Using IEEE 1346 To Combat Voltage Sags

A look at the details. First, turn the interruption or sag event into a statistical plot. Fig. 1 (click here to see Fig. 1) depicts such a plot, taken from a hypothetical site that is served by a local electric utility. All events in the light blue area have an equal chance of occurrence. A voltage sag down to 80% of normal that lasts 20 cycles has the same chance of occurring as one down to 30% of nominal voltage and lasts two cycles. Also, note that most events end in 15 cycles.

Likewise, you can characterize sensitive electronic equipment by noting how much of a reduced voltage it will still operate on as well as how long it can ride through an electrical disturbance. You can identify these characteristics in a susceptibility chart, a sample of which is shown in Fig. 2 (click here to see Fig. 2). Any event longer and deeper than the dropout box boundaries shown will inevitably cause problems.

Overlaying the dropout boundaries in Fig. 2 on top of Figure 1 reveals Fig. 3 (click here to see Fig. 3). The star on the graph indicates voltage sags will cause the sample 24V (output) power supply, which serves a critical control device, to produce five to 10 process shutdowns per site per year.

The next step is to predict the cost of the process interruptions for the year. You can then approximate the cost of using this power supply in your process equipment. Once you can predict the cost of an interruption to your process, you can determine what investment options are best for voltage sag ride-through.

Consider one key point: The testing of specific sensitive equipment. This testing should relate to susceptibility of malfunction from the effects of single-, 2-, and 3-phase sags, phase shifting, and point-on-wave transition angles. And since most electronic equipment achieves its voltage sag performance by capacitive energy (based on the peak sine wave value), these effects can be multiplied. For instance, a peak voltage depression of 10% will result in a 20% loss in energy storage capability, which translates into a lessening of voltage sag performance of the affected equipment.

Getting voltage sag activity. To find the probability of a sag's impact on your equipment, you should request voltage-sag characteristic plots for your site from your electric utility. Also ask the manufacturer of any sensitive electronic equipment for plots on equipment susceptibility to sags. After adjusting the two charts so they have the same scale, lay one over the other to observe where impacts occur.

Your electric utility may not have voltage sag information, especially for specific areas of its service territory. Instead, you may have to rely on sag information from actual measurements, predicted performance, or "typical" data. Nevertheless, you'll need reasonably accurate data for a good financial analysis.

Actual measured voltage information for the facility gathered over several years is accurate, as long as the supply system won't change significantly in the future. However, some electric utility engineers believe several years can be too short. Even specific data gathered by the utility varies somewhat for each year, each season, and each location. Voltage level and other factors will also influence data. Making projections from history may not be any more accurate than using typical data, since many electric utilities frequently reconfigure distribution circuits.

Where to measure sags is important. Electric utility data—when provided—may be measured at the utility connection to your facility, at the utility’s substation, or at a nearby site. As such, the sensitive equipment inside your plant might not see the same sag levels as those at the utility feed. Therefore, your best approach is to measure sag data as close to the actual feed of the proposed equipment as possible. If you don't have actual location data, you'll have to use your best judgment from the data you can obtain.

If measured data isn't available, you can install monitors and collect the necessary sag data. In such a situation, the longer you collect it, the more reliable the data will be. You can find information on recommended methods and suggested equipment to collect power quality data in IEEE 1159-1995, Recommended Practice for Monitoring Electric Power Quality.

The biggest influence on the frequency of sags is weather. A year with above average storms can significantly skew the data. Therefore, it may take a number of years of accumulated data to obtain an accurate picture of sag conditions at your site.

Predictive techniques use historical power failure rates to estimate the supply sag characteristics. IEEE 493-1997, Recommended Practice for the Design of Reliable Industrial and Commercial Power Systems (The Gold Book), provides guidance on predictive techniques for voltage sags. Such techniques allow you to analyze a variety of scenarios, while providing a means to estimate performance at new sites where there's no historical sag data. Predictive techniques may be helpful but in almost all cases, local electric utility data—if available—is more likely to be correct.

Without measured data and where lack of time or information precludes predictive analysis, you can use example data, such as someone else's electric utility sag data, national data, or other site data. Although this type of data doesn't establish a particular electric utility's service reliability levels, it does represent a sample of power system performance data.

Acknowledgment. We wish to recognize contributions made by members of IEEE Working Group 1346 toward the development of this standard. Special credit goes to Van E. Wagner, staff power quality engineer, Square D Co., who served as chairman of the Working Group; and Larry E. Conrad, manager of operations engineering/power quality, Cinergy Corp., who served as chairman of Chapter 9 of IEEE 493-1997 (The Gold Book).

Sidebar: Understanding the Standard's Methodology

IEEE1346-1998 doesn’t intend to set performance criteria for electric utility systems, power distribution systems, or electronic process equipment. Instead, it shows how you can use the performance data for each of these to evaluate their compatibility as a system, in financial terms. The recommended methodology also provides standardization of methods, use of data, and analysis of power systems and equipment in evaluating compatibility within a common frame of reference.

You should apply the methodology at the planning or design stage of a project, when power supply and equipment choices are still flexible. The cost of trying to fix an incompatible system after equipment installation is more expensive than addressing the issue during the planning stage of a project—before specifying equipment. As such, this document doesn’t discuss troubleshooting or correcting existing power quality problems.

This standard also doesn’t discuss technical options to improve compatibility. Instead, references and bibliographic listings in the standard provide detailed discussions of alternative methods. The corrective alternatives are so numerous and the sensitive equipment affected by voltage sags so specific that such a listing would detract from the basic purpose of the document, which is to plan for compatibility.