
insert
through
configurable and non-configurable
multipliers:
There are several sources of energy measurement multipliers:
(i) Current and voltage transformers ratios. (ii) Range selection
configured multipliers. For example: notifying that although
meter range is 5Ampere, need the A/D to be set at a scale of
1A. The range is then more accurate, but if current value
crosses 1A, there might be spurious errors. If by configuration
there erroneous definition, accuracy could be broken and
worse, it shall occur randomly. (iii) Multipliers of energyquanta to a single pulse. These multipliers exist at: (1) relays
output, (2) meter constant at red LED output, (3) load profile
report. Class0.2s meters are more sophisticated and
configurable. Methodology is then to maintain known list of all
multipliers, and configure them all, not relying on default
values. Inaccuracy of class1 meter at relay is usually much less
than the meter specified accuracy.
F. Inaccuracy due to insufficient sampling rate
Sampling rate of conventional class1,2 meters is 8-16
samples/cycle. According to Nyquist theorem only phenomena
8
bellow harmonic 2-4 are accurately visible. Inaccuracy is
shown at Fig. 13:
Fig. 13: effect of insufficient sampling rate with harmonics of higher order then
one. Integration is inaccurate.
Observing the inaccuracy phenomena at frequency domain the
low sampling rate acts as low pass filter: the waveform sum of
harmonics with order higher than 4 are lost. This subject is
addressed in many works and only mentioned here.
A. Inaccuracy
insert
through
configurable and non-configurable
D. Implication of meter inaccuracy findings on
multipliers:
There are several sources of energy measurement multipliers:
(i) Current and voltage transformers ratios. (ii) Range selection
configured multipliers. An example: notifying that although
meter range is 5Ampere, need the A/D to set scale to 1Ampere.
Range is then more accurate, but if current value crosses
1Ampere, there might be spurious errors. If by configuration
there erroneous definition, accuracy shall be broken and worse,
it shall occur randomly. (iii) Multipliers of energy-quanta to a
single pulse. These multipliers exist at: (1) relays output, (2)
meter constant at red LED output, (3) load profile report.
Class0.2s meters are more sophisticated and configurable.
Methodology is then to maintain known list of all multipliers,
and configure them all, not relying on default values.
Inaccuracy of class1 meter at relay is usually much less than
the meter specified accuracy. That is the LED count
inaccuracy.
B. Inaccuracy due to too wide energy scale
PV farms generate energy at a high scale: 1-100MWatt. They
consume energy at a much lower scale: 10kWatt. Conventional
meters although containing the ability to register separately
active import and export energies, lack the range for the above
ratio. A single A/D is linear at scale and not logarithmic and
most of accuracy shall be invested at manufactured energy and
not on consumed. Energy accuracy verification should consider
that. Class0.2s meters, that are more expensive, often has
starting current sensitive enough for the consumption scale, or
the meter manufacturer aware of scale issue measured lower
starting current then stated by spec. At that case a test report
must be provided by manufacturer, and range enhancement
should be used.
C. Implications of meter inaccuracy findings on PV
standards
This research group is not a standard committee and
conclusions are not fact and stated as opinion of research group
based on its findings. PV standards IEEE 519, IEC 61215, IEC
61646, IEC 61730-1, IEC 61730-2, define current THD should
be lower than 5%. Standards do not specify when, shall the
THD meet this value. From standard point of view it means
that it should be: always. Power Quality standards clarify that
answer cannot be: always, but instead a percentage of the total
observation period, where the threshold is not violated. PV
stray converters cannot be rejected on THD, since the violation
occurs spuriously and randomly in time. They can be
diagnosed however, violating power quality standard
EN50160. That standard can therefore be used for testing PV
new model type, over several samples.
power quality standardization
It is found that PV converters insert noise to the grid, and affect
meters accuracy. PV converters are characterized by 16 kHz
PWM frequency or another PWM frequency. This is a source
for noise due to harmonics. Power Quality standards define
regulation at range 0-2kHz. This paper results, suggest that it
may be a good idea to have a regulative look at spectral range
from 16 KHz up to 1 MHz, since a significant noise affecting
energy measurement is at that band.
V.
A MULTI-LAYERED VERIFICATION SCHEME
It is comprehended from the enlargement at so many branches
that verification of energy quantities accuracy is insufficient,
and additional verification niches are required. The last chapter
of this paper specifies what verification layers are required.
The list of required layers is: (i) meterology layers, (ii) correct
tariff functionality verification, (iii) field testing of both
accuracy correctness and electricity phenomena affecting the
energy accuracy. About ten issues where the grid affects the
meters were pointed out. Putting the three layers at more detail
the implementation measures in light of the ten grid issues are:
(i)
Purchase of relevant test equipment for the various
functionality layers. That means meterology test
equipment for the accuracy tests. Specific test
equipment for measurement according to IEC 62056
(DLMS/COSEM). Specific test equipment enabling
stimuli of electricity phenomena, as accurate as the
meterology verification but for tariff verification.
(ii)
Meter accuracy verification of energy measured
quantities. That layer has been there two decades ago.
Recently a new standard has entered the layer. EN
50470-{1, 3}. That standard is supported by IEC
smart grid standardization roadmap. Generally
speaking that standard overlaps existing IEC62052-11,
IEC62053-{21, 22, 23} standards. But the new
standard is more modern than IEC 6205X, and sets the
meter at a more realistic work environment: multiharmonic and other power quality effects. If the
9
(iii)
(iv)
(v)
previous standard tested that meter is accurate within
domestic consumer operating environment, then the
new standard tests the operation more within
industrial and renewable energy farm, operating
environment. Therefore it is important to adapt to that
standard, or at least insert some tests from it.
Functional tests of correctness of energy computed
quantities defined by IEC 62056. The weight of that
new verification scheme is considerable and increases
continuously. 120 quantities vs. 4 accuracy quantities.
There is no existing test equipment testing the entire
test envelope. There is test equipment for testing in
accordance with IEC 62056, and there is test
equipment capable of physically testing all functional
tests, but the automation software is not written yet.
Metering Development lab has developed a test book
including 600 tests for covering that verification
space. The verification items should be documented.
Recently a test standard in accordance with IEC 62056
was published by DLMS/COSEM org., and that is
half a step prior to full test standard by IEC. For the
first time in 22 years a standard covering meter design
specification was published. Another issue is that
accuracy verification items not covered by accuracy
testing and yet not covered by functional tests, and
still they are accuracy tests, is increasing
continuously. Examples of these new accuracy
verification items: (a) long time range metering
accuracy. A modern meter consists of a series of
multipliers from basic measured quantities registers up
to them being registered as load profile. It is required
to measure and test that albeit all the multipliers load
profile quantity is correct. Testing that is a unique
methodology developed
at
IECo
Metering
Development lab, with a lot of wisdom embedded into
it. (b) testing energy quantity correctness after being
processed by various parallel multipliers: for relay
pulses, optical pulses, for load profile, consumption
report.
Field testing. That verification layer is serving several
different objectives. Strong field testing similar to
accuracy meterology and functional verification, with
the aim of preventing meters removal from field and
testing at lab. The second objective is electricity
effects affecting meter accuracy, and in general
affecting their environment. Tagging meters according
to their identified energy computation formulas
according to IEEE 1459 and DIN 40110 is required. It
covers about 0.1% of meter population but it is at
rapid increase.
Quality assurance testing prior to meters arrival to
electric company for approval procedure, at
manufacturer site. In general that verification
discipline is not accuracy and correctness. But it does
contain accuracy and correctness, and these items are
in line with this paper subject.
(vi)
(vii)
(viii)
(ix)
Statistical testing of a very large sample of the meters
already installed at field. Identification of trend of
aging of meter model types and alert. Identification of
changes from first meters batch that is usually at good
shape and next batches were manufacturer might
change components providers. Relating to QA, there
are successful procedures for much earlier stage, for
detection of such issues.
Simulations related meter accuracy behavioral
modeling at various electricity environments. These
simulations provide accurate, fast and cheap answers
that are otherwise very expensive and difficult for
reproducing. After a required scenario has been
allocated using simulation, an actual test on real
meters is taken, but that is focused only on the last
step.
Power quality monitoring module accuracy
verification in accordance with IEC 61000-4-30am2.
The concept of VEE –Validation Estimation (meter)
Editing. Something similar to total quality
management. Implementation of all above verification
chapters.
All this is evidently not executable at a single layer. A multilayer verification scheme is required.
VI.
CONCLUSIONS
In this paper, a list focusing on smart grid effects on energy
measured quantities accuracy and energy computed quantities
correctness is presented. An attempt is made to put some order
at the interrelations between regulator's rules, mathematical
definitions, all problems caused by grid environment, all new
technology insert to meter, and standardization. Listing down
the issues has put structural order into this vast discipline. It
has also revealed a large list of inaccuracy and correctness
items insert by the grid, consisting of approximately ten issues.
Several physical phenomena were presented, with new
theoretical physical resolution. The number of inaccuracy
factors at energy measurement caused by the smart grid and
their scientific sophistication is surprising. A clear structure
transferring from regulator's rules to a scientific and technology
plane was set.
It is possible to discuss phenomena at a measurable way and
quantify it. The structure includes a minimal set of 3
definitions: accuracy, correctness and multi-layered
verification scheme. Upon that layer all the 10 listed
phenomena are discussed. Every new detected item is so far
describable by this minimal set. The collaboration of standards
and technology: both at meters and at the grid. Collaboration of
verification and the regulator's rules is demonstrated. That
collaboration is not trivial at all. On the contrary: the large
wealth of standards, technology, rules appears to move in
contradicting directions. This paper has put some order into
them, clarifying the major items there wise.
10
VII.
ACKNOWLEDGMENT
Thanks to Mr. Itzhak Mashiach, the manager of Metering
development lab, and a senior committee member of Israeli
Electric Company org. (IECo) smart grid pilot, and senior
standards institute committee member. Thanks to Mr. Emil
Koifman manager of National Meters division at IECo, and
head of IECo smart grid pilot committee, for enabling this
paper and non-classified knowledge release by this paper.
Thanks for enabling the invaluable anonymous measurement
data.
VIII.
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
REFERENCES:
IEC 62056 - standards for Electricity metering – Data exchange for meter
reading, tariff and load control.
IEC 62052-11: Electricity metering equipment (AC) - General
requirements, tests and test conditions - Part 11: Metering equipment.
IEC 62053-21: Electricity metering equipment (a.c.) – Particular
requirements –Part 21:Static meters for active energy (classes 1 and 2).
IEC 62053-22: Electricity metering equipment (a.c.) –. Particular
requirements –. Part 22: Static meters for active energy. (classes 0,2 S
and 0,5 S).
IEC 62053-23: Electricity metering equipment (a.c.) - Particular
requirements - Part 23: Static meters for reactive energy (classes 2 and 3).
IEEE Std. 1459–2010, “IEEE Trial-Use Standard Definitions for the
Measurement of Electric Power Quantities Under Sinusoidal,
Nonsinusoidal, Balanced or Unbalanced Conditions.”
DIN 40110–2:2002–11, Quantities Used in Alternating Current Theory–
Part 2: Multi-Line Circuits.
A.E. Emanuel, "Power Definitions and the Physical Mechanism of Power
Flow". John Wiley, IEEE press, 2010
L. S. Czarnecki, "Currents’ physical components (CPC) concept: A
fundamental of power theory," in Nonsinusoidal Currents and
Compensation, 2008. ISNCC 2008. International School on, 2008, pp. 111.
Budeanu C. I.: “Puissances R´eactives et Fictives,” Inst. National
Roumain pour l’ ´ Etude de l’Am´enagement et de l’Utilisation des
Sources d’ ´ Energie, Bucarest, 1927.
Buchholz F.: “Die Drehstrom-Sheinleistung bei Ungleichmassiger
Belastung Der Drei Zweige,” Licht und Kraft No. 2, Jan. 1922, pp. 9–11.
Fryze S.: “Effective, Wattless and Apparent Power in Circuits with
Nonsinusoidal Waveforms of Current and Voltage,” Elektrotechnishe
Zeitschrift,” No. 25, June 23, 1932, pp. 596–99, 625–27, 700–702.
Depenbrock M.: “The FBD-Method, a Generally Applicable Tool for
Analysing Power Relations,” IEEE Transactions on Power Systems, Vol.
8, No. 2, 1993, pp. 381–86.
EN50470-1: Electricity metering equipment (a.c.) - Part 1: General
requirements, tests and test conditions - Metering equipment (class
indexes A, B and C)
EN50470-3: Electricity metering equipment (a.c.) - Part 3: Particular
requirements - Static meters for active energy (class indexes A, B and C)
A.J. Wilks,"Hall effect based electrical energy metering device with
fraud detection and instantaneous voltage, current and power outputs",
Metering Apparatus and Tariffs for Electricity Supply, 1990., Sixth
International Conference on.
A.A Hossam-Eldin, R.M. Hasan , "Study of the effect of harmonics on
measurments of the energy meters", Power Systems Conference, 2006.
MEPCON 2006. Eleventh International Middle East (Volume:2 ).
EN50160: Voltage Characteristics in Public Distribution Systems.
IEC 61000-4-30am2: Electromagnetic compatibility (EMC) – Part 430:Testing and measurement techniques – Power quality measurement
methods.
IX.
BIOGRAPHIES:
Netzah Calamaro was born in Tel Aviv, Israel on 8 th June 1967.
He received his B.Sc.in Electrical and Electronic Engineering from
the Technion Israel Institute of Technology at 1990. He received
his M.Sc. in Electrical Engineering at 1998 from the Technion.
During 1989-1995 he served as an officer at Israeli Air-Force
as a deputy-commander of a: "missile maintenance lab". During 1995-2005 he
worked at Intel RnD at chip design. During 2005-2008 he worked as at Elspec's
RnD department –developing energy meters, Power Quality monitoring
equipment, Real-Time Power Factor correction, and SCADA systems. Starting
2005 until today, Netzah works at the Metering Development Laboratory –
National Metering Unit, Israel Electric Company – as a systems engineer and
deputy chief metrology officer. Netzah performs research at the School of
Electrical Engineering, Tel-Aviv University. His research interests are control
algorithms for active filters and grid diagnostics. He is a member of smart
meters standard committee at Israel Standard Institute. He is involved at
several research activities at IECo.
Vladimir Elkonin was born at Soviet Union at 1946. He studied
up to PhD Electrical Engineering specializing at meterology:
accurate measurement. He arrived to Israel Electric Company org
(IECo) at 1991. He is known for establishing the role and
significance of chief meterology officer at National Meters
division IECo. Among his notable actions is an official appearance of meters
accuracy at Israeli Parliament committee and convincing them – a notable
ocasion were science convinced regulation. As a result PhD Elkonin translated
the regulator's rules, to scientific and standard form specifications. He
documented the procedures as active/reactive accuracy and correctness
verification protocols. PhD Elkonin assimilated the knowledge downwards at
M. PhD Elkonin is in charge of definition of accuracy segment at all tenders,
and at smart grid activity related to meterology. PhD Elkonin is also
responsible for Quality Assurance, and visits to manufacturer factory, and any
regulative issue.
Yuval Beck was born in Tel Aviv, Israel, on November 30,
1969. He received the B.Sc degree in electronics and electrical
engineering from Tel Aviv University in 1996, the M.Sc.
degree in 2001, and the Ph.D. degree on the subject of ground
currents due to lightning strokes in 2007 both from Tel Aviv
University as well. Since 1998, he has been with the
Interdisciplinary Department, the Faculty of Engineering, Tel Aviv University.
In 2008 joined HIT-Holon Institute of Technology, Holon, Israel, as a Lecturer
and from 2010 is acting as the head of Energy and Power Systems department
at the faculty of engineering. His research interests include Smart Grid
technologies, lightning discharge phenomena; lightning protection systems;
power electronics, and photovoltaic systems.
Doron Shmilovitz (M’98) was born in Romania in 1963. He
received his B.Sc., M.Sc., and Ph.D. from Tel-Aviv University,
Tel-Aviv, Israel, in 1986, 1993, and 1997, respectively, all in
electrical engineering. During 1986–1990, he worked in R&D for
the IAF where he developed programmable electronic loads.
During 1997–1999, he was a Post-Doctorate Fellow at New York Polytechnic
University, Brooklyn. Since 2000, he has been with the Faculty of Engineering,
Tel-Aviv University, where he has established a state-of-the-art power
electronics and power quality research laboratory. His research interests
include switched-mode converters, topology, dynamics and control, power
quality, and special applications of power electronics such as for alternative
energy sources and powering of sensor networks and implanted medical
devices, and general circuit theory.