Rms Variation Indices and Its Applications | Electrical Engineering

For many years, the only indices defined to quantify rms variation service quality were the sustained interruption indices (SAIFI, CAIDI, etc.). Sustained interruptions are in fact only one type of rms variation.

IEEE Standard 1159-19957 defines a sustained interruption as a reduction in the rms voltage to less than 10 percent of nominal voltage for longer than 1 min.

Sustained interruptions are of great importance because all customers on the faulted section are affected by such disturbances.

Indices for evaluating them have been in use informally by utilities for many years and were recently standardized by the IEEE in IEEE Standard 1366-1998.

The standard also defines indices quantifying momentary interruption performance, which quantifies another very important type of rms voltage variation.

Momentary interruptions are due to clearing of temporary faults and the subsequent reclose operation. While they are not captured in the traditional reliability indices, they affect many end-user classes. The rms voltage variation indices take this one step farther and define metrics for voltage sags, which can also affect many end users adversely.

Characterizing RMS Variation Events:

IEEE Standard 1159-19957 provides a common terminology that can be used to discuss and assess rms voltage variations, defining magnitude ranges for sags, swells, and interruptions. The standard suggests that the terms sag, swell, and interruption be preceded by a modifier describing the duration of the event (instantaneous, momentary, temporary, or sustained).

RMS variations are classified by the magnitude and duration of the disturbances. Therefore, before rms variation indices can be calculated, magnitude and duration characteristics must be extracted from the raw waveform data recorded for each event.

Characterization is a term used to describe the process of extracting from a measurement useful pieces of information which describe the event so that not every detail of the event has to be retained.

Characterization of rms variations can be very complicated.

It is structured into three levels, each of which is identified as a type of event as follows:

i. Phase or component event

ii. Measurement event

iii. Aggregate event

i. Component Event Level:

Each phase of each rms variation measurement may contain multiple components. Most rms variations have a simple rectangular shape and are accurately characterized by a single magnitude and duration. Approximately 10 percent of rms variations are non-rectangular and have multiple components. It exhibits a voltage swell followed by two levels of voltage sag. This event was the result of clearing a temporary single-line-to-ground fault that evolved into a double- line-to-ground.

Phase A Voltage fault before the breaker tripped. The breaker then reclosed successfully in about 0.2 s. Note that only about 10 cycles of the initial voltage swell are shown in the waveform plot on the bottom. The entire event lasted nearly 1.5 s, although the instrument reports only the duration of the voltage swell. Other software is required to post process the waveform off-line to determine the other characteristics of this event.

ii. Measurement Event Level:

A power system occurrence such as a fault can affect one, two, or all three phases of the distribution system. The magnitude and duration of the resulting rms variation may differ substantially for different phases. A determination must be made concerning how to report three-phase measurement events. For an assessment of single-phase performance, each of the three phases are reported separately.

Thus, for some faults, three different rms variations are included in the indices. This will be inappropriate for loads that see this as a single event.

The method defined here for characterizing measurement events is a three-phase method. A single set of characteristics are determined for all affected phases. For each rms variation event, the magnitude and duration are designated as the magnitude and duration of the phase with the greatest voltage deviation from nominal voltage.

iii. Aggregate Event Level:

An aggregate event is the collection of all measurements associated with a single power system occurrence into a single set of event characteristics. For example, a single distribution system fault might result in several measurements as the overcurrent protection system operates to clear the faults and restore service. An aggregate event associated with this fault would summarize all the associated measurements into a single set of characteristics (magnitude, duration, etc.).

While there may be many individual events, many end-user devices will trip or misoperate on the initial event. The succeeding rms variations have no further adverse effect on the end-user process. Thus, aggregation provides a truer assessment of service quality. RMS variation performance indices are usually based on aggregate events.

A good method of aggregating measurements is to consider all events that occur within a defined interval of the first event to be part of the same aggregate event. One minute is a typical time interval, which corresponds to the minimum length of a sustained interruption. The magnitude and duration of the aggregate event are determined from the measurement event most likely to result in customer equipment failure.

This will generally be the event exhibiting the greatest voltage deviation.

RMS Variation Performance Indices:

The RMS variation indices are designed to assess the service quality for a specified circuit area. The indices may be scaled to systems of different sizes. They may be applied to measurements recorded across a utility’s entire distribution system resulting in SAIFI-like system averages, or the indices may be applied to a single feeder or a single customer PCC.

There are many properties of rms variations that could be useful to quantify— properties such as the frequency of occurrence, the duration of disturbances, and the number of phases involved. Many rms variation indices were defined in the EPRI RBM project to address these various issues. Space does not permit a description of all of these, so we will concentrate on one index that has, perhaps, become the most popular. The papers and reports included in the references contain details on others.

SARFI for the EPRI DPQ Project of RMS Variation:

The statistics for various forms of SARFI computed for the measurements taken by the EPRI DPQ project. These particular values are rms variation frequencies for substation sites in number of events per 365 days. One-minute temporal aggregation was used, and the data were treated using sampling weights. This can serve as a reference benchmark for distribution systems in the United States.

Example of RMS Variation Index Computation Procedure :

This example is based on actual data recorded on one of the feeders monitored during the EPRI DPQ project. This illustrates some of the practical issues involved in computing the indices.

First, one must know how many customers experience a voltage exceeding the index threshold for each rms variation that occurs.

Obviously, every customer will not be individually monitored. Consequently, one must approximate the voltage experienced by each customer during a disturbance. This is accomplished by segmenting the circuit into small areas across which all customers are assumed to experience the same voltage. Obviously, the smaller the segments, the better the approximation.

One method of determining voltages for many circuit segments based on a limited number of monitoring points is power quality state estimation.

Such state estimation requires a moderately detailed circuit model and known monitored data. Without the pseudo-measurements provided by state estimation, the number of physical monitoring locations becomes the number of constant-voltage segments upon which the indices that are calculated. This is referred to as monitor- limited segmentation (MLS) and results in only a few segments per circuit. Although the calculated index values are less accurate, MLS still yields indices that are informative.

Utility Applications of RMS Variation:

Utilities are using the discussed rms variation indices to improve their systems. One productive use of the indices is to compute the separate indices for individual substations as well as the system index for several substations. The individual substation values are then compared to the system value. Those substations that exhibit significantly poor performance as compared to the system performance are targeted for maintenance efforts.

Based on the sensitivity and needs of the customers served from the targeted substations, the economic viability of potential mitigating actions is assessed. The indices have also proven to be excellent tools for communicating performance of the power delivery system in a simplified manner to key industrial customers.