EPQU

Magazine

Electrical Power Quality & Utilization Magazine Volume 3, Issue 2

Daniel Kottick, Israel Electric Corp.

Available online August 2008

Power Quality Monitoring System— Voltage Dips, Short Interruptions and Flicker

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Abstract

The Israel Electric corp. deployed a nationwide Power Quality Monitoring System (PQMS). The PQMS monitors the quality of supply of all of its high voltage costumers, as well as a sample of its medium voltage customers. The PQMS monitors both the voltages and the currents. The PQMS has been operational since October 2005. The paper presents preliminary measurement results obtained from the PQMS.

1. Introduction

In recent years, Power Quality (PQ) assessment and improvement has been attracting a growing amount of attention, as the standard of living increases, and as a result of the growing dependency on a reliable and continuous supply of electricity [1]. The cost of damages caused by PQ events has become significantly higher than in the past, because of the increased usage of electronic equipment in the industrial and commercial sectors [2, 3, 4].

Semiconductor switching devices are being utilized for a wide range of applications in the domestic, commercial and industrial sectors. These devices offer economical solutions for the optimized use of electrical energy. However, they have nonlinear characteristics, and thus cause disturbances to the voltage and current waveforms. At the same time, semiconductor devices are sensitive to PQ problems.

For the last few years, PQ has become an increasingly important issue. Some electric companies worldwide have initiated monitoring systems and have begun tackling PQ related problems [5, 6]. When tackling PQ problems, there are two main approaches: The first deals with the planning and manufacturing of electrical equipment, which is designed and manufactured according to standards that ensure that it is less sensitive to PQ events [7]. The second approach involves the installation of mitigation equipment that depends on the characteristics of the protected device. The costumer usually buys the mitigation equipment. The most commonly used mitigation equipment is the Uninterruptible Power Supply (UPS).

The Israel Electric corp. deployed a nationwide Power Quality Monitoring System (PQMS). The PQMS monitors the quality of supply of all of its high voltage costumers, as well as a sample (200 measuring points) of its medium voltage customers [8]. The PQMS monitors both the voltages and the currents. The PQMS has been operational since October 2005.

This paper presents preliminary measurement results. A large majority of customer complaints regarding power quality focus on short interruptions and voltage dips. A statistical analysis of the latter phenomena is presented. In order to demonstrate the ability of the PQMS to serve as an investigation tool a specific event of flicker caused by a metal processing plant is introduced.

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2. Definitions

This section summarizes the definitions and causes of the PQ phenomena that are dealt with in this paper.

2.1 Voltage Dips

A typical voltage dip, as measured by the PQMS, is presented in Figure 1. The voltages of the PQMS are measured at the secondary coil of the billing transformer (22 kV / 0.110 kV).

Figure 1 – Typical voltage dip.

The main causes of voltage dips are: short-circuits in the supply network, start-up of large loads, faulted grounding system and failures of the customer facilities.

Aggregation of Voltage Dips

A voltage dip may refer to one phase, two or three phases. A three phase voltage dip can be symmetrical or asymmetrical. Aggregation of voltage dips is sometimes performed in order to represent it according to two parameters: duration and depth.

A method of three phase voltage dip aggregation is presented in Figure 2. The dip starts when the voltage of the first phase drops bellow a certain point and ends when the last phase recovers (in Figure 2 Δt = t6—t1). The dip depth is defined as the maximum of the three values of the different phases (in Figure 2 ΔV = max[ΔV1, ΔV2, ΔV3])

If several dips occur in a relatively short time frame, for example two dips that are caused by a short-circuit in the supply network that is not cleared after the first re-closing of the current breaker, a second aggregation step may be performed. A series of two dips is presented in Figure 3.

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Figure 2 – Aggregation of a three phase voltage dip.

Figure 3 – Multiple voltage dips.

The second step of the aggregation is performed if ΔT < T (for example T=1 sec.). The parameters that describe the aggregated event are: depth ΔV = max[ΔV1, ΔV2] and duration:

(1) Δt = t4—t1,

(2) Δt = max[(t2—t1)(t4—t3)],

(3) Δt = (t2—t1)+(t4—t3).

2.2 Short Interruptions

An interruption of a medium voltage customer as measured by the PQMS is presented in Figure 4. The voltages of the PQMS are measured at the secondary coil of the billing transformer (22 kV / 0.110 kV). According to the definitions used by IEC a short interruption lasts less than 3 min. The Figure represents only the first few cycles following the interruption and the first few cycles after the voltage restoration. The main causes for short interruptions are: short-circuits in the supply network and malfunction of customer facilities.

t1 t2

∆V1

t3 t4

∆V2

t5 t6

∆V3

∆V t1 t6

t1 t2 t3 t4

∆V1 ∆V2 ∆T

3 phase voltage dip

Aggregated voltage dip

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Figure 4 – Interruption of a M.V. customer (the first few cycles following the interruption and the first few cycles after the voltage restoration).

2.3 Flicker

Figure 5 presents flicker fluctuating voltage and its spectrum.

Figure 5 – Voltage flicker, a. voltage fluctuations, b. spectrum.

The main causes of flicker are the following loads: pulsed power output where there is burst-firing control, arc furnaces, drives with steeply changing loading etc.

The assessment of the flicker level is based on human response to voltage fluctuations and its influence on illumination systems.

3. Power Quality Monitoring in Israel

The Israel Electric Corp. (IEC) has deployed a Power Quality Monitoring System (PQMS), which was purchased from TeamWare s.r.l. - Italy. The PQMS consists of 200 monitoring units (Figure 6) connected to the points of common coupling of 200 medium voltage customers (the IEC has app. 2800 medium voltage customers), as well as 30 monitoring units measuring high voltage customers.

-200-100

0100200

-20 30 80

Time [mSec.]

Volta

ge

-200

-100

0

100

200

Time [mSec.]

Volta

ge

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Figure 6 – Power quality monitoring unit.

At the time when the IEC decided to deploy its PQMS it had limited knowledge on the statistical distribution of the power quality indices. In the past the IEC gathered data on short interruptions of medium voltage distribution lines (not customers). The determination of the sample size of the PQMS was based on analyzing this data. The sample size was determined according to the following equation:

Where:

N - Population size.

n - Sample size.

S2 - Disturbance variance.

- Disturbance average.

d - Error ratio.

In order to estimate the average number of short interruptions per power line and year with an error of up to 20% the sampling size should be (N=1063 power lines, S=9.4,

X=5, d= 0.2, Z=1.7):

( )2

22

2

ZXd

NS

Sn+

=

X

206

7.11

10634.9

4.9

22

2

=+

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The IEC decided to use this result for its PQMS size.

Each monitoring unit is equipped with local memory, capable of storing data complying with EN50160. The data is then transferred via cellular communication to a central database. All the monitoring units are equipped with a GPS card in order to synchronize their time stamps.

A schematic layout of the PQMS is presented in Figure 7.

Figure 7- Schematic layout of the PQMS.

The PQMS consists of several layers:

The PQMS has been fully operational since October 2005.

Prepared by: Information Systems & Communications division

Communication computer for data collection

Database software

Managing software

Client software

Database

Communication computer for data collection

direct TCP/IP connection for data

transfer

Cellular network

Field unit Field unit

Internal IEC network communication

Prepared by: Information Systems & Communications division

Communication computer for data collection

Database software

Managing software

Client software

Database

Communication computer for data collection

direct TCP/IP connection for data

transfer

Cellular network

Field unit Field unit

Internal IEC network communication

Computers

- Users, managers, a data acquisition server and a communication server

Communication

- TCP/IP communication for data transfer.

Monitoring units

- Installed at the point of common coupling of medium voltage consumers. Each monitoring unit is equipped with

a GPS card for time synchronization.

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4. Short Interruptions and Voltage Dips

This section presents data regarding short interruptions and voltage dips during a one year period from June 2005 to June 2006. At that time, the PQMS was composed of 122 monitoring units that were operational during the whole period. A distribution of the number of voltage dips per customer during the one year period is presented in Figure 8.

Figure 8 – Distribution of the number of voltage dip per customer and year.

Each point in Figure 8 represents the average number of voltage dips per customer for each month. The graph also includes a tendency curve. The tendency curve is a fourth order polynomial function that approximates the measured number of dips with a minimum means square error. One can observe that most voltage dips occur during the winter months (October-February). The rain in Israel appears only during winter period while the summers are dry. Contamination on insulators built up during the summer and the rain causes flashovers that cause voltage dips. The average number of voltage dips per customer per year was 87.

The distribution of voltage dips according to time is presented in Figure 9.

Figure 9 – Distribution of the number of voltage dip per customer and day.

Distribution of Voltage Dips

02468

101214

May-05

Jul-05

Sep-05

Oct-05

Dec-05

Feb-06

Mar-06

May-06

Jul-06

Num

ber o

f Vol

tage

Dip

s

Distribution of Voltage Dips

01234567

0 5 10 15 20

Time [Hour]

Num

ber o

f Vol

tage

Dip

s

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Each point in Figure 9 represents the average number of voltage dips per customer during periods of one hour; the graph also includes tendency curve. The tendency curve is a fourth order polynomial function that approximates the measured number of dips with a minimum means square error. One can observe that most voltage dips occur during the night hours, probably because the relative humidity during nigh-hours is higher than that of day-hours.

A distribution of the number of short interruptions per customer during the one year period is presented in Figure 10.

Figure 10 – Distribution of the number of short interruptions per customer and year.

Each point in Figure 10 represents the average number of short interruptions per customer for each month, the graph also includes tendency curve. The tendency curve is a fourth order polynomial function that approximates the measured number of dips with a minimum means square error. One can observe that most short interruptions occur during the winter months (October-February). The average number of short interruptions per customer per year was 5.7.

The distribution of short interruptions according to time is presented in Figure 11.

Figure 11 – Distribution of the number of short interruptions per customer and day.

Distribution of Short Interruptions

00.10.20.30.40.50.60.70.8

May-05

Jul-05

Sep-05

Oct-05

Dec-05

Feb-06

Mar-06

May-06

Jul-06

Num

ber o

f Sho

rt In

terr

uptio

ns

Distribution of Short Interruptions

00.10.20.30.40.50.60.7

0 10 20

Time [Hour]

Num

ber o

f Sho

rt

Inte

rrup

tions

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5. Flicker Event

On December 17, 2006 a flicker event was caused by a high-voltage metal processing plat. Figure 12 presents the Pst parameter and the minimal voltage during the event period.

Figure 12 - Pst parameter and the minimal voltage during the event period.

During the event the flicker level reached Pst=1.7, this rise in the flicker level was accompanied by a power consumption rise as can be seen in Figure 13. One can notice the high correlation between the power consumption changes and the flicker level.

minimal voltage

40.0045.0050.0055.0060.0065.0070.0075.0080.00

17/12/200600:00:00

17/12/200610:00:00

17/12/200620:00:00

18/12/200606:00:00

18/12/200616:00:00

Flicker

0.00

0.50

1.00

1.50

2.00

17/12/200600:00:00

17/12/200610:50:00

17/12/200621:40:00

18/12/200608:30:00

18/12/200619:20:00

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Figure 13 – Flicker and power consumption.

Figure 14 presents flicker levels during the event as measured at some other high-voltage customers.

Figure 14 - Flicker levels during the event as measured at some high-voltage customers.

Flicker

0.000.200.400.600.801.001.201.401.601.802.00

17/12/200600:00:00

17/12/200610:00:00

17/12/200620:00:00

18/12/200606:00:00

18/12/200616:00:00

Pow er consumption

0.00

100.00

200.00

300.00

400.00

500.00

17/12/200600:00:00

17/12/200610:00:00

17/12/200620:00:00

18/12/200606:00:00

18/12/200616:00:00

0.00

0.50

1.00

1.50

2.00

17/12/2006 18:00:00 17/12/2006 18:50:00

Flic

kr

Metal Plant Cust. I Cust. II

Cust. III Cust. IV

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One can notice that the flicker event that was caused by the metal plant was spread through the network and influenced other customers.

6. Conclusions

Power quality problems constitute a growing concern, as electricity consumption becomes more and more vulnerable to distortions of the sinusoidal voltage and current waveforms. A distorted waveform can cause malfunction of electronic equipment and electrical control systems. It is therefore important to monitor the quality of the electric power supply and to mitigate it according to international standards.

The paper described the power quality monitoring system installed in Israel, and presented the following one year measuring results:

• The Distribution of voltage dips during a one-year period was analyzed. An M.V. customer suffered on average 87 voltage dips, most of which occurred during the winter months (October-February).

• The distribution of voltage dips according to time was analyzed. Most voltage dips occurred during the night hours.

• The Distribution of short interruptions during a one-year period was analyzed. An M.V. customer suffered on average 5.7 short interruptions, most of which occurred during the winter months (October-February).

• The distribution of short interruptions according to time was analyzed. Most short interruptions occurred during the morning hours.

• A Flicker event caused by a metal processing plant was presented and analyzed.

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References

1. Bendre, D. Divan, W. Kranz and W. Brumsickle, " Equipment Failures Caused by Power Quality Disturbances", Industry Applications Conference 2004, 39th Annual Meeting, 3-7 Oct. 2004, pp. 482-489, 2004.

2. S. Z. Djokic and J. V. Milanovic, "Power Quality and Compatibility Levels: A General Approach", IEEE Transactions on Power Delivery, Vol. 22, pp. 1857-1862, 2007.

3. E. Styvaktakisand and M.H.J. Bollen, "Signatures of Voltage Dips: Transformer Saturation and Multistage dips", IEEE Transactions on Power Delivery, Vol. 18, pp. 265-270, 2003

4. M. McGranaghan and B. Roettger, “Economic Evaluation of Power Quality”, IEEE Power Engineering Review, Vol.22, No. 2, pp. 8-12, 2002.

5. T. Radil, P. M. Ramos, F. M. Janeiro and A. Cruz Serra, "PQ Monitoring System for Real-Time Detection and Classification of Disturbances in a Single-Phase Power System", IEEE Transactions on Instrumentation and Measurement, Vol. 57, pp. 1725-1733, 2008.

6. D. S. Dorr, M. B. Hughes, T. M. Gruzs, R. E. Juewics and J. L. McClaine, “Interpreting Recent Power Quality Surveys to Define the Electrical Environment”, IEEE Trans. On Industrial Applications, Vol. 33, pp. 1480-1487, 1997.

7. ITI (CBEMA) Curve Application Note http://www.itic.org/technical/iticurc.pdf (online).

8. D. Won and S. Moon, "Optimal Number and Locations of Power Quality Monitors Considering System Topology", IEEE Transactions on Power Delivery, Vol. 23, pp. 288-295, 2008.