Powerful analytical tools — software, PCs, networks, and the internet — are within a click of the mouse. Power monitoring equipment captures data; software analyzes critical data required for responsible electrical energy management. Power management software tools provide control over how you manage your use of electricity.
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Powerful analytical tools — software, PCs, networks, and the internet — are within a click of the mouse. Power monitoring equipment captures data; software analyzes critical data required for responsible electrical energy management.
Power management software tools provide control over how you manage your use of electricity. They enable you to renegotiate your rates, prevent costly power quality problems, identify and correct power delivery issues, and control demand to avoid penalties. State-of-the-art power monitoring technology provides consumption data as well as power-quality information.
Software functionality
Typically, power management software is offered in conjunction with associated hardware. State-of-the-art software functionality includes presentation, analysis, control, troubleshooting, and communication functions.
Presentation
Presentation functions include display and reporting features. Graphical meters, waveform displays, and trend charts are the most visible features of power management software tools. However, reports, data tables, and dynamic data exchange (DDE) features are important presentation functions as well.
DDE is a standard software characteristic found in most Windows-based programs. It makes it possible to use available data in other software applications. For example, power usage data can be brought into an Excel file, which facilitates report and graph generation. With DDE, some software programs can read, display, and save data and alarms from other applications, such as process controls or a building automation system.
Software generates reports based on historical data or real-time values using standard formats or templates included in the software. Most programs allow you to create your own. Reports may be saved in HTML format for display using an Internet browser.
Analysis
Analysis functions include load profiling; demand tracking; event, alarm, and historical data logging; and the acquisition and analysis of parametric trends and waveform captures.
Software saves historical and trend data from system devices to a central database. The data can be retrieved, displayed, or printed as tables, trends, or reports. Voltage and current waveforms may be viewed simultaneously or individually, and can be printed. Waveform captures can be analyzed to determine total harmonic distortion (THD) and the percentage of each harmonic order.
Software can link alarms to external digital and analog inputs as well as direct inputs from system devices. Alarm parameters can be set with a number of security levels.
Control
Control functions include load management, alarm annunciation, password management, system control, automated tasks, and power quality management.
Power system control manages system voltage, power factor, or harmonics. Power management systems maintain power quality by controlling load tap changers, generators, and capacitor and filter banks.
You can reduce the amplitude of your plant’s power peaks by controlling when major plant loads are brought online or taken offline. Emergency load shedding allows you to preserve critical loads or avoid total shutdown due to unforeseen loss of power sources. Typical power management software preserves system stability during sudden loss of a power source by determining system topology, evaluating remaining loads and sources, and then shedding loads.
However, load shedding can be a relatively severe practice that may differ from the needs of some plants. Using power management software, you can fine-tune your electrical system so that the load curve at the meters is relatively flat.
A better approach to load shedding would be to delay slightly the startup of multiple loads, which can be done with a power management system or machine automation. In some cases, these delays are slightly noticeable; in most cases they are not. For example, an HVAC controller does not care if the blowers are started immediately or 5 sec after the start command. No one inside the plant will notice the difference — but the electrical billing meters will notice.
Loads should be monitored and controlled so that the power to them is not cycled rapidly. This type of load timing intervention smoothes the power demand by reducing peaks and raising the valleys of the load curve.
Besides potentially reducing demand charges, a benefit to flattening the load curve is that wear on plant equipment due to excessive startups is reduced significantly. In some cases, it would be better to keep loads running instead of stopping and starting them frequently.
Software can manage electrical devices such as circuit breakers and lighting controllers automatically. Other automatic tasks include launching programs, resetting devices, sending e-mail, acquiring data, and capturing waveforms. A task may be launched when an alarm is detected or at a precise time determined by the user.
Troubleshooting
Troubleshooting functions quantify energy levels and power quality parameters (See “Power system troubleshooting). A software-based power monitoring system can help you troubleshoot malfunctions. Using real-time status information, many systems can identify correctable events to help you proactively reduce downtime. These diagnostic capabilities include:
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Verifying THD levels, which can prevent variable frequency drive (VFD) damage
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Detecting phase imbalance, which can help prevent equipment malfunction or damage
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Detecting blown power factor (PF) pacitors and fuses
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Discovering oscillatory transients (due to capacitor switching on the utility side) that can cause mysterious VFD trips
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Monitoring status and waveforms for improper motor-starting operation
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Monitoring ground currents to aid in early detection of arcing to ground, or improper neutral-to-ground bonds.
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Alarm functions facilitate maintenance because technicians cannot be in all locations at once. Software generates alarms triggered by system anomalies, power quality events, or in response to user-defined conditions.
Communication
Software can communicate with devices installed in the electrical distribution system as long as they have networking capabilities. These smart devices include power meters, circuit monitors, low-voltage circuit breakers, protection relays, and other power-related devices connected to the network. Communication connectivity allows you to view metering points on your desktop PC. Those with appropriate password authority can set and change meter configuration values remotely.
Software enables you to capture, analyze, store, and share energy data across your entire enterprise through standard web browsers. This makes it easy for you to acquire and distribute the knowledge you need to optimize energy consumption and improve productivity while lowering energy costs.
Reducing energy costs
Power monitoring software helps you track and allocate energy costs by enabling you to diagnose the causes of many electrical system problems. According to one supplier’s claim, installing a power monitoring system can save you 2%—4% initially on your energy costs. However, using software enables you to look beyond the utility bill to gain an additional 2%—5% savings through better equipment utilization and by avoiding unnecessary capital purchases. Improving power system reliability can save another 10%.
Cost allocation enables you to determine where your energy dollars go. Software measures and records energy usage to allocate energy costs by department, process, and facility. By knowing the amount of incoming electrical power, when and where it is used, and its condition, you can compare and validate these data against utility bills as well as analyze alternate energy sources or rates (Fig. 1).
Software can store and retrieve useful energy information using distributed data logging and onboard memory from metering devices. Information can be accessed over the Internet and disseminated through reports, which can be run periodically or on demand. For example, using cost allocation reports and usage trends, you can verify utility billing accuracy, distribute bills internally by department, and make effective fact-based energy decisions. Costs can be distributed according to shift, department, or product, thus directing energy cost accountability to the appropriate cost centers of your plant.
Demand management
High power peaks cause plants to pay more for electricity every month because most utilities charge a demand rate in addition to the metered energy usage (Fig. 2). Demand management features allow you to reduce demand charges and manage real-time power purchases. Typical software enables demand limiting by using peaking or cogeneration control, load interlocking, load shedding, and load trimming.
Load profiling indicates energy consumption patterns. Software-based systems measure and record energy usage to determine load factor, identify peak demand periods, and correlate consumption with plant production requirements.
Equipment utilization
A software-based power monitoring system can help you reveal bonus capacity sources and identify stressed equipment. It helps you balance loads on substations, panel boards, and other critical power distribution equipment. These quantitative insights into your plant’s electrical usage help you extend the life of your equipment and maximize your equipment investments.
Improving power quality
The quality of your electrical power affects the reliability of your equipment. Power reliability determines electrical system capacity, availability, and uptime. An ideal system would prevent electrical power disruption and equipment damage, and also provide advance warning of impending problems.
The quality (or lack thereof) of your electrical power affects your bottom line. Harmonic and transient conditions can cause equipment damage and, if left undetected, can lead to expensive downtime and lost productivity, which directly affects profitability. Problems on either side of your substation can be detected and identified by using a power monitoring system with state-of-the-art software.
Power tolerance curves
Software tools allow you to convert power quality data into an index that can be tracked over time. This power quality index (PQI) is determined based on the relationship of each recorded event to an appropriate power tolerance curve.
A power tolerance curve provides an indication of the likelihood that an event will cause an equipment failure. In other words, it measures how sensitive your equipment is to the quality of electrical power in your plant. Event magnitude and duration relationships quantify the possibility of electrical power quality events causing equipment problems.
The CBEMA curve and the newer ITIC curve quantify the sensitivity of electronic equipment (Fig. 3). Some software tools allow you to define your own curves based on the needs of your plant, equipment type, location, sensitivity, and power monitoring point (see “Using PQI for predictive maintenance”).
Power tolerance curves focus your attention on worst-case events. The software allows you to delve further into the data from which the index was derived. You can then compare and trend any parameter against any other parameter; compare data among locations; or compare one survey with another.
Predictive maintenance
Power management software provides advance warning of impending problems and enables you to prevent unnecessary downtime stemming from electrical power disruption. Using historical data, you can build predictive maintenance (PdM) models that compare and trend power quality problems such as sags, swells, harmonics, ground currents, and phase imbalance. These models enable you to build system profiles that identify overloading conditions, equipment malfunctions, electrical distribution equipment deterioration, and other stresses on the electrical system.
One way to make power management software work for you is to perform periodic surveys of your power system with PdM in mind. To develop a successful power management PdM program, begin by surveying your electrical system to establish a baseline. Then monitor your electrical system continuously to collect critical data. Compare these data to the baseline periodically. Finally, replace components or equipment when necessary and make the essential corrections, repairs, or adjustments to your equipment to maximize uptime, minimize downtime, and increase its useful life expectancy.
PLANT ENGINEERING magazine extends its appreciation to Fluke Corp.; Olson Power Trend Management, Inc.; Rockwell Automation; Siemens Energy & Automation, Inc.; and Square D/Schneider Electric for the use of their materials in the preparation of this article.
Power system troubleshooting
Generally, companies don’t look for these types of corrections until they receive a nasty utility bill. However, you can level out demand peaks by identifying and correcting trouble spots. The following list of trouble indicators is a good place to start.
Using a reliable power harmonic analyzer, check for “silver bullet” fixes such as poor power factor, harmonic distortion, phase imbalance, and overvoltage conditions. Sometimes a power tune-up is all your plant requires.
Further issues are revealed by looking at electrical utility invoices from the past 12 mo. Calculate what your plant is paying for demand, and compare that to what your flat-line demand would be by dividing the monthly energy usage by the number of hours in the month.
If there is a large difference between flat line demand and metered demand there is an opportunity for redirecting dollars toward energy — something that can be turned into finished goods or value-added services.
Examine your loads in detail and estimate how much you can reasonably expect to reduce your actual demand. In some cases, you will have to renegotiate your agreement with your utility so that the demand charge is not locked in for several months.
Evaluate your motor repair bills. If your plant has a large annual budget for motor shaft and/or rewinding work, then some loads are seeing more on/off power cycles than they should. This can drive the rms power of the motor above its rated limit. It also creates excessive core heat. If the load duty-cycle cannot be controlled without adversely affecting safety or business, then consider using a decoupling system such as a magnetic clutch, electrically operated mechanical clutch, or fluid drive. Then the motor and the load can have different duty cycles.
Source: Adapted from Olson Power Trend Management, Inc.
Using PQI for predictive maintenance
PQI is a numerical index derived by converting accumulated power-monitoring data into a quantified indicator of power quality, which can be tracked over time. Trending this index can provide advance warning of electrical system failures.
Each event is assigned a number or index, which is calculated by determining the event’s relationship to a power quality tolerance curve. Any meaningful curve can be used. But using standard electronic equipment reference curves is a good place to start. These standard reference curves are the Computer and Business Equipment Manufacturers Association (CBEMA) curve and the Information Technology Industry Council (ITIC) curve, which is proposed as being the “new” CBEMA curve.
Begin by assigning an index of 0 to the nominal voltage and an index of 100 to an event landing on the curve (Fig. A). Assign indices to other events based on the ratio of the event’s distance from the nominal voltage, to the same distance from the limits of the curve and multiply by 100. If an event is halfway between the nominal voltage and the curve, the index is 50. If an event is twice the distance from the nominal voltage as it is from the curve, the index is 200. After each event is assigned an index, calculate the mean index at regular intervals, and plot this mean over time. If the plotted value of the mean index increases, power quality is deteriorating; if it decreases, power quality is improving. This plot also indicates fluctuations.
Reshaping the curve
If the standard curve doesn’t exactly describe the sensitivity of a critical load, you can reshape it. For example, if an event’s index is less than 100 on the CBEMA curve, it could be misleading. Depending on your specific application, and therefore equipment sensitivity, the event’s index could actually be greater than 100, according to real-world performance. This event index departure from a standard curve is an indication that the curve should be reshaped.
To make PQI useful in predictive maintenance programs, look for events with indices greater than 100. The goal is to ensure that events and their indices remain below 100. Using a modified curve, you can increase its accuracy to improve its ability to help you identify events that could potentially cause electrical system failure or power disruption.
Developing your own curve
Suppose you don’t know the exact shape of the curve that quantifies the operational limits of your critical load, and suppose the standard CBEMA curve doesn’t quite fit. Furthermore, suppose that the equipment supplier can’t supply a curve either. The way to deal with this is to develop your own specific power quality tolerance curve adapted for predictive maintenance by fine-tuning a standard curve.
For example, assume your equipment is more sensitive to impulses or to high-speed transients. You should adjust the curve to be more sensitive in the microsecond region, giving the correct indices to events in the impulse region. Start with the standard CBEMA curve and note which events cause actual equipment problems. Then, modify the curve so that it correctly describes the sensitivity of your equipment.
Remember that the curve is just an overlay; it has no effect on how you capture the events. Software tools are available that allow you to modify any power quality tolerance curve at any time — even after you’ve collected data. Because these data reside in a database, you can recalculate the power quality index at any time simply by changing the curve.
Source: Adapted from Fluke Corp.
