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IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 2, JUNE 2012
Utilizing a Smart Grid Monitoring System to Improve
Voltage Quality of Customers
Kerry D. McBee, Member, IEEE, and Marcelo G. Simões, Senior Member, IEEE
Abstract—The implementation of smart grids will fundamentally change the approach of assessing and mitigating system
voltage deficiencies on an electric distribution system. Many
distribution companies have historically identified customer level
voltage deficiencies utilizing a reactive approach that relies upon
customer complaints. The monitoring capabilities of a smart grid
will allow utilities to proactively identify events that exceed the
voltage threshold limitations set forth by ANSI Std. C84.1 before
they become a concern to end-users. This proactive approach can
reduce customer complaints and possibly operational costs. This
paper describes an approach for determining voltage threshold
limits as a function of duration for proactive voltage investigations
utilizing smart grid monitoring equipment. The described approach was applied to a smart grid located in Boulder, Colorado.
This paper also describes the results of this two-year study.
Index Terms—Customer complaints, operational costs, power
quality, smart grid, smart meter, voltage quality.
I. INTRODUCTION
T
HE Department of Energy (DOE) envisions a smart grid
as a distribution system that consists of an extensive monitoring system [1]. Such a system allows for the monitoring of
attributes such as voltage, current, kWh, and kVA at substations
transformers, distribution transformers, smart meters, distribution switching devices, and strategically installed power quality
monitors. The number of system monitors on a smart grid is considerably more than the number found on existing distribution
systems, which may only have several power quality monitors
per feeder even if installed in accordance with the EPRI recommendations for monitoring feeder level power quality events
[2].
Prior to the implementation of smart grids, EPRI recommended the installation of power quality monitors at the
substation, middle of the feeder, end of the feeder, and near
customers with sensitive loads. Unfortunately many electric
distribution systems in use today fall short of even these EPRI
recommendations by focusing most power quality efforts at the
substation transformer. This lack of monitoring at the distribution level allows many voltage events that occur on distribution
feeders or on the secondary side of distribution transformers
Manuscript received May 30, 2011; revised October 08, 2011; accepted December 11, 2011. Date of publication April 27, 2012; date of current version
May 21, 2012. Paper no. TSG-00153-2011.
K. D. McBee is with the Colorado School of Mines, Golden, CO 80401
USA, and also with Xcel Energy, Denver, CO 80235 USA (e-mail: kerry.d.
mcbee@xcelenergy.com).
M. G. Simões is with the Department of Engineering at Colorado School of
Mines, Golden, CO 80401 (e-mail: msimoes@mined.edu).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TSG.2012.2185857
to go unnoticed. In most cases the only notification the utility
has of a voltage discrepancy comes from customers who are
experiencing discomfort and/or equipment malfunction. The
implementation of a smart grid monitoring system allows utility
personnel to perform remote voltage investigations as soon as
voltage events occur and before problems occur for customers.
These investigations can be performed at the feeder level and
at the customer’s point of common coupling (PCC), which is
important when investigating customer power quality issues
[1], [3].
All devices that sense voltage, even if they do not possess
power quality monitoring accuracy, are available to utilize for
identifying voltage fluctuations that are damaging to customer
equipment and/or reduce the quality of service for customers. A
smart grid monitoring system consists of a main communication
system that connects all devices with remote monitoring capabilities, utility and end-user owned, to a central data collection
location which simplifies access to all data retrieved [4]. The
aggregate number of these devices can account for hundreds of
monitoring points per feeder depending upon design and customer penetration. Remote monitoring devices include:
• capacitor banks;
• distribution transformers;
• smart meters;
• power quality meters;
• phase monitoring units.
Remote monitoring will allow for the identification of voltage
deviations prior to equipment malfunction or misoperation that
are noticeable to customers. Also, system deficiencies that
have gone unnoticed by customers and utility personnel prior
to the installation of a monitoring system will become evident.
Four benefits to implementing a remote voltage investigation
approach include the following:
• reduced number of customer voltage complaints;
• lowered operational costs associated with investigating
customer voltage problems;
• reduced number of outages caused by failed connections;
• prevention of damage to utility or customer equipment.
Historically customers have been the main source of identifying voltage discrepancies. The goal of a proactive approach is
to identify problems before they become a concern to customers,
therefore a new notification system is required. A smart grid can
employ numerous software applications to interface with, interpret measurements from, and control distribution system devices. This type of software can provide automatic notification
to utility personnel of voltage sags, swells, and other voltage
events prior to them becoming a nuisance or problem to customers. Because many voltage events are temporary in nature,
1949-3053/$31.00 © 2012 IEEE
MCBEE AND SIMÕES: UTILIZING A SMART GRID MONITORING SYSTEM TO IMPROVE VOLTAGE QUALITY OF CUSTOMERS
and do not warrant field investigations, threshold limits that include magnitude and time durations should be employed to insure the effectiveness of a proactive voltage investigation program.
This paper examines how to establish threshold limits for
the duration and magnitude of voltage events. Section II details both the existing reactive approach and the proposed proactive approach. Upper and lower threshold limits are detailed in
this section along with an approach for determining duration
threshold levels. To determine the effectiveness of the proactive
approach and the methods described for determining thresholds
limits, the methodology was applied to a smart grid located in
Boulder, Colorado and operated by Xcel Energy. The Boulder
smart grid, commonly referred to as SmartGridCity, consists of
26 feeders that serve approximately 25 000 customers. At the
time of this research, its smart grid monitoring system consisted
of over 10 000 smart meters and 5000 sensors installed on distribution transformers, both of which provide real time voltage
readings. The results of applying the proactive approach to this
smart grid along with an evaluation of the customer and economic benefits are detailed in Section IV.
II. REACTIVE VERSUS PROACTIVE APPROACH
INVESTIGATIONS
TO
A. Reactive Approach to Investigations
In the past, most voltage quality investigations performed by
distribution companies have been the result of customer complaints. This paper categorizes this approach of identifying and
mitigating such problems as a “reactive” approach. The general
reactive approach is described below.
A utility company is notified by a customer that equipment
is malfunctioning due to suspected voltage fluctuations, which
are identified by customer equipment failure and dimming or
flickering lights. Customers may also hire an engineering firm
to investigate problems prior to notifying the utility. Although
informative, a distribution company never wants to rely exclusively on a report provided by a customer’s investigator due
to the unknowns associated with their monitoring techniques,
specifically in regards to the IEEE std. 1159 [3].
Utility field personnel, many times in the form of a lineman,
are dispatched to obtain instantaneous readings and/or to identify the severity of the voltage fluctuations. If instantaneous
readings do not suggest a problem, the utility company may
choose to install power quality recording devices at the customer’s PCC, within the customer’s facility, and possibly at several locations along the circuit serving the customer in accordance with [3]. Voltage readings are recorded for a given time
period, which is dictated by the frequency of the disturbances
[3]. Many times the duration of recordings are limited by the
small number of power quality recorders and the high volume
of investigations. For events that are infrequent, this situation
leads to investigations that are not thorough. This is rarely the
case with a smart grid investigation since information is provided for days, weeks, and months.
Power quality investigators analyze the recorded data to determine if the voltage fluctuations violate the threshold limitations set forth by ANSI Std. C84.1 and possibly a local regula-
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tory agency [5]. If it is found that threshold limits are exceeded,
the utility company will act to mitigate the problem. If it is found
that the deviation is due to customer equipment, it is the customer’s responsibility to mitigate the problem.
The action taken by the distribution company is heavily
dependent upon two things: 1) exceeding limits set by ANSI
Std. C84.1 and/or tariffs set forth by local regulatory agencies;
2) a customer complaint regarding poor service. Utilizing
both known standards and customer complaints has proven
to be a very reliable approach for mitigating voltage quality
problems in the past. However, a smart grid monitoring system
can remove customers as the notification system and thereby
improve customer service.
B. Proactive Approach to Investigations
The increased monitoring capabilities of a smart grid will
allow for the identification of voltage quality problems at the
same time as the customer, or before the customer experiences
any significant equipment malfunctions or misoperations. This
“proactive” approach will eliminate the customer as a means of
identifying system deficiencies, which will leave the utility engineer with only the known standards and regulatory tariffs as a
guide for determining system deficiencies.
The authors have chosen to refer to voltage, current, and
frequency fluctuations found through a smart grid monitoring
system as deficiencies and not power quality events. Most definitions of power quality include the powering and grounding
of equipment that is appropriate for normal operation [3],
[6], [7]. Since customers are removed from the investigation,
there is no evidence that equipment has malfunctioned or
misoperated. Therefore the incentive of the utility company is
not to improve power quality for customers, but to reduce and
eliminate system deficiencies that are inefficient and may result
in customer and/or utility equipment failure if not addressed.
The elimination of customers as a means for voltage problem
identification also presents a problem to the utility company.
Which voltage deficiencies are investigated to minimize customer impact and optimize operational efficiency? Should a
utility company investigate every voltage deficiency, even if its
duration is only several cycles and only occurs once?
The proactive approach to system monitoring should rely
heavily upon voltage thresholds set forth by ANSI Std. C84.1
and local regulatory agencies. Std. C84.1 was developed for
the purpose of protecting equipment from experiencing damaging voltages; therefore utilizing these thresholds provides
protection for customer and utility equipment [5].
The standard defines two voltage ranges that are applicable
for utility service and the utilization of end-user equipment
above and below 600 V. Range A, which describes acceptable
voltage ranges for steady state operations, provides the most
conservative approach to investigations since these limits are
the most stringent and will thereby identify more system deficiencies. For residential customers at 120 V the upper and lower
limit is
, which is more stringent than the minimum
variation limits that define voltage sags and voltage swells [3].
Range B accounts for voltages that result from abnormal, but
necessary operating conditions. Table I illustrates Range A of
ANSI Std. C841 [5].
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IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 2, JUNE 2012
TABLE I
ANSI STD. C84.1-2006 RANGE A ACCEPTABLE VOLTAGE LEVELS
Voltage threshold limits are applied according to the location
of the device that is being monitored. If the reading is taken at
a smart meter, the service voltage limits should fall within the
limits set by Range A of B. However, if the voltage is monitored
at the distribution transformer, the lower limit should reflect at
least a 2 –3 V drop on the service conductors, which would result
in a lower limit of 116 –117 V on systems below 600 V. Any
violation of these limits, regardless of duration, is considered
a voltage deficiency, which by definition includes more events
than if only voltage sags and swells were considered.
The smart grid monitoring system should interface with software that automatically notifies utility engineers when voltage
deficiencies occur. Upon notification, the utility must determine
if the event was temporary in nature or is the result of system
deficiencies, with the latter type of events being investigated further. These system deficiencies are continuous in nature and will
not remedy themselves.
Evaluation of continuous events should include summing the
duration of all voltage events that occur in a given time period.
Temporary faults, which can be the cause of voltage events, can
comprise as much as 76%–80% of all system faults on system
[8]–[10]. Most customer complaints are the result of long-term
voltage problems, not those caused by temporary events.
The aggregate time below or above the magnitude threshold
is utilized to distinguish between temporary events and events
that are consistent, but possibly infrequent. Any violation that
deviates below or under the set magnitude threshold for an accumulated time of
for a given period
is investigated in
further detail. The concept is illustrates mathematically in (1)
and graphically in Fig. 1.
(1)
where:
total time duration above or below threshold
limits for time period ;
time duration of
event in time period
;
total number of different events where voltage
thresholds are exceeded;
investigation duration, typically a day, week, or
month.
Fig. 1. Investigation envelope graph illustrating different investigation zones
for events based on total time below or above threshold.
Investigation zones are defined utilizing high and low
threshold limits and . Voltage events that have aggregate
time less than and fall into Zone 1 of Fig. 1 are considered
temporary in nature and are not investigated any further. The
time duration of this zone, which is defined by , should be
based upon customer type. Customers more susceptible to
voltage sags and swells, such hospitals and commercial or
industrial facilities with critical processes could arrange an
agreement with the Utility to have a
that is satisfactory to
capture repeated voltage sags and swells. Zone 2 consists of
voltage levels that are acceptable. Therefore, the only voltages
deficiencies investigated are those that fall into Zones 3 and
4, which are undervoltage and overvoltage zones. can range
from a day, week, to a month, depending upon the desired level
of investigation.
III. APPLICATION OF PROACTIVE APPROACH
The proactive investigation approach was applied to a smart
grid located in Boulder, Colorado and operated by Xcel Energy,
an electric utility company that generates, transmits, and distributes energy in eight states. At the time of the analysis, the
smart grid consisted of 26 circuits served by 4 substations. The
smart grid served over 25 000 customers with its smart meters
and 5000 voltage sensors installed on distribution transformers,
both of which provided real time voltage and kWh readings. The
system, which also utilizes self healing automation, went online in August of 2008, which coincided with the start of proactive investigations. The software utilized for interpreting smart
meter and distribution transformer data was OpenGrid Distribution (OGD), which is manufactured by the Current Group. The
authors utilized the software and the guidelines described in the
previous section to proactively investigate voltage discrepancies that exceeded the voltage investigation envelope illustrated
in Fig. 1. Upon the proactive identification of voltage problems,
utility field personnel were dispatched to verify problems and to
evaluate if mitigation actions were required.
The magnitude threshold limits utilized for the study were
based on Std. C84.1 Range A, but did not follow them exactly.
A lower threshold limit of 117 V was utilized for sensors at
distribution transformers, which can have a voltage that is 2–3 V
higher than the voltage at the customers’ meter. The upper limit
was not adjusted to account for secondary voltage drop so as
MCBEE AND SIMÕES: UTILIZING A SMART GRID MONITORING SYSTEM TO IMPROVE VOLTAGE QUALITY OF CUSTOMERS
Fig. 2. Voltage profile of 50 kVA transformer with a loose neutral connection
as provided by Open Grid Distribution software.
not to exceed 126 V for situations where the secondary voltage
drop is less than 2 V. The total duration
for events was set
at 30 min (0.5 h). The period of 96 h was utilized as .
Investigations included researching any system event that fell
into Zones 3 and 4. Problems found included:
• low voltage due to overloaded transformers;
• high and low continuous voltage due to loose neutral connections;
• intermittent high and low voltage due to loose conductor
connectors;
• low voltage as a result of system reconfiguration due to
outage restoration and new construction;
• high and low voltage due to failed distribution transformer
windings.
The software provided the authors with visual graphs of
voltage events, which simplified the identification of violations
of the voltage investigation envelope. A loose neutral connection was identified in Fig. 2, which illustrates the separation
of voltage between the two transformer secondary conductors
(LEG 1 and LEG2). A distribution transformer overload, which
is illustrated in Fig. 3, was verified as being caused by a new
customer connecting to the distribution transformer. Fig. 4
illustrates the identification of high voltage that was the result
of a malfunctioning substation transformer load tap changer.
Because the voltage problem found in Fig. 4 was caused by
a substation device, the majority of the transformer sensors
and smart meters recorded the same excessive voltage, which
simplified the identification of the cause.
Events such as overloaded transformers, loose connections,
and failing transformers are not self-correcting over time; in
fact they would most likely become progressively worse due to
the nature of electrical equipment failures. Therefore, the utility
company can pay for repairs before it affects customers or after.
Waiting to mitigate problems can possibly be more expensive
if the system deficiency results in utility or customer equipment
damage, or a catastrophic failure occurs outside of normal business hours, thereby resulting in utility personnel working overtime and possibly requiring the emergency shipment of equipment.
The results of the study revealed that investigation zones accurately captured problems that would eventually lead to cus-
741
Fig. 3. Voltage profile of an overloaded 50 kVA transformer as provided by
Open Grid Distribution software.
Fig. 4. Voltage profile of a 50 kVA transformer with high primary side voltage,
as provided by OpenGrid Distribution software.
tomer complaints. A total of 45 voltage discrepancies were identified between August 2008 and December 2010. Fig. 5 illustrates the voltage problems identified, where they fell on the investigation envelope graph, and if the problems required equipment repair or upgrade (Action Required) or if they were due
to abnormal operating conditions or were temporary in nature
(No Action), which did not warrant mitigation. From these results, a more refined investigation envelope graph was developed, which is also illustrated in Fig. 5.
Prior to implementation of the smart grid monitoring system,
Xcel Energy regularly experienced voltage complaints in excess of 20 per year in the smart grid territory, with a peak of 50
complaints occurring in 2007. In 2009 and 2010, which were
the first two complete years of implementation, 5 and 7 voltage
complaints were recorded in the SmartGridCity territory. Fig. 6
illustrates the voltage complaints by year for the smart grid territory.
It should be noted that the complaints recorded in 2009 and
2010 where not caused by voltage deficiencies. Customers
requested investigations because of equipment misoperations;
however, in each case the cause was determined to be due
to customer owned equipment. Because of these types of
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IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 2, JUNE 2012
TABLE II
FIVE-YEAR SUMMARY OF VOLTAGE COMPLAINTS
Fig. 5. Graph of all voltage deficiencies identified during 28-month analysis
period.
TABLE III
COSTS AFFILIATED WITH VOLTAGE EVENTS 8/1/08–12/31/10
Fig. 6. Voltage complaints between 2004 and 2010 in SmartGridCity footprint.
occurrences, voltage complaints may never go to zero in the
SmartGridCity territory.
Proactive investigations reduced the number of customer
complaints, which are illustrated in Fig. 6, but did not reduce
the number of voltage investigations. Complaints and proactive
investigations were combined to determine the percentage of
investigation performed within the SmartGridCity territory to
those occurring outside of the smart grid territory. Between
2006 and 2010, the percentage of investigation performed in
the smart grid territory, including both reactive and proactive
investigations, ranged between 8.72% and 5.08%, with the
latter occurring in 2010. Although the percentage decreased
with time, as evident from Table II, the authors believe that the
slight deviation is possibly the result of annual fluctuations in
load, weather, and system constraints. Although the number
of investigations did not decrease, the cost associated with
investigating voltage deficiencies proactively did decrease.
The total cost savings for 2009 and 2010 were calculated
based on investigation costs. Specifically, the costs of remote investigations were compared to the costs of performing the same
investigations utilizing the reactive approach to voltage investigations, which utilizes lineman and/or field visits by power
quality investigators. Between 2006 and 2008, a lineman was
initially dispatched for 36% of the investigations. The average
cost of a lineman per investigation was $120, which included a
single lineman, bucket extension truck, travel time, and investigation time. On-site power quality investigations were assumed
to include a power quality investigator, recording equipment,
recording equipment installation time, one week of data monitoring, and at least a day of data processing and analysis totaling
an average operational cost of $520 per investigation.
Smart grid investigations averaged no more than 2 h, which
include office and field work. The authors, who are experienced
in power quality investigations, performed the remote investigations; therefore the only requirement was 1 h of training on
OGD, the software utilized to interpret smart meter and distribution transformer sensor measurements. The proactive investigations consisted of two actions. First, the authors identified
a voltage problem with OGD, which took approximately 5 min
with the automatic system notification. Once identified, the authors determined if field validation was required. A lineman was
dispatched for 84% of the identified voltage events to validate
and excess the problem. The average time spent on a remote
investigation by the authors was 5–20 min, at an average cost
of $14 per investigation. Based on the 45 problems identified
during the 16-month period, the total cost of remote investigations was estimated to be approximately $5190. Applying the
same 45 voltage problems to the reactive investigation costs described in the previous paragraph would result in a monetary
MCBEE AND SIMÕES: UTILIZING A SMART GRID MONITORING SYSTEM TO IMPROVE VOLTAGE QUALITY OF CUSTOMERS
impact of $25 320, an increase of $20 130 or 487% from the
cost of proactive investigations. Table III summaries the costs
associated with both proactive and reactive investigations for
the 45 voltage events identified. Even if the proactive approach
resulted in more voltage event investigations than if the utility
relied exclusively upon customer complaints, a success rate of
20% for proactive investigations would still be less costly than
relying exclusive upon a reactive approach.
The cost of implementation is not considered in the economic evaluation presented in this paper. Because of the many
functionalities of the equipment utilized for proactive voltage
investigations, comparing implementation costs to voltage
investigation benefits would be inaccurate and misleading.
Additional functions of the equipment utilized includes automated meter reading, feeder voltage and var optimization that
reduces system losses, transformer loss management, outage
notification, and the identification of nested outages during
storm outages restoration efforts.
IV. CONCLUSION
The extensive monitoring system of a smart grid will
allow distribution companies to proactively investigate system
voltage deficiencies. Without customers acting as a notification
system, distribution companies can rely upon ANSI Std. C84.1
and local tariffs in conjunction with predetermined duration
thresholds to determine if a potential voltage problem exists.
The case study presented in this paper illustrated that utilizing a
30-min duration for a 96-h window of monitoring is sufficient
for reducing customer voltage complaints. Although complaints
were reduced with a proactive approach to investigations, the
total number of investigations or voltage events investigated
did not decrease. However, the costs associated with voltage
investigations were significantly reduced when compared to
utilizing the existing reactive approach.
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[3] IEEE Recommended Practice for Monitoring Electric Power Quality,
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[5] American National Standard for Electric Power Systems and Equipment—Voltage Ratings (60 Hertz), ANSI Standard C84.1-2006.
[6] IEEE Recommended Practice For Powering and Grounding Electronic
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[7] R. Dugan, M. McGranaghan, and H. Beaty, Electrical Power Systems
Power Quality. New York: McGraw-Hill, 1996, p. 2.
[8] S. F. Tan and S. K. Salman, “Investigation into the implementation of
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Kerry D. McBee (BS’99–MS’00) received the B.Sc.
degree from the Colorado School of Mines, Golden,
in 1999 and the M.Sc. degree in electric power
engineering from Rensselaer Polytechnic Institute,
Troy, NY, in 2000. He is currently working toward
the Ph.D. degree in the Department of Engineering,
Colorado School of Mines.
During his career he has focused on power quality,
reliability, forensic engineering, and distribution design for companies such as NEI Power Engineers,
Peak Power Engineering, Knott Laboratory, and Xcel
Energy. His field of interest is smart grid implementation effects upon distribution engineering and utility operations.
Marcelo G. Simões (S’89–M’95–SM’98) received
the Ph.D. degree from the University of Tennessee,
Knoxville, in 1995.
He is with Department of Electrical Engineering
and Computer Science, Colorado School of Mines,
Golden, where he is the Director of the Center for
Advanced Control of Energy and Power Systems
(ACEPS). He has been conducting research and
education activities in the development of intelligent
control for high-power-electronics applications
in renewable- and distributed energy systems and
smart-grid technology.
Dr. Simões is currently Past Chair for the IEEE IAS IACC and Co-Chair for
the IEEE IES Smart Grid Committee. He has been involved in activities related
to the control and management of smart-grid applications since 2002 with his
NSF CAREER award “Intelligent Based Performance Enhancement Control of
Micropower Energy Systems.”