The following points highlight the three main techniques used for measuring flicker in voltage during electricity supply. The techniques are: 1. RMS Strip Charts 2. Fast Fourier Transform 3. Flicker Meters.
Technique # 1. RMS Strip Charts:
Historically, flicker has been measured using rms meters, load duty cycle, and a flicker curve. If sudden rms voltage deviations occurred with specified frequencies exceeding values found in flicker curves, such as one shown in Fig. 5.5, the system was said to have experienced flicker.
A sample graph of rms voltage variations is shown in Fig. 5.6 where large voltage deviations up to 9.0 V rms (AV/V = ± 8.0 percent on a 120-V base) are found. Upon comparing this to the flicker curve in Fig. 5.5, the feeder would be experiencing flicker, regardless of the duty cycle of the load producing the flicker, because any sudden total change in voltage greater than 7.0 V rms results in objectionable flicker, regardless of the frequency.
The advantage to such a method is that it is quite simple in nature and the rms data required are rather easy to acquire. The apparent disadvantage to such a method would be the lack of accuracy and inability to obtain the exact frequency content of the flicker.
Technique # 2. Fast Fourier Transform:
Another method that has been used to measure flicker is to take raw samples of the actual voltage waveforms and implement a fast Fourier transform on the demodulated signal (flicker signal only) to extract the various frequencies and magnitudes found in the data. These data would then be compared to a flicker curve.
Although similar to using the rms strip charts, this method more accurately quantifies the data measured due to the magnitude and frequency of the flicker being known. The downside to implementing this method is associated with quantifying flicker levels when the flicker- producing load contains multiple flicker signals. Some instruments compensate for this by reporting only the dominant frequency and discarding the rest.
Technique # 3. Flicker Meters:
Because of the complexity of quantifying flicker levels that are based upon human perception, the most comprehensive approach to measuring flicker is to use flicker meters. A flicker meter is essentially a device that demodulates the flicker signal, weights it according to established “flicker curves,” and performs statistical analysis on the processed data. Generally, these meters can be divided up into three sections. In the first section the input waveform is demodulated, thus removing the carrier signal.
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As a result of the demodulator, a dc offset and higher-frequency terms (sidebands) are produced. The second section removes these unwanted terms using filters, thus leaving only the modulating (flicker) signal remaining. The second section also consists of filters that weight the modulating signal according to the particular meter specifications. The last section usually consists of a statistical analysis of the measured flicker.
The most established method for doing this is described in IEC Standard 61000- 4-15.8 .The IEC flicker meter consists of five blocks. Block 1 is an input voltage adapter that scales the input half-cycle rms value to an internal reference level. This allows flicker measurements to be made based upon a percent ratio rather than be dependent upon the input carrier voltage level.
Block 2 is simply a squaring demodulator that squares the input to separate the voltage fluctuation (modulating signal) from the main voltage signal (carrier signal), thus simulating the behavior of the incandescent lamp. Block 3 consists of multiple filters that serve to filter out unwanted frequencies produced from the demodulator and also to weight the input signal according to the incandescent lamp eye-brain response.
The basic transfer function for the weighting filter is:
Block 4 consists of a squaring multiplier and sliding mean filter. The voltage signal is squared to simulate the nonlinear eye-brain response, while the sliding mean filter averages the signal to simulate the short-term storage effect of the brain. The output of this block is considered to be the instantaneous flicker level. A level of 1 on the output of this block corresponds to perceptible flicker. Block 5 consists of a statistical analysis of the instantaneous flicker level. The output of block 4 is divided into suitable classes, thus creating a histogram. A probability density function is created based upon each class, and from this a cumulative distribution function can be formed.
Flicker level evaluation can be divided into two categories, short-term and long- term. Short-term evaluation of flicker severity PST is based upon an observation period of 10 min. This period is based upon assessing disturbances with a short duty cycle or those that produce continuous fluctuations. PST can be found using the equation-
Where, the percentages P0.1, P1s, P3s, P10s, and P50s are the flicker levels that are exceeded 0.1, 1.0, 3.0, 10.0, and 50.0 percent of the time, respectively. A PST of 1.0 on the output of block 5 represents the objectionable (or irritable) limit of flicker.
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For cases where the duty cycle is long or variable, such as in arc furnaces, or disturbances on the system that are caused by multiple loads operating simultaneously, the need for the long-term assessment of flicker severity arises. Therefore, the long- term flicker severity PLT is derived from PST using the equation-
Where, N is the number of PST readings and is determined by the duty cycle of the flicker-producing load. The purpose is to capture one duty cycle of the fluctuating load. If the duty cycle is unknown, the recommended number of PST readings is 12 (2-h measurement window).
The advantage of using a single quantity, like P , to characterize flicker is that it provides a basis for implementing contracts and describing flicker levels in a much simpler manner. 24-h period. The melt cycles when the furnace was operating can be clearly identified by the high Pst levels. Note that Pst levels greater than 1.0 are usually considered to be levels that might result in customers being aware of lights flickering.