**6. Interharmonic source determination case study #1**

The case study presented in this section illustrates the worst known effect of the interharmonics at present, which is the interference with control signals at the power line. The Automatic Meter Reading devices (AMR) of a utility company of the province of Alberta had experienced difficulties to receive inbound signals in a large oilfield extraction area. Utility engineers suspected that this interference could be caused by the presence of interharmonics. Field measurements were carried out at the substation feeder and at large customers that were suspected to be interharmonic polluters. The arrangement for the field measurement is shown in Fig. 10. The measured feeder supplies three customers, codenamed Customer 1, Customer 2 and Customer 3. These customers operate large oil extracting drives. The measurements were done through potential transformers and current transformers (PTs and CTs). The data were acquired for a period of two days, taking automatic snapshots of 5 seconds at every minute. The hardware utilized was a National Instruments NI-DAQ6020E, which operates at 100kb/s and has 8-channel capability. With this sampling rate, the recorded waveforms contained 256 points per cycle.

Fig. 10. Field measurement locations at the measured area

After processing all data snapshots taken at the four locations, a spectrum contour plot measured at the feeder is drawn in order to obtain the frequencies of the interharmonic components that are present in this system. Fig. 11 shows the contour plot of the data recorded at the feeder during one of the measured days. From this figure, it can be seen that there are four dominant interharmonic components, which seem to be two pairs: at around 228 Hz and 348 Hz, and 264 Hz and 384 Hz. These components drift a little in frequency due to the change of the drive operation conditions, but they exist inside a narrow frequency range.

The case study presented in this section illustrates the worst known effect of the interharmonics at present, which is the interference with control signals at the power line. The Automatic Meter Reading devices (AMR) of a utility company of the province of Alberta had experienced difficulties to receive inbound signals in a large oilfield extraction area. Utility engineers suspected that this interference could be caused by the presence of interharmonics. Field measurements were carried out at the substation feeder and at large customers that were suspected to be interharmonic polluters. The arrangement for the field measurement is shown in Fig. 10. The measured feeder supplies three customers, codenamed Customer 1, Customer 2 and Customer 3. These customers operate large oil extracting drives. The measurements were done through potential transformers and current transformers (PTs and CTs). The data were acquired for a period of two days, taking automatic snapshots of 5 seconds at every minute. The hardware utilized was a National Instruments NI-DAQ6020E, which operates at 100kb/s and has 8-channel capability. With

**6. Interharmonic source determination case study #1** 

this sampling rate, the recorded waveforms contained 256 points per cycle.

Fig. 10. Field measurement locations at the measured area

range.

After processing all data snapshots taken at the four locations, a spectrum contour plot measured at the feeder is drawn in order to obtain the frequencies of the interharmonic components that are present in this system. Fig. 11 shows the contour plot of the data recorded at the feeder during one of the measured days. From this figure, it can be seen that there are four dominant interharmonic components, which seem to be two pairs: at around 228 Hz and 348 Hz, and 264 Hz and 384 Hz. These components drift a little in frequency due to the change of the drive operation conditions, but they exist inside a narrow frequency

Fig. 11. Contour plot of the interharmonic data recorded at the feeder

The active power index was monitored at the three loads. This is shown in Fig. 12-Fig. 15. The system was observed to be fairly balanced, and therefore only the power in phase A is shown. By looking into these figures, one would conclude that Customer 2 is the source of interharmonics 228Hz, 348Hz and 384Hz, whereas Customer 3 is the source of interharmonics 264Hz and 348Hz. As explained in equation (2), it is almost impossible that an interharmonic component is generated by two sources at the same time. Furthermore, after deeper investigation, it is shown that this apparent identification of the interharmonic polluters is incorrect, and the reliability criteria proposed in this chapter is useful in aiding the researcher to drawing correct conclusions.

Fig. 12. Active power at the loads for *fIH = 228Hz* 

On the Reliability of Real Measurement Data for Assessing Power Quality Disturbances 83

The first step to utilize the reliability criteria is to obtain the percentage of snapshots containing measurements with energy levels above the quantization error. This result for the case study is shown in Table 1. According to this criterion, the interharmonic currents measured at the feeder may be unreliable because they are too low as compared to the current fundamental component. This fact does not mean that the measured interharmonics are harmless, but simply that 12 bits of the data acquisition device are not enough to accurately measure their magnitudes. As for the loads, all data are reliable, except those of

> **IH freq (Hz) Feeder Customer 1 Customer 2 Customer 3**  228 0.00 19.44 100.00 91.84 264 0.00 0.00 77.19 81.63 348 0.00 0.00 3.51 0.00 384 0.00 100.00 100.00 100.00

The interharmonic voltage-current correlation for all the locations is calculated as well, and shown in Table 2. The results obtained for the feeder show that its measurements may not reliable. For the loads, it can be seen that the correlation is generally high, except for that of

> **IH freq (Hz) Feeder Customer 1 Customer 2 Customer 3**  0.68 0.98 0.96 0.98 0.31 0.96 0.59 0.92 0.55 0.96 0.92 0.96 0.77 0.99 0.98 0.97

The other reliability criteria are also used but do not add much information to the conclusions to be drawn in Table 3, which summarizes the reliability at each frequency for

> **IH freq (Hz) Feeder Customer 1 Customer 2 Customer 3**  No Yes Yes Yes No No No Yes No No Yes No No Yes Yes Yes

Table 4 shows the average of calculated active power at the feeder and at the loads (phase

A). Note that the shaded cells are the ones that should not be trusted.

Table 1. Percentage of Snapshots with Energy Level Higher than Quantization Step

**6.1 Applying the reliability criteria** 

Customer 3 at 348 Hz.

Customer 2 at 264 Hz.

each location.

Table 2. *V-I* Correlation Coefficient (%)

Table 3. Reliability Summary

Fig. 13. Active power at the loads for *fIH = 264Hz* 

Fig. 14. Active power at the loads for *fIH = 348Hz* 

Fig. 15. Active power at the loads for *fIH = 384Hz* 
