Non-Intrusive Electric Power
Sensors for Smart Grid
Pradeep Pai, Lingyao Chen, Faisal Khair Chowdhury, and Massood Tabib-Azar
Electrical and Computer Engineering
University of Utah
Salt Lake City, USA
azar.m@utah.edu
Abstract— An electric power sensor that measures near-field
voltage and current waveforms through the insulation layer on a
power cord is presented. To measure the line current, we
examined Hall, giant magneto-resistive (GMR) and inductive
sensors and found that for sensing 60 Hz current through its
magnetic field, the inductive probe resulted in the best
performance. To measure the voltage waveform, we developed a
near-field electric dipole antenna that consisted of two strips of
copper approximately 3 mm long. The voltage and current
sensors were then calibrated and uncertainties due to the
placement of the sensors over power cords were determined. A
method was developed to enable the power sensor to perform
auto calibration to estimate miss-alignments between the sensors
and the wires in the cord. Power measurement accuracy of
better than 5% was achieved.
I.
(a)
INTRODUCTION
There is a need for non-intrusive power sensors that can be
simply placed over a power cord to monitor power
consumption of appliances at home or power tools in a
factory. These power sensors can be equipped with wireless
telemetry and on-board power excavenging devices to report
power consumptions to handheld devices such as smart
phones or to central control units to monitor their efficiency
and modify their operation schedule to minimize operation
cost. It will be very desirable to wirelessly monitor power
consumptions of different devices and appliances in a
household using a smart phone without tapping into their
power cords.
In this paper, we discuss a relatively simple approach
(Fig.1) to measure power through the insulation of power
cords with high accuracy, good performance, fast response (in
µs) and good sensitivity (minimum detectable signals of 1 V
and ~ 0.1 A). To estimate power, voltage and current
waveforms are needed. In our work, we measured the voltage
waveform, using capacitive sensors and we measured the
current waveform using the magnetic field that is generated
near the cord. We also developed a technique for autocalibration of the voltage sensor and showed that it can also be
used to calibrate the current sensor as well.
This work is partially supported by Utah’s USTAR Program
978-1-4577-1767-3/12/$26.00 ©2012 IEEE
(b)
Fig. 1:
Placements of voltage and current sensors on the intact power
cord. Separate directly wired sensors were used to measure line voltages and
current for calibration. Additionally, a 100-300 kHz signal source was used to
induce AC signal in the line for auto calibration of the voltage sensor.
Conventional electric power sensing is usually performed
by electrodynamometers or digital power meters with direct
connection to the power line. In recent years, two methods are
frequently used in remote power sensing devices, optical
electric power sensing (OEPS) and thermal effect power
sensing (TEPS). OEPS uses sensing elements such as
crystalline quartz, bismuth germanium oxide [1], bismuth
silicate, Zinc Selenide, Zinc Telluride, bismuth germinate, etc.
These crystals exhibit both Faraday and Pockels effects.
However, large background optical activity has always been
problematic with crystalline quartz, Bi12GeO20 and Bi12SiO20
[2]. ZnSe and ZnTe are good sensing elements without this
shortcoming, but low resistivity has limited their application.
Bi4Ge3O12 has high performance on direct optical
measurements of electric-power, but the measurement
uncertainties come from other resources such as dimensions,
and uncertainties in material parameters. TEPS is based on
integrated temperature sensor and requires thermal isolation
and has longer time constant than optical techniques [3].
Other techniques incorporating MEMS also are reported
[4-5]. Such technology is generally based on capacitive and
magnetic field variation detection. Examples are cantilevers
coupled to permanent magnet setup [1], MEMS scale
inductive coils on flexible PET [5] etc, which have resulted in
sensitivities of 74mV/A and 31.1µV/A, respectively. Recent
attempts at detecting extremely small magnetic fields
(nanoTesla - picoTesla regime) primarily for medical purposes
using magnetostrictive MEMS-FET [6] and ferro-fluidic [7]
technology have also been presented and are indicative of the
increased effectiveness these can have for comparatively
larger magnetic fields involved in the applications targeted by
our sensor.
II.
SENSING METHODS
To non-intrusively sense power, two independent sensors
to respectively sense the voltage and current waveforms are
needed. We intentionally refer to signal “waveforms” because
the phase angle between current and voltage is important and
can only be measured using simultaneous detection of the
voltage and current waveforms. Capacitive and inductive
loads produce non-zero phase angle ( ) between current and
voltage signals and lead to IVcos( ) power. Fig. 1(a)
schematically shows the structure of our power sensor that is
composed of a voltage sensor and a current sensor. In-line
wired sensors are also shown that were used for calibration.
Additionally, we also developed a method to inject 100-300
kHz signal into the power lines and subsequently detect them
for auto calibration of the voltage sensor. Fig. 1(b) shows a
possible application of our power sensor in its wireless version
to provide information for the smart grid and smart phones.
To enable non-intrusive voltage calibration (i.e., to
eliminate the need to measure V1), we capacitively injected a
100-300 kHz signal into the power cord and detected it using
the same capacitive sensors that we used to sense the 60 Hz
line voltage. The detected voltage waveform is shown in Fig.
3. Fig. 3(b) shows the capacitances that exist between the
external 100-300 kHz source and the capacitive sensor. The
external source is simply coupled to the cord using small
lengths of wires adjacent to the insulation of the cord. When
the capacitive voltage sensors are separated from the surface
of the power cord because of miss-alignment, the overall 100200 kHz detected signal reduces. The assumption here is that
miss-alignment affects the calibration signal the same way that
it affects the 60 Hz line voltage. Using the calibration signal
we can estimate the coupling capacitances that are then used
to estimate the calibrated value of the sensed 60 Hz signal.
The results of voltage sensing are shown in Figs. 2-3. The
output signal is shown in Fig. 2(a). After we perform the
calibration of V2×(n), the results fit V1 provided that we use n
= 112. The error between the calibration results and V1 is
around 4%. High frequency AC signal detection is also done
using dipole sensors (Fig.1). The capacitance between the wire
A
and sensor (Fig.1) is estimated by: C = ε r ε 0 , in which ε r is
d
approximately 2 (the relative permittivity of the cord
insulation, ε0 is the vacuum permittivity and A is the sensor
area 2.5mm×12mm, d is the distance between the sensor and
the wire (~3mm). The capacitance is approximately 177fF
according to the above calculations. The equivalent circuit of
the system is shown in Fig.3(b).
In the measurements reported below, we used an
incandescent light as the load and varied the power using a
transformer from 0 to 110 V. All the measurements were
repeated 10 times to ensure reproducibility.
A. Voltage Sensing Using Capacitive Coupling
To sense and measure the line voltage, we used two
metallic strips as capacitive sensors that were simply placed
over the insulation of the power cord. The capacitive sensors
pick up the voltage signal in the power cord through
Q(t)=CV(t) where the voltage V(t) is produced by the cord and
C is the capacitance between the metallic strips and the power
cord. The resulting charge Q(t) was then amplified and a
voltage proportional to Q(t) was recorded as shown in the
oscilloscope trace in Fig. 2(a).
The capacitor voltage that was proportional to the
amplified Q(t) varied from 40 to 196 mV as shown in Fig.
2(a). As can be seen in Fig. 2(b), the calibration can be
accomplished using a simple constant scale factor in this case.
The calibration scale factor is determined by the sensor
structure (area, distance to the metallic core, the cord insulator
and its permittivity) and the gain of the amplifier. The sensed
voltage (V2) and directly measured voltage (V1) are shown in
Fig. 2.
Fig. 2: Results of voltage sensing and calibration. a) Output signal of V2, and
b) result of calibration.
B. Current Sensing Using Inductive Coupling
The line current was sensed using its magnetic field.
Typical value of current from household appliances is around
0.1-10A resulting in small magnetic fields. In order to sense
this alternating magnetic field, a solenoid with large turns and
a ferromagnetic core was selected as the sensor. We also
examined Hall and Giant Magneto Resistive sensors that
worked well at high end of the current range but had difficulty
sensing the low end values. An induced electromotive force
(EMF) is generated on the current/magnetic field sensor that
2
can be related to the line current: I 2 = 2 2 N μ r μ 0 ω R
i1
r
where N is the number of turns of the solenoid, μrµ0 is the
permeability of the ferromagnetic core, ω is the angular
frequency of the AC source, R is the radius of the solenoid and
r is the distance between the wire and the surface of the
solenoid.
0.8
19.34 Vp
117.5 Vp
196.12 Vp
0.6
V3 (v)
0.4
0.0
-0.2
0
10
20
Time(μs)
30
III.
EXPERIMENTAL SETUP AND RESULTS
The main experiment setup is shown in Fig.1(a). A
solenoid and two pairs of copper dipoles are surface mounted
on an insulating platform. One pair of dipole is connected
with high frequency AC generator and the other pair provides
the output of V2 and V3 through amplifier 1. The black (red)
wire is Live (Neutral) wire. When AC signal passes through
the circuit of the light bulb, alternating magnetic field is
generated and penetrates the side face of the solenoid. Fig.1(a)
displays one situation when the direction of the magnetic field
points into the paper. Amplifier 2 is connected with solenoid
outputs I2, which can give a description of the current in the
circuit. We measure the electric power consumption under
different loads which ranges from 10V-100V, and the
corresponding results of V1, V2, V3, I1, I2 are tested and
compared.
We used a solenoid for current sensing. The results of
current sensing are shown in Fig.4. Fig.4 (a) shows an
obvious shift between zero input voltage and when the load is
on. I2 with the unit of V is measured and inserted into equation
(1), so that i1 can be determined and compared with I1 which
comes from ammeter (Fig.4(b)). The error between I1 and i1 is
also around 2%-4%, which is indicative of a reliable current
sensor.
0.2
-0.4
The ratio of I2 and i1 is calculated to be 0.00321 according
to equation (1) and above parameters. Consequently, we can
compare i1 with the straightforward measurement I1 through
an ammeter.
40
(a)
Fig.3: a) Results of high frequency AC signal detection. b) Equivalent circuit
of High frequency AC signal. The coupling capacitances (Ccoupling) are
between the power cord and the external calibration source and the sensing
amplifier.
An empirical formula which gives relation between
inductance of the solenoid and the effective number of turns
d 2N 2
(μrN)
is
given
by:
L=
18 d + 40 l
where d is diameter of the coil, l is the coil length, L is the
inductance in µH. Our solenoid is 11 mH with ferromagnetic
core, and has an effective number of turns of 2000. So the
constants used in equation (1)-(2) are: N~2000, µ0~4π ×10-7
N/A, ω~2 π×60 rad/s, R~2.1 mm, and r~1.3 mm.
The current sensing does not depend on the angle between
the wire and the solenoid, as shown in Fig.5(a)-(b). As a
result, it is fairly easy to align the wires on a household
appliance with the sensor. To make the voltage sensor work
reliably, the wires should be parallel with the sensing copper
dipoles, which may not always present an easily applicable
case. In an attempt to account for this variation, we tested the
voltage at different angles (Fig.5(a)-(b)). Two observations
from the results are important here: (1) positive angle and
negative angles with same magnitude have the same results.
The angle of our measurement here goes from 0° to 40°. The
aim of each calibration is to make the error retain between
2%-4%.
Fig. 6 shows the diagram of a wireless power sensing
module based on the power sensors. Analog voltage and
current signals will be converted to digital signals by analogto-digital converters (ADC) and all power related data will be
transmitted to smart phone or smart grid with the Bluetooth
module RN-41, with control by on-board microcontroller.
IV.
CONCLUSION
In this paper, we propose a new design for a power sensor
which we senses the current and voltage separately. We use a
pair of copper dipoles to sense the voltage and a solenoid to
sense the current. We also used an ammeter and voltmeter to
measure the exact values of the current and voltage, then
compared them with results of the sensor. The error between
two sets of results is between 2%-4%, which indicates that our
sensor works reliably. With that we can conclude that our
sensor can sense the current and voltage without any intimate
measurement of either, with good sensitivity and high
performance.
200
(a)
150
100
I2(V)
50
No Input
39.87 Vp
0
-50
Fig.6: Diagram of wireless version of the power sensing module for smart
phone or smart grid.
79.89 Vp
117.5 Vp
-100
155.40 Vp
-150
196.12 Vp
-200
0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09
ACKNOWLEDGMENT
Technical assistance provided in measuring electrical
power and assembling sensors by Mr. Yuchen Yang is
appreciated. This work was partially supported by the USTAR
Program at the University of Utah.
Time(s)
REFERENCES
[1]
0.35
(b)
Output(A)
0.30
0.25
0.20
I1
Calculation from I2
0.15
0.10
0
20
40
60
80
100
Input(V)
Fig.4:(a) Output signal of I2. The shift is very obvious. b) I1 compared with i1
which is calculated through equation (1).
Fig.5: Application (a),(b): positive and negative angles during measurement.
C. Li, X. Cui, T. T. Yoshino, “Optical electric-power sensor using one
Bi4Ge3O12 crystal”, Proceedings of the SPIE - The International Society
for Optical Engineering, Vol. 4920, pp 415-421, 2002.
[2] E. S. Leland, et al., “A MEMS AC current sensor for residential and
commercial
electricity
end-use
monitoring”,
Journal
of
Micromechanics and Microengineering, Vol. 19, pp. 094018, 2009.
[3] Y. C. Chen, et al., “A flexible, non-intrusive power sensor tag for the
electricity monitoring of two-wire household appliances”, IEEE
MEMS, pp. 620-623, 2012.
[4] F. Li, et al., “Magnetoelectric Resonant Gate Transistor”, Solid State
Sensors, Actuators and Microsystems Workshop, Hilton Head Island,
2012.
[5] G. Hatipoglu and S. Tadigadapa, “A Novel Magnetometer Employing
Magnetoviscous Effect Of Ferrofluids”, Solid State Sensors, Actuators
and Microsystems Workshop, Hilton Head Island, 2012.
[6] K. Wong, “Power sensor calibration and uncertainties”, 60th ARFTG
Conference Digest. Fall 2002. Automatic RF Techniques Group.
Measurements Needs for Emerging Technologies (Cat. No.02EX739),
pp. 167-178, 2002.
[7] T. Lalinsky, S. Hascik, Z. Mozolova, E. Burian and M. Drzik, “The
Improved Performance Of GaAs Micromachined Power Sensor
Microsystem”, Sensors and Actuators A, Vol. 76, pp. 241–246, 1999.
[8] S. H. Lightbody, M. E. Teachman, C. N. Gunn and B. T. Huber, “Nonintrusive Power Monitor”, U. S. Patent 7265533.
[9] D. Lin, C. Afei, S. Wenxia, W. Youyuan and L. Guojun, “A Noncontact Over-voltage Sensor for Overhead Power Transmission Lines”,
Automation of Electric Power Systems, Vol. 34, pp. 93-97, 2010.
[10] M. Stamate, “Non-Intrusive Measurement Of The Active Power In
Induction Heating Systems Through The Proximate Magnetic Field”,
IEEE Sensors Applications Symposium, pp. 1-6, 2012.
[11] M. Zeifman and K. Roth, “Nonintrusive Appliance Load Monitoring:
Review and Outlook”, IEEE Transactions on Consumer Electronics,
Vol. 57, p. 76-84, 2011.
[12] H. Chang, K. Chen, Y Tsai and W. Lee, “A New Measurement Method
for Power Signatures of Nonintrusive Demand Monitoring and Load
Identification”, IEEE Transactions on Industry Applications, Vol. 48,
pp. 764-770, 2012.