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. 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 auto-calibration of the voltage sensor and showed that it can also be used to calibrate the current sensor as well.

(a)

(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

This work is partially supported by Utah’s USTAR Program

978-1-4577-1767-3/12/$26.00 ©2012 IEEE

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.

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.

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 100-200 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

and sensor (Fig.1) is estimated by: 0rACd

ε ε= , in which rε is

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).

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

can be related to the line current: r

RNiI r

20

1

2 22 ωμμ=

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 10 20 30 40-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

V 3(v

)

Time(μs)

19.34 Vp 117.5 Vp 196.12 Vp

(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

(μrN) is given by: ld

NdL4018

22

+=

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 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.

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.

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 analog-to-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.

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09-200

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0

50

100

150

200

I 2(V)

Time(s)

No Input 39.87 Vp 79.89 Vp 117.5 Vp 155.40 Vp 196.12 Vp

(b)

0 20 40 60 80 1000.10

0.15

0.20

0.25

0.30

0.35

I1

Calculation from I2

Out

put(

A)

Input(V)

(a)

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.

Fig.6: Diagram of wireless version of the power sensing module for smart phone or smart grid.

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.

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