Mobile electric field sensor based phasor measurement unit for monitoring an electric power grid

A system may include an electric field sensor, an analog to digital converter, and an estimator. The electric field sensor may measure electric fields of electric power grid. The analog to digital converter may generate digital output based upon measurements from the electric field sensor. The estimator may estimate phasor data of the electric power grid based upon the digital output.

BACKGROUND

Wide-area measurement systems (WAMS) have made possible the monitoring of overall bulk power systems as well as provided insights into system dynamics. Phasor measurement units (PMU) have been deployed in many points of a power grid system to measure phasor parameters, such as frequency, amplitude and angle of the electrical supply in a 3-phased alternating current (AC) electric power grid. A type of single-phase Phasor Measurement Unit (PMU) known as a Frequency Disturbance Recorder (FDR) may be used for amplitude, angle, and frequency measurements at a typical distribution level electric outlet. Typical PMUs and FDRs require direct electrical contacts with the power lines to sense the electric signals, making the setup process for the PMUs and the FDRs relatively complex and costly. PMUs may employ current transformers physically connected to the transmission line, transformers or bus to obtain current signals/information, and potential transformers physically connected to the transmission line, transformers to obtain voltage information for synchrophasor measurement. However, the physically connection of PMUs results in high installation and maintenance costs. The high installation and maintenance costs limited installation and widespread use of PMUs. In addition, PMUs may be deployed in substations to monitor electric power systems, so they have low accessibility and portability. In remote areas, it may be difficult and inconvenient to set up a PMU or FDR, which may be typically bulky and expensive. The low accessibility and low portability limits the deployment locations of PMUs in wide-area electric systems.

Therefore, there may be a need for a portable inexpensive type of PMU/FDR systems that can function in remote locations without significant performance degradation or complex setup processes.

DETAILED DESCRIPTION

FIG. 1illustrates a real-time PMU system100for monitoring and situational awareness of electric power systems according to an embodiment.

A PMU may be a device which measures the phasor of specific location points of an electricity grid, using a common time index for synchronization. Time synchronization allows synchronized real-time measurements of multiple remote measurement points on the grid. Synchronized phasor (Synchrophasor) measurement may be one of the key elements of wide area measurement systems (WAMS) in advanced power system monitoring, protection, and control applications. Synchrophasor measurements can provide a unique capability to monitor system dynamics in wide area and in real-time, as well as the possibility of controlling and protecting the electric power system.

According to an embodiment ofFIG. 1, the system100may include a sensor110, an amplifier filter120, an analog-to-digital (A/D) converter130, and an estimator140. The system100may be implemented on a mobile communication device, such as a cell phone or a satellite phone, by augmenting the mobile device with additional components, such that the microprocessor of the mobile device may be used to control the various components of system100and perform various calculations. For example, the estimator140may be implemented on the mobile device, and the sensor110, the amplifier filter120, and the A/D converter130may be connected to the estimator140on the mobile device.

The sensor110may be placed near a set of power grid equipment (such as power transmission lines)900without directly contacting them, and may include an electric field transducer, which measures by transduction an electric field characteristic of a voltage carrying element such as transmission line at a specific location point in an electrical power system, and generates at least one signal representative of the electric supply at the specific point. For a 3-phase power transmission lines for example, the combined electric field of the transmission lines may add up as an electric field of varying strength and polarity (sinusoidal in waveform) at the sensor110. The amplifier filter120may amplify and filter the signal from the sensor110. The A/D converter130may convert the signal into digital form. The estimator140may calculate/estimate the phasor data, such as phase angle and frequency, of the electric power grid at the specific point in the electric system.

The system100may optionally include a server150, designed to receive and store phasor data, such as phase angle and frequency, estimated from one or more remote locations, simultaneously or otherwise.

The A/D converter130may be controlled by a microprocessor of a mobile device to generate the digital output signal. The A/D converter130may be connected to the mobile device through Universal Serial Bus (USB) connectors. Mobile local time may be calibrated by Network Time Protocol (NTP) using the mobile device's communication link with the server150, or a communication network of a wireless/cellular service. Alternatively, Global Positioning System (GPS) signals may be used to provide a synchronized local time. The local time may be used as synchronization signal to control the A/D converter130.

The estimator140may be a separate dedicated processor that calculates/estimates phasor data, or a phasor estimation algorithm may be implemented on the microprocessor of the mobile device to calculate phasor data, such as phase angle and frequency. The phasor data may be transmitted over any wireless network for system and/or saved locally on the mobile device, using NTP synchronized time as global timestamp for the phasor data.

The electrical characteristics of the specific point of a transmission line may be determined without physical connection to transmission line by using measurement from the electric field generated by the transmission line, known as transduction. The transmission line produces an electric field between the line itself and the ground. The frequency of the varying electric field corresponds to the frequency of the voltage signal in the transmission line.

An electric field transducer with free-body type sensor may measure the charging current in between the two halves of isolated conductive bodies. The free-body type sensor refers to sensors that include two conductive plates (isolated conductive bodies) with an insulation layer (or vacuum) between them. Larger sized isolated conductive bodies may produce stronger measurement signals. Consequently, it may be desirable to design and construct an electric field transducer sufficiently large to maximize measurement signal strength. On the other hand, to make the PMU mobile and portable, the size of electric field transducer may need to be as small as possible. An exemplary sensor110may include a printed circuit board (PCB) that has two layers of parallel copper plates. The PCB, for example, may have copper plates of each 5.05 cm in length, 3.05 cm in width, (˜15 cm2in area), and 0.75 cm in thickness between the two parallel copper plates.

The analog output signal from the sensor110may be directly converted to a digital signal via A/D converter130. However, the overall resolution and accuracy of digital signal may be significantly improved as the magnitude of the input signal to A/D converter130reaches the maximum input range of the A/D converter130. For this reason, it may be desirable to amplify the signal generated by sensor110.

The amplifier filter120may use ultra-precision operational amplifier (Op Amp) to amplify the output signal generated by electric field transducer. The amplifier filter120may have multi-stage amplification circuits to achieve desired amplification. The amplifier filter120may include analog low pass filter to filter noise in the signal, at the output end of the amplifier filter120.

FIG. 2illustrates a portion of the system according to an embodiment of the present disclosure, including the sensor210and the amplifier filter220.

According to an embodiment as illustrated inFIG. 2, sensor110may be an electric field sensor that includes two isolated conductive bodies, with one body connected to ground (GND), and another body connected as input to the amplifier filter220. The amplifier filter220may include 3 operation amplifiers (Op-Amp), Op-Amp1through Op-Amp3. Each Op-amp may be for example, an Op-Amp OP177from Analog Devices, Inc of Norwood, Mass. Op-Amp1may be connected to resistor R1and capacitor C1to provide as a high input impedance stage. Op-Amp2may be connected to resistors R2, R3, and R4to provide as an amplifier stage. Op-Amp3may be connected to resistors R5and C2to provide as a low pass filter stage.

R1may be a 1 Kiloohm (KΩ) resistor which may be electrically connected as input to Op-Amp1. A C1of 0.1 microFarad (μF) capacitance and a R2of 1 KΩ resistance may be used to connect between the output of Op-Amp1and the input of Op-Amp2. C1may be used to block any direct current (DC) components in the measured signals. Op-Amp2may be connected with a 1 KΩ resistor R3and an adjustable resistor R4with maximum value 500 KΩ to allow adjustment of the range of gain for the different voltage level of transmission line. Thus here, the amplifier filter220may provide a maximum gain ratio of 500. The Op-Amp3may be connected to a 806Ω resistor R5and a 1 μF capacitor C2to provide as a low pass filter with a cutoff frequency of 197 Hz. The output signal Vout may be connected to the input of the A/D converter130.

Further referring to the PMU system100inFIG. 1, the A/D converter130may convert analog output signal from the amplifier filter120to digital signal. Internal A/D converter in a microcontroller may be used for analog to digital signal data conversion. An exemplary microcontroller may be for example, a ATmega328. It has an internal 10-bit A/D converter. However, the greater resolution of A/D conversion, the greater accuracy of phasor data becomes. Thus, additional external A/D converters may be used with a microcontroller to provide additional bits for higher A/D conversion resolution.

A microcontroller may control the A/D converter130's sampling rate, and may receive the digital data from A/D converter130. The digital data may be transmitted to the mobile device via USB connection, such as through a USB host controller IC MAX3421E. The MAX3421E host controller implements a full-speed host compliant to USB specification v2.0. The mobile device may send the sampling command to the A/D converter130.

The microcontroller may be a part of the A/D converter130. The microcontroller may control the A/D converter130using firmware/hardware, or may be implemented with a processor performing the calculations according to a set of computer program codes from a non-transitory computer-readable storage medium.

Network Time Protocol (NTP) may provide timestamp data for phasor data and may provide synchronization signal for the A/D converter130. The Coordinated Universal Time (UTC) timestamp may be retrieved by requesting a NTP server every 2 second. The received NTP timing information coordinates local time of mobile PMU system100to calculate the local time and globally synchronized timestamp.

FIG. 3illustrates a digital sampling of a signal in a timing diagram according to an embodiment of the present disclosure.

Synchronized and time stamped digital data may be transmitted to the estimator140for processing in phasor estimation algorithm on the mobile PMU system100. Digital data may be processed in the estimator140with digital filter to reduce the noise and harmonics of the digital signal. Digital averaging filter may be implemented by oversampling the analog signal at the A/D converter130and then averaging the sequence of digital samples to reduce the noise in signal, as illustrated inFIG. 3. The equation used for realizing filter may be shown in Equation (1) below.

where Avg(i) may be the sample data of filtered signal, and Sa(j) may be the sample data of input signal. Avg(i) may be calculated by averaging Nssamples from Sa(i×Ns−(Ns−1)/2) to Sa(i×Ns+(Ns−1)/2). Generally, the noise can be better filtered with higher value of Ns. However, a larger Ns requires a higher sampling rate, which increases the hardware and computation burden. As a result, a balance needs to be struck between filter performance and hardware burden. An exemplary Ns may be set to 15.

In addition, digital band-pass filter that has a central frequency close to nominal frequency can also reduce the noise in the signal, results in accuracy improvement of phasor data.

FIG. 4illustrates a phasor estimation process400according to an embodiment of the present disclosure. The phasor estimation process400may be implemented as on a firmware/hardware level, or may be implemented in a processor performing the calculations according to a set of computer program codes from a non-transitory computer-readable storage medium.

The phasor of filtered digital signal may be calculated by phasor estimation algorithm shown inFIG. 4. The filtered digital signal may be fitted to extended phasor model that includes both fundamental and multiple harmonics components. Equation (2) represents the extended phasor model includes harmonics.
s(t)=A0(t)cos(2πf0t+φ0(t))+Σi=2∞Ai(t)cos(2πif0t+φi(t))  (2)

An exemplary of the extended phasor model may be to model fundamental frequency component, 2ndand 3rdorder harmonics components of the digital signal as shown in Equation (3).
s(t)=A0(t)cos(2πf0tφ0(t))+Σi=23Ai(t)cos(2πif0tφi(t))  (3)

Compared to other higher harmonics components, 2ndorder and 3rdorder harmonics causes greater estimation error of phasor data. As a result, including 2ndorder and 3rdorder harmonics component in phasor model may significantly compensate for the errors and improve the estimation accuracy of phasor data.

The phasor model may be linearized using polynomial for estimation. Quadratic polynomial equations may be accurate enough to linearize the fundamental component of the digital signal, and linear polynomial may be appropriate to linearize 2ndorder and 3rdorder harmonic component. As a result, the linearized phasor model may be represented by

f0may be the nominal frequency;P(t) andQimay be complex conjugates of P(t) and Qi(t), respectively.

Then, sequential samples of the digital data may be fitted to the linearized phasor model to obtain the following equation
S=BM(5)

M may be a matrix constructed with the coefficients of the quadratic polynomial and linear polynomial.

B corresponds to the relationship between S and M.

Then, a weighted least squares method may be used to estimate the phasor p0in M. The best estimate of M may be given by
{circumflex over (M)}WLS=(B′W′WB)−1B′W′WS

where W may be weights of the window, and Hanning widow may be used in this method. It should be noted that the other windows cam also be adopted, so the window may be not limited to the Hanning window.

Then the angle and magnitude can be calculated by
φ0(t)|t=0=∠p0(6)
A0(t)|t=0=|p0|  (7)

Because frequency may be derivative of angles, in order to estimate frequency, angles may be fitted to polynomial functions as shown below.

where N may be the number of angles used to estimate frequency, and i=1, . . . , N. K may be the order of the polynomial. φ(i) (i=1, . . . , N) may be the angle estimated using Equation (6).

A least squares fitting method may be used to estimate the coefficients of polynomial
φcoef=(Mf′Mf)−1Mf′φ  (9)
where
φcoef=[φF0,φF1, . . . ,φFK]′.

Mfmay be a N×(K+1) matrix, and

Then, frequency can be derived using the coefficients of polynomial, as shown below.

Ncycmay be the number of samples per fundamental cycle. Msampmay be the number of samples slid by angle estimation window. In order to eliminate the effect of odd order harmonics on frequency estimation, a ½ fundamental cycle shift may be used in the method. Note that the number of samples slid between windows may be very important for frequency estimation under harmonics condition. A ½ fundamental cycle shift will not cause frequency estimation error under odd order harmonics condition.

As a length of phasor estimation window affects estimation accuracy, a longer estimation window has better accuracy under steady-state signal condition, but worse accuracy under dynamic conditions. The length of the window may vary to comply with the requirement of different applications. An exemplary window size of phasor estimation window may be a four fundamental frequency cycle. Additionally, the number of angles and the order of polynomial used for frequency estimation may affect the frequency estimation accuracy. Generally, a steady-state signal may be able to use more angles and low order polynomial, and dynamic signal may be able to use less angles and higher order polynomial. An exemplary of the parameters of the phasor estimation algorithm may be shown in Table 1 below.

FIG. 5illustrates a mobile user interface500for use on a mobile platform based PMU system100according to an embodiment of the present disclosure. According to an embodiment, phasor data may be visually displayed on a mobile device for better user interaction. Users may be able control the PMU system100and to display different phasor information such as signal magnitude, angle, and frequency, in real time, or alternatively retrieve historical data stored on PMU system100or on server150.

Thus, the mobile platform wireless PMU system100may be much less costly and easier to setup and install than PMUs that use current transformers and potential transformers to measure phasor data by direct contact. More importantly, a significant feature of mobile platform wireless PMU may be portability. The unique features of mobile platform wireless PMU may be able to promote its quick and extensive deployment in larger-scale interconnected electric power system and/or distributed systems.

The mobile platform based wireless PMU and method therefore may be not limited to the specific embodiments described above, but includes variations, modifications, and equivalent embodiments defined by the following claims. The embodiment described above may be not necessarily in the alternative, as various embodiments may be combined to provide the desired characteristics.

It may be appreciated that the disclosure may be not limited to the described embodiments, and that any number of scenarios and embodiments in which conflicting appointments exist may be resolved.

Although the disclosure has been described with reference to several exemplary embodiments, it may be understood that the words that have been used may be words of description and illustration, rather than words of limitation. Changes may be made within the purview of the appended claims, as presently stated and as amended, without departing from the scope and spirit of the disclosure in its aspects. Although the disclosure has been described with reference to particular means and embodiments, the disclosure may be not intended to be limited to the particulars disclosed; rather the disclosure extends to all functionally equivalent structures, methods, and uses such as may be within the scope of the appended claims.

The illustrations of the embodiments described herein may be intended to provide a general understanding of the various embodiments. The illustrations may be not intended to serve as a complete description of all of the elements and features of apparatus and systems that utilize the structures or methods described herein. Many other embodiments may be apparent to those of skill in the art upon reviewing the disclosure. Other embodiments may be utilized and derived from the disclosure, such that structural and logical substitutions and changes may be made without departing from the scope of the disclosure. Additionally, the illustrations may be merely representational and may not be drawn to scale. Certain proportions within the illustrations may be exaggerated, while other proportions may be minimized. Accordingly, the disclosure and the figures may be to be regarded as illustrative rather than restrictive.

One or more embodiments of the disclosure may be referred to herein, individually and/or collectively, by the term “disclosure” merely for convenience and without intending to voluntarily limit the scope of this application to any particular disclosure or inventive concept. Moreover, although specific embodiments have been illustrated and described herein, it should be appreciated that any subsequent arrangement designed to achieve the same or similar purpose may be substituted for the specific embodiments shown. This disclosure may be intended to cover any and all subsequent adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the description.

In addition, in the foregoing Detailed Description, various features may be grouped together or described in a single embodiment for the purpose of streamlining the disclosure. This disclosure may be not to be interpreted as reflecting an intention that the claimed embodiments require more features than may be expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter may be directed to less than all of the features of any of the disclosed embodiments. Thus, the following claims may be incorporated into the Detailed Description, with each claim standing on its own as defining separately claimed subject matter.