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 [email protected]

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 (a) 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 (b) consumption of appliances at home or power tools in a factory. These power sensors can be equipped with wireless Fig. 1: Placements of voltage and current sensors on the intact power telemetry and on-board power excavenging devices to report cord. Separate directly wired sensors were used to measure line voltages and power consumptions to handheld devices such as smart current for calibration. Additionally, a 100-300 kHz signal source was used to phones or to central control units to monitor their efficiency induce AC signal in the line for auto calibration of the voltage sensor. and modify their operation schedule to minimize operation Conventional electric power sensing is usually performed cost. It will be very desirable to wirelessly monitor power by electrodynamometers or digital power meters with direct consumptions of different devices and appliances in a connection to the power line. In recent years, two methods are household using a smart phone without tapping into their frequently used in remote power sensing devices, optical power cords. electric power sensing (OEPS) and thermal effect power In this paper, we discuss a relatively simple approach sensing (TEPS). OEPS uses sensing elements such as (Fig.1) to measure power through the insulation of power crystalline quartz, bismuth germanium oxide [1], bismuth cords with high accuracy, good performance, fast response (in silicate, Zinc Selenide, Zinc Telluride, bismuth germinate, etc. µs) and good sensitivity (minimum detectable signals of 1 V These crystals exhibit both Faraday and Pockels effects. and ~ 0.1 A). To estimate power, voltage and current However, large background optical activity has always been waveforms are needed. In our work, we measured the voltage problematic with crystalline quartz, Bi12GeO20 and Bi12SiO20 waveform, using capacitive sensors and we measured the [2]. ZnSe and ZnTe are good sensing elements without this current waveform using the magnetic field that is generated shortcoming, but low resistivity has limited their application. near the cord. We also developed a technique for auto- Bi4Ge3O12 has high performance on direct optical calibration of the voltage sensor and showed that it can also be measurements of electric-power, but the measurement used to calibrate the current sensor as well. 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 To enable non-intrusive voltage calibration (i.e., to and has longer time constant than optical techniques [3]. eliminate the need to measure V1), we capacitively injected a 100-300 kHz signal into the power cord and detected it using Other techniques incorporating MEMS also are reported the same capacitive sensors that we used to sense the 60 Hz [4-5]. Such technology is generally based on capacitive and line voltage. The detected voltage waveform is shown in Fig. magnetic field variation detection. Examples are cantilevers 3. Fig. 3(b) shows the capacitances that exist between the coupled to permanent magnet setup [1], MEMS scale external 100-300 kHz source and the capacitive sensor. The inductive coils on flexible PET [5] etc, which have resulted in external source is simply coupled to the cord using small sensitivities of 74mV/A and 31.1µV/A, respectively. Recent lengths of wires adjacent to the insulation of the cord. When attempts at detecting extremely small magnetic fields the capacitive voltage sensors are separated from the surface (nanoTesla - picoTesla regime) primarily for medical purposes of the power cord because of miss-alignment, the overall 100- using magnetostrictive MEMS-FET [6] and ferro-fluidic [7] 200 kHz detected signal reduces. The assumption here is that technology have also been presented and are indicative of the miss-alignment affects the calibration signal the same way that increased effectiveness these can have for comparatively it affects the 60 Hz line voltage. Using the calibration signal larger magnetic fields involved in the applications targeted by we can estimate the coupling capacitances that are then used our sensor. to estimate the calibrated value of the sensed 60 Hz signal. II. SENSING METHODS The results of voltage sensing are shown in Figs. 2-3. The To non-intrusively sense power, two independent sensors output signal is shown in Fig. 2(a). After we perform the × to respectively sense the voltage and current waveforms are calibration of V2 (n), the results fit V1 provided that we use n needed. We intentionally refer to signal “waveforms” because = 112. The error between the calibration results and V1 is the phase angle between current and voltage is important and around 4%. High frequency AC signal detection is also done can only be measured using simultaneous detection of the using dipole sensors (Fig.1). The capacitance between the wire voltage and current waveforms. Capacitive and inductive A and sensor (Fig.1) is estimated by: C = εε , in which ε is loads produce non-zero phase angle ( ) between current and r 0 d r voltage signals and lead to IVcos( ) power. Fig. 1(a) approximately 2 (the relative permittivity of the cord schematically shows the structure of our power sensor that is insulation, ε0 is the vacuum permittivity and A is the sensor composed of a voltage sensor and a current sensor. In-line area 2.5mm×12mm, d is the distance between the sensor and wired sensors are also shown that were used for calibration. the wire (~3mm). The capacitance is approximately 177fF Additionally, we also developed a method to inject 100-300 according to the above calculations. The equivalent circuit of kHz signal into the power lines and subsequently detect them the system is shown in Fig.3(b). 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. 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 ratio of I2 and i1 is calculated to be 0.00321 according The line current was sensed using its magnetic field. to equation (1) and above parameters. Consequently, we can Typical value of current from household appliances is around compare i1 with the straightforward measurement I1 through 0.1-10A resulting in small magnetic fields. In order to sense an ammeter. this alternating magnetic field, a solenoid with large turns and a ferromagnetic core was selected as the sensor. We also III. EXPERIMENTAL SETUP AND RESULTS examined Hall and Giant Magneto Resistive sensors that The main experiment setup is shown in Fig.1(a). A worked well at high end of the current range but had difficulty solenoid and two pairs of copper dipoles are surface mounted sensing the low end values. An induced electromotive force on an insulating platform. One pair of dipole is connected (EMF) is generated on the current/magnetic field sensor that with high frequency AC generator and the other pair provides I 22 ωμμ RN 2 the output of V2 and V3 through amplifier 1. The black (red) can be related to the line current: 2 = r 0 wire is Live (Neutral) wire. When AC signal passes through i r 1 the circuit of the light bulb, alternating magnetic field is μ where N is the number of turns of the solenoid, rµ0 is the generated and penetrates the side face of the solenoid. Fig.1(a) permeability of the ferromagnetic core, ω is the angular displays one situation when the direction of the magnetic field frequency of the AC source, R is the radius of the solenoid and points into the paper. Amplifier 2 is connected with solenoid r is the distance between the wire and the surface of the outputs I2, which can give a description of the current in the solenoid. 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 0.8 19.34 Vp compared. 0.6 117.5 Vp We used a solenoid for current sensing. The results of 196.12 Vp current sensing are shown in Fig.4. Fig.4 (a) shows an 0.4 obvious shift between zero input voltage and when the load is on. I2 with the unit of V is measured and inserted into equation

(v) 0.2

3 (1), so that i1 can be determined and compared with I1 which V 0.0 comes from ammeter (Fig.4(b)). The error between I1 and i1 is also around 2%-4%, which is indicative of a reliable current -0.2 sensor.

-0.4 The current sensing does not depend on the angle between 0 10203040 the wire and the solenoid, as shown in Fig.5(a)-(b). As a Time(μs) (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 Fig.3: a) Results of high frequency AC signal detection. b) Equivalent circuit current signals will be converted to digital signals by analog- of High frequency AC signal. The coupling capacitances (Ccoupling) are to-digital converters (ADC) and all power related data will be between the power cord and the external calibration source and the sensing transmitted to smart phone or smart grid with the Bluetooth amplifier. An empirical formula which gives relation between module RN-41, with control by on-board microcontroller. inductance of the solenoid and the effective number of turns 22 IV. CONCLUSION μ Nd ( rN) is given by: L = + In this paper, we propose a new design for a power sensor 4018 ld which we senses the current and voltage separately. We use a where d is diameter of the coil, l is the coil length, L is the pair of copper dipoles to sense the voltage and a solenoid to inductance in µH. Our solenoid is 11 mH with ferromagnetic sense the current. We also used an ammeter and voltmeter to core, and has an effective number of turns of 2000. So the -7 measure the exact values of the current and voltage, then constants used in equation (1)-(2) are: N~2000, µ0~4π ×10 ω × compared them with results of the sensor. The error between N/A, ~2 π 60 rad/s, R~2.1 mm, and r~1.3 mm. 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.

200 150 (a) 100 50 No Input Fig.6: Diagram of wireless version of the power sensing module for smart

(V) 0

2 phone or smart grid. I 39.87 Vp -50 79.89 Vp ACKNOWLEDGMENT -100 117.5 Vp 155.40 V Technical assistance provided in measuring electrical p power and assembling sensors by Mr. Yuchen Yang is -150 196.12 V p appreciated. This work was partially supported by the USTAR -200 Program at the University of Utah. 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 Time(s) REFERENCES [1] C. Li, X. Cui, T. T. Yoshino, “Optical electric-power sensor using one 0.35 Bi4Ge3O12 crystal”, Proceedings of the SPIE - The International Society (b) for Optical Engineering, Vol. 4920, pp 415-421, 2002. 0.30 [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. 0.25 [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. 0.20 Output(A) I [4] F. Li, et al., “Magnetoelectric Resonant Gate Transistor”, Solid State 1 Sensors, Actuators and Microsystems Workshop, Hilton Head Island, Calculation from I 2012. 0.15 2 [5] G. Hatipoglu and S. Tadigadapa, “A Novel Magnetometer Employing Magnetoviscous Effect Of Ferrofluids”, Solid State Sensors, Actuators 0.10 and Microsystems Workshop, Hilton Head Island, 2012. 0 20406080100 [6] K. Wong, “Power sensor calibration and uncertainties”, 60th ARFTG Conference Digest. Fall 2002. Automatic RF Techniques Group. Input(V) Measurements Needs for Emerging Technologies (Cat. No.02EX739), pp. 167-178, 2002. Fig.4:(a) Output signal of I . The shift is very obvious. b) I compared with i 2 1 1 [7] T. Lalinsky, S. Hascik, Z. Mozolova, E. Burian and M. Drzik, “The which is calculated through equation (1 ). 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, “Non- intrusive Power Monitor”, U. S. Patent 7265533. [9] D. Lin, C. Afei, S. Wenxia, W. Youyuan and L. Guojun, “A Non- contact 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.

Fig.5: Application (a),(b): positive and negative angles during measurement.