Principal Research Results

Development of Analytical Software to Predict Influence ofVoltage Dips by Lightning Faults
Background
With the widespread use of high-tech load equipment which is very sensitive to power quality in recent years, there is growing concern regarding the possible adverse influence of momentary voltage dips lasting for several tens to more than one hundred milli-seconds, mainly caused by lightning faults with transmission lines, on such load equipment.
There are basically two types of measure to these voltage dips: (i) clarification of the situation of voltage drop at each load
point due to these dips and (ii) introduction of an equipment to avoid voltage dips. One presumably effective method for the former isthe computation of the influence of voltage dips (scale and frequency of the occurrence of voltage drops) at each load point of thepower supply system based on the probability of lightning faults with transmission lines.
At present, however, the accuracy of estimation method regarding such computation is low and an analytical technique topredict voltage dips, which is easy to use, has not yet been developed.

Objectives
To develop a highly accurate analytical technique to predict voltage dips caused by various lightning faults with probabilities on the standard parallel 2 circuits in Japan, and then to develop an analytical computation software based on that technique.

Principal Results
1. Development of Highly Accurate Analytical Technique for Voltage Dips
The analytical technique already developed ＊ 1 by the CRIEPI was further extended to develop a highly accurate as well as
high speed computing technique for voltage dips at load points caused by lightning faults with the respective transmission lines. The
main characteristics of this newly developed technique are described below (Fig. 1).
(1) A total of all 12 types of lightning fault pattern, which can emerge with the parallel 2 circuits shown in the top right of Fig. 1, canbe computed.
(2) Computation is possible for multiple faults on the transmission route in addition to the conventional node end faults (sending endand receiving end) so that the accuracy of the computation results can be improved.
(3) To efficiency compute multiple voltage dips caused by entire transmission faults at the target load points (ds), a technique capableof producing solutions in higher speed in the order of two digits or so without losing computing accuracy by using the sensitivity
coefficient between each fault point and the load point d has been developed.
2. Development of Analytical Software to Predict Voltage Dips
An analytical software based on the new analytical technique described above has been developed. Its main characteristics
are listed below (Fig. 2).
(1) The software is configured for computation using existing standard input data for power system analysis owned by each electriccompany (CRIEPI Transient Stability Simulation Software). Users can compute multiple voltage dips only by adding transmission
fault data.
(2) The above-mentioned high speed analysis function allows the speedy analytical solutions even for the largest scale power systemmodel in practical use in Japan.
(3) Accumulative probability variation values of voltage dips in a target period can be computed to allow easy analysis and evaluationof the influence of voltage dips on load points which users are concerned about. In addition, a useful voltage dip severity index forcomparison of the influence of voltage dips on multiple load points has been devised and incorporated in the new software.
A study analysis is shown in Fig. 3 where a hazard map used for earthquake prediction, etc. is applied. By using different
colours for different ranges of computation results on the system diagramme, it is visually possible to see and analyse different degrees
of influence of voltage dips in different areas.

Future Developments
Apart from contributing to the analytical computation of the distribution of influence of voltage dips caused by lightning
faults with the power systems of electric companies, efforts will be made to use the new software to quantify the voltage dip reduction
effects of various measures, including the installation of lightning arresters.
Main Researcher: Kazuyuki Tanaka,Senior Research Scientist, Consumer Systems Sector, System Engineering Research Laboratory
Reference
Development of Analytical Software to Predict Voltage Dips by Lightning Faults, CRIEPI Report T03004 (October, 2003)＊1：Development of Multi-Fault Analysis Software for Large-Scale Power Systems, No. T92034 (1993)

68

4. Power Delivery - Cost reduction and ensuring reliability of power delivering

No. 1 Transmission Circuit< Power System >Sending End

Patterns of Lightning Faults ＊ ：Faulted (Phases-to-Ground Faulted) PhaseNo. 2 Transmission Circuit

ＡａＢｂＣｃ1LG 1 : ＊ ａＢｂＣｃ

1LG 2 : ＊＊ＢｂＣｃ2LG 1: ＊ ａ＊ｂＣｃ2LG 2 : ＊ ａ
Ｂ＊Ｃｃ2LG 3: ＊ ａ＊＊Ｃｃ2LG 4: ＊＊＊＊Ｃｃ3LG 1: ＊ ａ＊ｂ＊ｃ3LG 2 : ＊ ａ＊ｂＣ＊3LG 3: ＊ ＊＊ｂ＊ｃ3LG 4 : ＊ ａ＊＊Ｃ＊3LG 5: ＊ ＊＊＊＊ｃ3LG 6: ＊＊＊＊＊＊

Phase-to-Ground Fault on Transmission Route1LG2LG3LG1LG1LG1Only faults at "nodeends" can be analysedby conventional method.

3LG
3LG

5261LG
1LG

13LG
3LG

5261LG
1LG

13LG
3LG

5Receiving End

21LG
2LG
3LG

6Fault on Transmission RouteMultiple solutions
Vd
corresponding to multiple
faults are produced at once.

Voltage Drop Vd
at Load Point dFig.1 Outline of Developed Analytical Technique for Voltage Dips
< Newly Developed >Data for probability oflightning faults
Analytical Software to Predict Voltage Dips・Fault computation using the symmetricalcoordinate method・Entire faults with the parallel 2transmission circuits

Existing system analysis
data owned by eachelectric company

Fig.2 Configuration of Newly Developed Voltage Dip Analysis System
Voltage Dip Severity Index：
It is judged that the larger thebottom left area is, the higher
the severity is.

IEEJ East 30
Standard Model
SystemDistribution Map of Voltage
Dip Severity Index

Voltage Dip Severity Comparison Index(Worst 5 and Best 5)
Voltage Dip Severity
Comparison Index K

Accumulative Frequency of Occurrence(Times/Year)

Accumulative Probability
Graph of Voltage Dip Influence

The computation results for two
points are shown as examples.

Worst 5 andBest 5

Node Number

Voltage Drop Rate at Receiving End (%)
Index (Influence) Value
High: Red

Green: Index (Influence) ValueLow

Fig.3 Study Analysis of Distribution of Voltage Dip Severity Index (Hazard Map)

69