An engineer’s main objective when troubleshooting a power quality event
is to identify the source of the disturbance in order to determine the required
corrective action. To identify the source, the engineer depends on recorded
data captured by monitoring equipment.
Management demands a cost-effective solution to the problem be implemented as
quickly as possible. The electrical engineer speaks of installing
instrumentation, collecting data, analyzing data, re-installing, and re-analyzing.
It is not uncommon for months to pass until the problem is isolated and a
solution is implemented.
Power quality analysis has traditionally posed a unique challenge to the
engineer, demanding an accurate assumption as to the dimensions of the disturbance
in order to capture the event to memory for examination. The correct balance
between memory size and the deviation of the disturbance from the norm is often
elusive. Thresholds set too low capture too many events of little or no
consequence, filling the memory before the sought after damaging event occurs.
Setting the threshold too high can overshoot the event.
Data
Compression Technology
Revolutionary data compression technology takes the guesswork out of isolating
the source of power quality problems by eliminating the need for devising set
points and calculating threshold values.
The ability to capture all the waveform data in high resolution in its entirety
over an extended period of time is the only way to ensure that the event will
be recorded, allowing the engineer to analyze the data and define a solution.
Until now, monitoring and analyzing system electrical trends have presented a
true challenge because certain data compromises were required to counteract
capacity, processing, and physical limitations. Data compression technology
provides unlimited capacity for power quality data storage. This eliminates the
requirement to set constraints on system data, rendering the risk in data
selection based on set thresholds and triggers obsolete.
Operators of electrical networks are constantly faced with power events and
transient occurrences that affect power quality and heighten energy costs.
In the past, to determine whether such events reflect system trends or isolated
incidents, electrical engineers relied on partial information indicating what
events occurred and when; not all events were recorded due to data capacity
limitations and missed thresholds. Now, engineers analyzing multi-point,
time-synchronized real-time power quality data can actually see why all power
events occur and what causes them. In short, data compression technology pushes
power quality analysis capabilities into the next generation.
Data compression technology allows for both immediate power quality problem
solving as well as for true proactive energy management. The ability to analyze
all data at any time enables energy managers to call up and analyze historic
time-based energy consumption trends in order to make supply side decisions.
Data compression technology allows control over both the consumption and
quality of the supplied energy.
Considerations for optimal system functionality in diverse network topologies
are based on the capabilities of the energy suppliers, service providers, and
industrial and commercial consumers of energy to provide power quality over
time and to successfully analyze, predict, and prevent energy events using
multi-point, historic, and true-time logged data.
Achieving
Benefits
The U.S. Department of Energy estimates that about $80 billion a year is
lost to power quality issues. To reduce these losses, operators must identify
the source of power events, identify the problem sources, and prevent their
re-occurrence.
Problem sources are many and often reflect the need for predictive and
preventative maintenance measures. Utility operators face problem sources such
as capacity, weather conditions, and equipment failures. Consumers suffer from
equipment failures, faulty installations, and incompatible equipment usage
creating destructive resonant situations.
When effective monitoring is installed, power providers will strive to avoid
negative impacts due to diminished quality and service capabilities, so as not
to cause damages due to the following factors:
In industrial sectors:
- downtime
- product quality
- maintenance costs
- hidden costs (reputation, recall)
In commercial and service sectors:
- service stoppage
- service quality
- maintenance costs
- hidden costs (reputation, low customer satisfaction level)
Once a power quality event is fully characterized by accessing compressed power
quality data, a solution can be implemented successfully.
Analysis
Resources and Capabilities
Implementing data compression technology in an electrical installation means:
- Needed information is stored; there are no more data compromises to counter recording resolution and capacity issues
- Years of data for every network cycle are available with no data gaps
- Thresholds and triggers are no longer needed; missing events becomes a thing of the past
- All data parameters are recorded; there is no need to select measurement parameters
- Comprehensive power quality reporting and statistics for data analysis and report generation are accessible and organized
- Multi-point time-synchronized recording provides a true snapshot for any period in the entire network
Over the years, various technologies have evolved for monitoring and logging
power quality data. Su
rely, throughout this period, developers addressed the
same challenges regarding potential power quality, data capacity, and system
trends. Ultimately, the analysis of sampled data serves to manage, maintain,
and optimize system operations and costs.
Four
Technological Generations
It is possible to delineate four distinct generations in the development of
power quality technology:
- 1st generation, power meter/monitor: First-generation
technologies provide display capabilities only. Utilizing analog or digital
technology, logging information is used for monitoring the system.
- 2nd generation, data logger:
Second-generation technologies use periodic logging mechanisms and present data
in paper or paperless form. Still, the information is utilized for system
monitoring only.
- 3rd generation, event recorder/power quality
analyzer: Third-generation technologies require the setting of thresholds and
triggers, which are always difficult to assess correctly given that memory
capacity is finite and quickly filled. When values are set too low the capacity
is filled instantly; when values are set too high very few events are recorded.
- 4th generation, power quality data center:
Fourth-generation technology provides limitless, continuous logging, and
storage of power quality data using data compression technology. Setting of
parameter values, thresholds, triggers, and other constraints on data are no
longer required.
Additionally, a troubleshooter can determine why power quality events occur
over the entire electrical network and then successfully identify what causes
them, regardless of their cycle occurrence. This measurement and analysis
technology enables the engineer to optimize electrical network efficiency and
cut power quality losses by relying on the analysis of ungapped data.
Data
Analysis Advantages
Data compression can help optimize analysis activities by introducing
multi-point time-synchronization to the process (see figure 1 on right). Troubleshooters
can trace energy flows over the network during power events to determine event
causes. It is also important to log network energy flows when there are no
events occurring. Also, logging is necessary at all other points while an event
occurs at a specific point to correctly analyze the event.
During power quality events, impedances change. Using fourth-generation technology,
it is possible to calculate impedances and perform accurate network simulations
for comprehensive analysis.
Examples
Question:
What was the source of the voltage sag?
Answer:
The possible source could be either one, or a combination, of the illustrated
events. Other factors could also be involved. Monitoring multiple sites
simultaneously and continuously allows the engineer to see the whole picture –
all the time. Power quality events can be examined at the time of the event,
and in the context of the timeline before and after the event; comparing the
impedances at this site at different times.
Question:
What causes data bottlenecks when logging data with non-compression
technologies (see figure 2 on right)?
Answer:
Data bottlenecks with non-compression technologies are caused by limitations in
recording speed capabilities, storage space, communication throughput, and
computer processing capacity.
Question:
How are data bottlenecks eliminated by using data compression technology?
Answer:
Data bottlenecks in the logging process are eliminated using data compression
technology (see figure 3 below): the CPU compresses the data; a compact flash is
utilized instead of a hard disk; data are compressed so capacity is not a
factor; in addition, block-oriented processing is implemented.
Implementing
Data Compression
Patent-pending PQZip data compression technology is employed by the
Elspec G4400 Power Quality Data Center and implements:
- Compression algorithm with typical 1000:1
compression ratio. This real-time compression, performed independent of the
sampling, prevents data gaps.
- Multi-point implementation of
time-synchronized devices over the entire grid shows the interactivity of the
values recorded at the different points in the network at that point in time
- Infinite continuous logging and storage of
data for total network analysis.
Summarizing
Benefits
Of the four generations of technological evolution for storing power quality
data for analysis, only fourth-generation data compression technology affords
the unprecedented advantage of infinite, continuous logging and storage of
high-resolution data. Using this new technology avoids capacity issues and for
this reason yielded data are entirely uncompromised. This represents a clear
advantage when analyzing system power trends and events. The natural and
desired outcome of in-depth system analysis is prediction and prevention of
power events, reduced power costs and the constant supply of enhanced power
quality.
This article was printed on December 2006 issue of Energy & Power Management magazine (pp. 18-20).