8/18/2019 Curve Itic Cbema Labview http://slidepdf.com/reader/full/curve-itic-cbema-labview 1/23 Meter Data to Metrics First Semester Report Fall Semester 2013 -Full Report- By Keaton Andersen Chad Brotherton Jeremy Eldridge Prepared to partially fulfill the requirements for ECE 401 Department of Electrical and Computer Engineering Colorado State University Fort Collins, CO 80523 Project adviser: Dr. Siddharth Suryanarayanan
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Quality of power is a very important issue in the world of electronics and computer systems, as well as
for the health of the grid. With this in mind, there are many different metrics that power systems mustadhere to so as to promote the performance and reliability of the grid and the equipment powered by it.
All pieces of equipment powered by the grid are going to have some sensitivity to the quality of power
received. It is for this reason that the quality of power must be monitored. Normally, power quality is
not continuously monitored on the distribution level as the equipment to do so is rather expensive.
With the advent of ‘smart meters’, there are more advanced technologies embedded allowing the meter
its self to monitor some power quality metrics, and collect raw data. Anticipating more and more
advanced meters being deployed more broadly, the “Meter Data to Metrics” project was born.
The “Meter Data to Metrics” project is a 2013-2014 Senior Design project created at CSU with
sponsorship from the customer Schneider Electric. The goal of this project is to develop a dashboard
application that allows the user to easily and intuitively interpret the quality of supplied power signals
via a simple and clean front end interface. While this project was previously done at CSU, all intellectual
developments made on this project are freestanding and independent of what was previously done. This
project is being worked on by senior ECE students: Keaton Andersen, Chad Brotherton and Jeremy
Eldridge with supervision and advising from Dr. Siddharth Suryanarayanan and Ms. Oilvera Notaros.
In order to develop the dashboard application for this project the team has researched various power
quality metrics to full understand how they affect the faithfulness of the supplied power signals as they
relate to an ideal sine wave at 60 hertz. The development for this application was all done using National
Instruments LabView development software. LabView was chosen due to the project member’s level of
knowledge in this coding environment and LabView’s ability to translate from software development
into hardware realization.
Using software, the project will utilize data that is already being collected to calculate power quality
metrics. This allows for cheaper surveying of power quality, as the current cost of a stand-alone power
quality meter can range from $2000 to more than $10,000.
The team has successfully completed the first iteration of the project which runs currently using
simulated data. Future iterations of the project will run off of actual data received from City of Fort
Collins that has been “scrubbed” so as to maintain ethical standards. Intermediate testing between
these stages is planned using data gathered from looking at the current drawn by a compact fluorescentlamp. Shown in Figure 1 below are the current pictures of the Front End Panel of the project
values should be identical in magnitude but opposite in sign. If this is not the case, when the Fourier
Transform is taken of the signal, it will show not only the presence of odd harmonics (which is expected)
but the presence of even harmonics as well. Figure 2 shown below helps illustrate this
In Figure 2, the green arrows represent the maximum and minimum values of the fundamental
waveform with no distortion. The orange arrows represent the maximum and minimum values when aneven harmonic is added to the signal. As seen in Figure 2, if an even harmonic is present it will affect the
fundamental waveform by complimentary or destructive interference. This will cause the maximum and
minimum values to no longer be equal in magnitude. In order to test this numerically, the equation
is used. When using this equation it is important to note that it is unlikely to ever get exactly one, so for
the purposes of this project a small tolerance (0.5% range) is added so that the calculations done by our
application do not always flag a relatively good signal as bad for it not having an asymmetry factor ofexactly one.
When designing the asymmetry factor portion of our application, many different functions from
LabView were utilized. The block diagram of this section, shown in Figure 3 below, is simplistic and clean
to make it easy for future edits to be made if necessary.
Data is pulled in from the supplied power signal and fed into a minimum/maximum value calculator.
From here, the polarity of the minimum value of the waveform is reversed by multiplying by negative
one. It is important to note that a large assumption is made that the minimum value of the signal is
negative. If this is not the case the waveform received would be so distorted that it will fail other metrics
present in the system therefore it is safe to assume for the purposes of this application. After flipping
the polarity of the maximum negative value, the code then processes the data through the equation
discussed previously and checks it against a low tolerance. If the test passes, it will keep the associated
indicator light on the front panel lit green for “pass”. However, if the test fails it will change the color of
the indicator red to let the user know in a simple manner that there is an issue with the signal. In the
current data set up, this light does not need to be latched due to a single input of data but in the future
this indicator may need to latch if the application becomes real time.
b. Total Harmonic Distortion (THD)
Another important Power Quality metric that our program measures is Total Harmonic
Distortion (THD). The presence of THD distorts the current and voltage waveforms, which can be very
detrimental to a power system. Harmonics are introduced when non-linear loads or components are
present in the gird. The non-linearity of these devices causes extra current to be introduced back into
the grid. At a first glance this could seem like a beneficial effect, but the unpredictability of this
introduced current causes problems. This metric is highly regulated by The Institute of Electrical and
Electronics Engineers (IEEE) and the Public Utility Commission (PUC) to ensure that the Power Quality ismaintained. Figure 4 shows the Labview block diagram of how the THD is calculated.
The Computer & Business Equipment Manufacturers Association (CBEMA) curve gives a guideline for the
magnitude and duration of voltage sags and swells from the nominal voltage. The bottom of the curve is
approximated by the equation V3.142
*T=12455, with V as the voltage, and T as the duration. Any voltage
that falls below 10% of the nominal voltage is then used to calculate CBEMA compliance. If the duration
of the sag, along with the magnitude, is above the line, it is acceptable. For example, a sag down to 50%
of the nominal voltage would be acceptable for one half cycle at 60 Hz, where it would no longer be
acceptable for a full cycle. Figure 5 shows the acceptable window for this power quality metric.
This particular metric for power quality was agreed upon by manufacturers of equipment in
acknowledgement of the fact that incoming power will not be perfect, and that all equipment must have
some tolerance to voltage sags or swells. In a fault situation on the grid, the voltage may drop abruptly
for a duration, and it is important that equipment, particularly computers, be able to withstand such
inconsistencies. Any deviation outside of this metric can lead to noticeable effects in lighting andperformance of equipment, up to total malfunction and loss of data on a computer. Other places where
non-compliance with this metric can be troublesome are industrial applications, specifically production
line equipment and automated systems. Voltage sags can cause these pieces of equipment to reset, and
can even lead to unusable product.
The Labview code programmed to fulfill this task is shown below in Figure 6 and Figure 7. In the first
module, Figure 6, each value is run in to the module and checked whether or not it is within 10% of the
nominal value. If the value is determined to be outside this window, it is passed to the next module in
For this project, there have been minimal concerns with budget as it is a software based project.
Currently, the project is being put together with the Labview Student Edition which was free for thegroup. The project was also recently sponsored by National Instruments and will be receiving a MyDAQ
device for later integration to the project if time permits. Other than this hardware, there are no other
looming topics in the budget that need attention. The only exception to this will be presentation
materials for the E-Days event next semester. Total, expenditures for the project are unlikely to exceed