A novel tool for transient stability analysis of large-scale.pdf

Simulation Modelling Practice and Theory 15 (2007) 786–800

www.elsevier.com/locate/simpat

A novel tool for transient stability analysis of large-scalepower systems: Its application to the KEPCO system

Yoon-Sung Cho a,b, Jungsoo Park a, Gilsoo Jang a,*

a School of Electrical Engineering, Korea University, Seoul 136-701, South Koreab Electrotechnology R&D Center, LS Industrial Systems, Cheongju 361-720, South Korea

Received 31 July 2006; received in revised form 3 April 2007; accepted 11 April 2007Available online 29 April 2007

Abstract

Time-domain simulation is an important tool for power system dynamic analysis. We solve a set of differential and alge-braic equations (DAE) in order to study the dynamic behavior of power systems. These power systems include thousandsof generators, exciters, turbine-governors, loads, and other devices. The resultant large-scale DAEs are very difficult tohandle and solve. Nevertheless, solution techniques are needed to not just guarantee accuracy but have computationalefficiency.

In this paper, we report on a novel tool that we developed to deal with time-domain simulation for dynamic analysisand operation of large-scale power systems. The tool has several major features related to transient stability analysis, con-tingency screening, and ranking. We mainly discuss the structure of this tool and the accuracy of the included dynamicmodels. Also, the paper proposes a new load model to overcome the low-voltage problem. The proposed technique pro-vides a good performance and convergence when the terminal voltage is below some predefined value. Compared to thecommercial tools, the developed tool is numerically well conditioned by introducing the ZIP model algorithm. This toolhas been used to support and enhance power engineering education at both the undergraduate and graduate levels. In thecase study, simulation results were validated through comparative simulations with the Power System Simulator for Engi-neering (PSS/E) and Transient Security Assessment Tool (TSAT).� 2007 Published by Elsevier B.V.

Keywords: Transient stability analysis; Power system modeling; Large-scale power systems; PSS/E; TSAT

1. Introduction

Because of deregulation and privatization in the power market and the increasing trend of interconnectionof power grids, the dynamic characteristics of power systems are being significantly changed [1]. Therefore, theanalysis of the dynamic behavior of power systems has become important. The results of stability analysis arecritically dependent on the choice of power system analysis tools. The summer peak load of the Korea Electric

1569-190X/$ - see front matter � 2007 Published by Elsevier B.V.

doi:10.1016/j.simpat.2007.04.007

* Corresponding author. Tel.: +82 2 3290 3246; fax: +82 2 3290 3692.E-mail address: [email protected] (G. Jang).

mailto:[email protected]

Y.-S. Cho et al. / Simulation Modelling Practice and Theory 15 (2007) 786–800 787

Power Company (KEPCO) system in the year, 2005, was 54,631 MW. Its installed generating capacity inAugust, 2005 was 61,737 MW. Despite the KEPCO system’s demand increases of 6% per year, there has beenno tool for transient stability analysis of the KEPCO system. In the restructuring process, engineers in theKEPCO are also faced with the need of a power system simulation tool developed with use of domestic tech-nology. The use of a KEPCO specific tool is to provide a convenient simulation environment taking intoaccount the dynamic and geographical characteristics of the KEPCO system. The objective of this paper isto report on our efforts in developing a transient stability analysis tool for the KEPCO system.

Traditional tools for power system dynamic simulation, such as the PSS/E [2,3], EUROSTAG, ETMSP,and TSAT [4], are very efficient and reasonably user-friendly. Also, most of these tools provide the possibilityof creating models for use in a dynamic simulation (e.g., Model writing of PSS/E, Macroblock of EURO-STAG, and the User-defined model of TSAT). However, implementation of new component models withinthese simulators is very difficult. Many papers have published this topic for the power system dynamic simu-lation tools as documented in the literature [5–15]. In the last decade, the topic of power system simulation inMATLAB/SIMULINK has been presented in [5–9]. The use of the MATLAB/SIMULINK for the develop-ment of power system component can provides a very strong benefit in handling control blocks and powersystem elements, validating new component through comparison of the simulation results for various events,and understanding of the basic concepts of power system modeling and simulation. Also, the extensive studyfrom the viewpoint of transient stability, voltage stability, and small-signal stability within the SIMULINKenvironment is available. However, MATLAB/SIMULINK-based simulation tools need their supporting pro-grams such as the MATLAB, SIMULINK, and so on. Although the MATLAB/SIMULINK is very efficientand reasonably user-friendly, the developed models using the SIMULINK cannot be implemented directlyinto the structure of the current tool we developed.

This paper presents the development of a novel tool for transient stability analysis of large-scale power sys-tems. The developed tool can be used to analyze the dynamic behaviors of large-scale power systems withoutother supporting programs such as the MATLAB. And, the developed tool has several features related to con-tingency analysis and enhanced output processing. In addition, the proposed ZIP model algorithm improvedthe accuracy of the developed tool. The developed tool has a robust stability of numerical integration and thecomputational efficiency required for the large-scale power systems.

The developed tool, with a good performance for the dynamic behaviors of the generators, exciters, tur-bine-governors, power system stabilizers, and load models with respect to power system stability, can providea very strong benefit in facilitating engineers’ understanding of the basic concepts of a power system dynamics,control, and operation. In addition, the developed tool permits students to study large-scale power systemdynamic simulations easily with an enhanced user-friendly interface which allows users to compose the con-tingency and scenario lists.

The important factor of the developed tool is to have a comparable accuracy with the PSS/E and TSAT,and it has been accomplished well. The comparison among the developed tool, the PSS/E, and the TSAT isnecessary to validate the developed dynamic models, the proposed algorithms, and etc. For example, in orderto implement the block diagrams such as the PSS/E library and IEEE Standards into the developed tool, wehave developed our own source codes for the models. In this paper, the tool we developed was applied to a testsystem and the KEPCO system in the year, 2005.

This paper is organized as follows. An overview of the tool’s structure and modules is presented in Section2. Section 3 includes a discussion of the development of the tool’s power system models based on the pro-posed modeling procedure. We introduce techniques used in developing a constant Impedance–Current–Power (ZIP) model. To demonstrate the validity of the component library against the commercial tool,comparative simulations of a 3-generator, 9-bus test system and the KEPCO system were conducted. Theresults are presented in Section 4. Some conclusions and comments about the developed tool are presentedin Section 5.

2. Overview of the developed tool

The power system calculations performed and actions provided by the developed tool are summarized asfollows.

Powrflow

Control

Dynamic

Monitor

Scenario

Contingency

Mandatory Data

Optional Data

Dynamic Simulation

Contingency Screening

SecurityComputation

Simulation Engine

Graphic Module

- Copy/save/print- Comparison- Others

Text Module

- Contingency Ranking- Security Index- Others

Simulation Result

Fig. 1. The overall structure of the developed tool.

788 Y.-S. Cho et al. / Simulation Modelling Practice and Theory 15 (2007) 786–800

• Power flow• Time-domain simulation• Transient security assessment• Contingency analysis• Scenario setup module• Output module

The overall structure of the developed tool is shown in Fig. 1. The input and output modules are written inC++ and the simulation engine is written in FORTRAN. The developed tool accepts a power flow data file inthe PTI and IEEE formats. It also accepts a dynamic data file in the PTI format. The remaining data files use anew format. The control data file defines a sequence of switching commands. The monitor data file specifiesthe monitored machine parameter, bus, and branch. The contingency data file defines a list of contingencies.The output module performs detailed analysis on the results obtained from the time-domain simulation, thetransient security assessment, and the contingency analysis. In addition, the tool includes a user-friendly inter-face which allows users to compose the contingency list and scenario and a flexible user-friendly graphical userinterface (GUI). Fig. 2 shows the simulation framework of the developed tool.

The security computation module is calculated using various security indices [4]. When the criteria are dis-satisfied, the result shows that the system is insecure. Also, the contingency screening and ranking module canbe used to rapidly screen and to rank a set of severe contingencies in terms of a critical clearing time (CCT). Afast contingency screening algorithm using a single machine equivalent was adopted for use in the tool [16,17].

3. Power system modeling

Fig. 3 illustrates the steps involved in developing modeling regime and the overall flow of a dynamic sim-ulation in the tool. The numerical integration of some modules affects the validity of the results. The second-order Euler method to solve power system DAEs is used. Since the second-order Euler method is used forcommercial tools such as the PSS/E, the numerical instability, an important property of numerical integration,will not be discussed in this paper [18–20].

As shown in Fig. 3, computational modeling involves a step-by-step procedure for solving a mathematicalmodel. Dynamic simulation requires that each component affecting the response of a physical system to a dis-turbance be faithfully modeled. Then, the procedure is to use model writing in the PSS/E to obtain the desiredresults. Verification tests involve a well-designed set of tests to verify that the modeling accurately representthe intended characteristics of the power system. This includes comparison with results obtained from the

Fig. 2. Graphical user interface of the developed tool. (a) A main configuration and display of simulation results and (b) wizard forcontingency process.


commercial tool. Unsatisfactory results of this testing require modifications of modeling as appropriate. Sincethe PSS/E has been used by KEPCO engineers for the operation and planning of the KEPCO system, themodel library of PSS/E was implemented in the tool as shown in Table 1.

3.1. Proposed modeling procedure

The process to develop a dynamic model [21–27] of a power system is proposed as follows:

Step 1. Construct a block diagram representing the requirements of the dynamic model.Step 2. Determine the DAEs of the equipment to be modeled and identify the state variables associated with

the model.Step 3. Develop the decomposed model by converting the transfer function blocks such as lag, washout, and

lead/lag into decomposed blocks illustrated in Fig. 4.

Analysis of results

Data Acquirement

Initialization

Network Solution

Time Derivative Calculation

Output

NumericalIntegration

Optionally Apply Disturbances

Advance TimeYes

No

ModelDefinition

Mathematical Modeling

Computational Modeling

Model Writing

Satisfactory?Yes

No

Debug

Simulation Run

The step involved in developing a dynamic model

Fig. 3. Proposed modeling procedure and dynamic simulation flow.

Table 1Power system model library in developed tool

Generator Exciter Turbine-governor PSS Othersa

GENROU IEEET1 IEEET3 TGOV1 IEEEST SVCGENSAL IEEEX1 IEEEX2 HYGOV PTIST1 STATCOM

IEEX2A EXAC1 IEEEG1 PSS2A UPFCEXAC1A EXAC3 IEEEG3 HVDCEXST1 EXST2 GASTEXST3 SCRX GAST2AEXPIC1 ESST4B IEESGO

a The task of expanding additional devices is underway.


Step 4. Calculate initial machine conditions and state variable time derivatives.Step 5. Go back to Step 3 when the criteria, the initial values, and the characteristics in accordance with the

dynamic simulation are not in agreement with the PSS/E and TSAT.Step 6. Use the power system models developed with the proposed procedure if simulation performs

satisfactory.

The test model in this application was based on a simplified excitation system as shown in Fig. 4(a). Applyingthe proposed procedure (Step 3), a decomposed model was developed. The block diagram of the developedmodel is shown in Fig. 4(b). Applying the proposed procedure (Step 4), the initial values and state variabletime derivatives can be expressed as

Initialization:

y1 ¼ 1� T A

T B

� �� EFD

Kð1Þ

y2 ¼ EFD ð2Þ

+- +

REFV

V

CE

MINE

MAXE

EFDBT

1s

AT s1++

S

ETK

s1+

EFD+

- +CE

REFV

SV

MAXE

MINEs

1

ET1

K+

-

-

+

++

1

2y1U

1y

x

2x

s1

BTAT

BT1

Fig. 4. Block diagram of simplified excitation system. (a) Transfer function block and (b) decomposed block.


Simulation:

x1 ¼U 1 � ðU 1 � T A=T B þ y1Þ

T Bð3Þ

x2 ¼ðU 1 � T A=T B þ y1Þ � K � y2

T Eð4Þ

where x1, x2 denote the state variable and y1, y2 represent the state variable time derivatives. With non-winduplimit, the state variable (y2) in Eq. (4) is limited.

3.2. Load model

Power system load modeling is one of the most important parts of analyzing power system transient sta-bility [28–34]. Network solution involves computing of current injections and solving YV = I. Especially, loadmodels with constant impedance, current, and power characteristics, which are the algebraic part of theDAEs, bring singularity issues into time-domain simulation of power systems. It is because the current injec-tion of constant impedance type is zero, whereas the current injection of constant current and power are notzero. In order to solve this problem, the load current must be recomputed and the network must be resolvedrepeatedly until the currents and voltages converge to a final value. However, the representation of constantimpedance load is simple to implement, whereas the representation of constant current and MVA load is dif-ficult to implement, cause low-voltage problem when the terminal voltage is small. This problem results in lossof accuracy, poor convergence, and divergence. In general, the load models used for stability analysis in sev-eral simulation tools about the low-voltage should be overcome by using a constant impedance model to rep-resent loads where the voltage is below predefined value.

A load modeling relevant to dynamic studies is described from the following equation. For a constantMVA load model, the boundary condition is given by [3]

REALðvki�kÞ ¼ �P k ð5ÞIMAGðvki�kÞ ¼ �Qk ð6Þ

Since this characteristic is not realistic for voltages below 0.8 per unit, Eqs. (5) and (6) are modified to make Pit

k and Qk functions of the magnitude of the bus voltage as shown in Fig. 5(a). For the constant current loadmodel, load may be obtained as follows [3]:

REALðvki�kÞjvkj

¼ �Ipk ð7Þ

IMAGðvki�kÞjvkj

¼ �Iqk ð8Þ

Voltage (pu)

0.0 0.5 1.0

P o

r Q

(pu

)

0.0

0.5

1.0

Voltage (pu)0.0 0.2 0.4 0.6 0.8

Cur

rent

(pu

)

0.0

0.5

1.0

Fig. 5. Load characteristic. (a) Constant MVA and (b) constant current.


Eqs. (7) and (8) are modified to make Ipk and Iqk functions of the magnitude of the bus voltage as shown inFig. 5(b), because this characteristic is not realistic for voltages below 0.5 per unit.

The overall structure of the ZIP model algorithm to analyze the power system stability is shown in Fig. 6.The V_Load and Cur in Fig. 6 are the complex voltage at load bus and the complex injection current used dur-ing the network solution. The Load_cur and Load_MVA in Fig. 6 are the complex constant current and MVAload at load bus. In Fig. 6, the P/Q_Fig. 5(a) is the P or Q value at the magnitude of the low bus voltage asshown in Fig. 5(a), the Current_Fig. 5(b) is the current value at the magnitude of the low bus voltage as shownin Fig. 5(b).

4. Numerical results

4.1. The test system

To examine the validity of the component library in the tool, comparative simulation was performed on themodified nine-bus system [25]. This system has 3 generators and 9 buses, where the double line was adopted.Each generator was assumed to be equipped with the same type of exciter and governor. The round rotor gen-erator model (GENROU), the proportional/integral excitation system (EXPIC1) and the steam turbine-gov-ernor (TGOV1) were used.

To demonstrate the performance of the PST, six scenarios were defined and are shown in Table 2. The valuefor the ZIP model is based on a static characteristic of the KEPCO system summer load as shown in Table 3.Before the transient stability performance of the PST, the calculation of initial condition values was per-formed. Tables 4 and 5 show the results of the initial machine conditions of the commercial tools and thedeveloped tool.

Start

Volt = V_Load

VM = |Volt|

Load_cur = P_Load_cur + jQ_Load_cur

Load_cur 0

VM > 0.5 (pu)

Cur = Cur VM · (Load_cur / Volt) *

Load_cur = Load_cur · Current_Figure 4(b)

Load_MVA = P_Load_MVA + jQ_Load_MVA

Load_MVA 0

VM > 0.8 (pu)

Cur = Cur (Load_MVA / Volt) *

Load_MVA = Load_MVA · P/Q_Figure 4(a)

Constant Impedance (Cur = 0)

End

Yes

Yes

Yes

Yes

No

No

No

No

Fig. 6. ZIP model algorithm.


In Scenario A, a three-phase fault between buses #5 and #7 was applied in the dynamic simulation. It wasinitiated at 1.0 s and cleared at 1.35 s. The simulation was performed for 5 s. The rotor angle plot for the gen-erator at bus #2, with respect to the generator at bus #1, is illustrated in Fig. 7(a). Fig. 7(b) and (c) show thefield voltage and the electrical power for the generator at bus #2. From the results, we saw that the system wasstable. The results exhibited good agreement between the commercial tools and our tool.

In Scenario B, a simulation is performed to examine the validity of the PST over a wide range of CCT.Table 6 shows the result of CCT by the PSS/E, TSAT and the PST. It should be noted that the commercialtools differ in the CCT respect and the PST is similar to the PSS/E. The difference between the PST and theTSAT corresponds to 1 time step (approximately 0.0083 s). In order to show the simulation results with thesame clearing time, the PSS/E, PST and the TSAT were initiated at 1.0 s and cleared at 1.3917 s. The simu-lation was performed for 2.5 s. Fig. 8 shows the response of the relative rotor angle of the generator #2 whenthe fault duration time of the three tools is 0.3917 s. The difference between the TSAT and other tools iscaused by a different fault clearing time. The results of Fig. 8 show the transient stability performance ofthe PST.

Table 2Description of scenarios

Scenario Fault type Fault location Fault duration (s) Load model Stability Output

A Line fault One circuit of buses #5 and #7 0.3500 Impedance Stable Fig. 7(a)–(c)B 0.3917 Impedance Unstable Fig. 8C 0.1000 Current Stable Fig. 9(a)D 0.1000 MVA Unstable Fig. 9(b)E 0.1000 ZIPa Stable Fig. 9(c)F 0.1750 ZIPa Unstable Fig. 9(d)

a Coefficients of load characteristics for simulations are summarized as follows: constant impedance (%): 14.1, constant current (%):35.1, constant impedance (%): 50.8.

Table 3Static load characteristics of the KEPCO system (a summer peak case)

At 04:00 At 15:00 (peak) At 19:00

Constantimpedance

Constantcurrent

Constantimpedance

Constantcurrent

Constantimpedance

Constantcurrent

Active power (%) 12.8 34.4 14.1 35.1 14.0 35.5Reactive power

(%)32.1 42.9 29.3 44.4 30.8 42.9

Table 4Initial machine condition (rotor angle)

Generator # Rotor angle (degree)

PSS/E TSAT PST

1 34.599 34.444 34.5962 73.519 73.514 73.5093 49.239 48.962 49.245

Table 5Initial machine condition (EFD)

Generator # EFD (pu)

PSS/E TSAT PST

1 1.9290 1.9169 1.92842 2.9302 2.9141 2.93053 1.4178 1.4157 1.4177


To demonstrate the effect of the load model used for the PST on stability, four scenarios were used. Theresponse of the generator rotor angle was compared to the PSS/E and the TSAT. In Scenarios C and D, loadswere considered to be 100% constant current and 100% constant MVA, respectively. The point of these sce-narios, with the same fault-clearing time, was to show that simulation results are critically dependent on thechoice of the load models. In Scenarios E and F, loads were modeled as ZIP models. Fig. 9 shows that therelative rotor angle of generator #2 with respect to various load models. In Fig. 9, the difference betweenthe PST and the TSAT corresponds to 1–2 time steps. The stability among the three tools should be deter-mined by the modeling method of the constant MVA load model as shown in Fig. 9. For the constantMVA model the PST used the proposed algorithm when the voltage is below the predefined value. But theconstant MVA model of the TSAT used a constant impedance model to represent the load in the situation.As a result, having accurate models considering load behavior during disturbance enhances the power system’sstability in anticipation of potential emergency conditions. The results of investigations on six scenarios withsignificantly different characteristics have made it evident that the PST performs satisfactory.

Time (seconds)

0

Rel

ativ

e an

gle

(deg

rees

)

-50

0

50

100

150

200PSS/ETSATPST

Time (seconds)

EFD

(pu

)

2.0

2.5

3.0

3.5

4.0

4.5PSS/ETSATPST

Time (seconds)

Ele

ctri

cal p

ower

(MW

)

20

40

60

80

100

120

140

160

180

200

220

PSS/ETSATPST

1 2 3 4 5 0 1 2 3 4 5

0 1 2 3 4 5

Fig. 7. The simulation results of generator #2 for Scenario A. (a) Relative rotor angle, (b) EFD and (c) electrical power.

Table 6Critical clearing time of Scenario B

Clearing time (s) PSS/E TSAT PST

1.3750 Stable Stable Stable1.3833 Stable Unstable Stable1.3917 Unstable Unstable Unstable


As shown in Figs. 8 and 9, the difference among the three tools is due to the difference in modeling the gen-erators, exciters, turbine-governors, power system stabilizers, and loads. Also, the numerical and networksolution methods to solve DAEs affect the results.

The computational time of the PSS/E, the TSAT and the PST in Scenario E is shown in Table 7. It showsthat the PST requires more time than the commercial tools to finish the dynamic simulation.

4.2. Study on dynamic characteristics of the KEPCO system

More than 40% of the total load demand is in the metropolitan region, while the majority of generation is inthe non-metropolitan regions. Because of this reality, a large amount of active power flows through a set ofinterface lines connecting the metropolitan regions and other regions. To reduce transmission congestion inmetropolitan regions, FACTS devices are currently being studied, and an 80 MVA UPFC, one such FACTSdevice, installed as a pilot system in Gangjin is now in operation.

Time (seconds)

0.5 1.0 1.5 2.0 2.5

Rel

ativ

e an

gle

(deg

rees

)

0

100

200

300

400

500

PSS/ETSATPST

Fig. 8. The relative rotor angle of generator #2 for Scenario B.

Time (seconds)

0 1

Rel

ativ

e an

gle

(deg

rees

)

20

30

40

50

60

70

80

90PSS/EPSTTSAT

Time (seconds)

Rel

ativ

e an

gle

(deg

rees

)

0

1000

2000

3000

4000

5000

6000PSS/EPSTTSAT

Time (seconds)

Rel

ativ

e an

gle

(deg

rees

)

20

30

40

50

60

70

80

90PSS/EPSTTSAT

Time (seconds)

Rel

ativ

e an

gle

(deg

rees

)

0

1000

2000

3000

4000PSS/EPSTTSAT

2 3 4 5 0 1 2 3 4 5

0 1 2 3 4 50 1 2 3 4 5

Fig. 9. The relative rotor angle of generator #2 with respect to various load models. (a) Scenario C, (b) Scenario D, (c) Scenario E and (d)Scenario F.


The test system was based on the KEPCO system in the year, 2005. The system consisted of 258 generators,1622 buses, and 2716 AC branches. Its total generation was 52238.2 MW and 12221.7 MVAR. 994 loads had51434.6 MW and 23768.3 MVAR. The contingencies of the simulation were a double line three-phase fault at

Table 7Computational time for Scenario E

CPU time (s)

PSS/E 0.210TSAT 0.300PST 0.519


345 kV and 765 kV lines cleared by tripping the double line. The contingency ranking module was applied tothe contingency list of 106 contingencies. The top 17 severe contingencies are listed in Table 8.

From this result, it was found that the contingencies were divided into two components: plant fault andinter-area fault. To deal with the detailed simulation for the inter-area fault where an entire area separatesfrom the rest of the system, we selected the contingency of the main transmission line between buses #4010and #6030. This is an important line as the amount of active power transfer on this line has 7.27% of the loadof the metropolitan region. Fig. 10(a) shows the rotor angle plot for the generator at bus #26201 with respectto the generator at bus #29351 for the stable case. In the critical case, generators at bus #26101 and bus#26151 lost synchronism with respect to the rest of the system as shown in Fig. 10(b) obtained from thePST. The contingencies affecting the inter-area mode have had significant influence on the stability of theKEPCO system. Through comprehensive simulation results under large-scale power systems, the PST is com-patible with those commercial programs in terms of transient stability analysis.

Table 9 shows the computational time of the PSS/E, the TSAT and the PST in the above-mentioned con-tingency which was ranked 14th on the Table 8. It was initiated at 1.0 s and cleared at 1.1 s. The simulationwas performed for 5 s. The PSS/E is almost twice as fast as the PST.

From Tables 7 and 9, we observe that network solution problem affects the computational time of the PST.The time-domain simulation involves tasks such as network solution, numerical integration, and interfacing

Table 8Results of contingency analysis for the KEPCO system

Rank Fault location PST PSS/E TSAT Mode* Critical generatorFrom To CCT (s) Actual CCT CCT (s)

1 6020 6030 – – – P 26201–41 7900 87,200 – – – P 28811–31 9150 9800 – – – P 29151–21 10301 10350 – – – P 303511 1020 5010 – – – I 25151–41 6450 7151 – – – P 27155–67 7150 7600 0.0831 0.0750–0.0833 0.0710 P 27151–48 5150 5600 0.0872 0.0750–0.0833 0.0830 P 25151–49 10150 10700 0.1078 0.1000–0.1083 0.1070 P 30151–6

10 6300 6950 0.1078 0.1000–0.1083 0.1190 P 26101–626951–626201–4

11 4400 4450 0.1127 0.1083–0.1167 0.1130 P 24451–412 5152 5500 0.1128 0.1083–0.1167 0.1130 P 25155–613 10150 10800 0.1218 0.1167–0.1250 0.1250 P 30151–614 4010 6030 0.1220 0.1167–0.1250 0.1250 I 26101–6

26151–626201–4

15 6100 6900 0.1329 0.1250–0.1333 0.1370 P 26101–616 6101 6300 0.1331 0.1333–0.1417 0.1370 P 26101–617 6300 6900 0.1461 0.1417–0.1500 0.1550 P 26101–6

26951–626201–4

* I: The contingency is a double line three-phase fault at interface lines between the region and the neighboring regions.P: The contingency is a double line three-phase fault at transmission lines within region.

Time (seconds)

0.0 0.5 1.0 1.5 2.0

Rel

ativ

e an

gle

(deg

rees

)-20

0

20

40

60

80PSS/ETSATPST

Time (seconds)0.0 0.5 1.0 1.5 2.0

Rel

ativ

e an

gle

(deg

rees

)

0

200

400

600

800Bus #23251 (MP area)Bus #26101 (ML area)Bus #26151 (ML area)Bus #27151 (SW area)

-40

Fig. 10. The simulation results of the KEPCO system. (a) Relative rotor angle of generator #26201, (b) relative rotor angle of generators#23251, #26101, #26151 and #27151 using only PST.

Table 9Computational time for the KEPCO system

CPU time (s)

PSS/E 7.831TSAT 10.000PST 15.537


the solutions of the DAEs. Generally, optimally ordered triangular factorization of sparse matrix has beenemployed to speed up the solution of algebraic equations. From this perspective, the task of optimizing thePST with more computational time is underway.

5. Conclusions

This paper presented the development of a transient stability analysis tool for large-scale power systems.The validity of the developed tool was evaluated for the cases of a modified nine-bus system and the KEPCOsystem. Various scenarios were simulated and stability was analyzed. The key conclusions, drawn from thisstudy are as follows.

• The results exhibited good agreement between our developed tool and the commercial tools. Therefore, thedeveloped tools can be used to analyze the dynamic behaviors of large-scale power system.


• The generators, exciters, turbine-governors, loads, and other devices were accurately modeled using theproposed modeling procedure. Because the characteristics of the load model were not realistic for low-volt-age, a ZIP model, based on the proposed algorithm, was developed. The development of a ZIP modelimproved the accuracy of the developed tool.

• This novel tool was sufficient for graduate students and undergraduate students who major in power sys-tems enabling them to understand and learn about power systems. Also, the developed tool has been usefulfor engineers who are new to the subject of design and operation of the KEPCO system.

• The developed tool has been used for the students of several power engineering courses at Korea Universitysince the fall semester of 2006. They used it well with one day training, and we will get their feedback toenhance our tool. Also, the tool is going to be used at the research group at Cornell University. The stu-dents obtain a good knowledge of the power system dynamic simulation associated with understanding dif-ferential and algebraic equations, assessing transient stability analysis, and handing small power system aswell as large-scale power system. Especially, they get experience and enjoyment in learning about time-domain simulation of power system through the comparative study between theoretical derivations andsimulations results.

• The necessity for user-defined functions for educational and research purposes has being significantlyincreased. Although the commercial tools provide the possibility of creating new components modelsand modifying existed models, the approach for implementation of new component models within thesetools is very difficult. The developed tool does not provide a convenient function for the modification oraddition of new component models and algorithms, but the authors are trying to enhance the ability ofthe developed tool.

• Further work on incorporating FACTS devices, nonlinear load models, and KEPCO’s recently installedunique dynamic equipment, is going on. Also, the PST is continuously under development as optimalordering method, triangular factorization method and forward-elimination/back-substitution using LUmethod w.r.t. solving YV = I.

Acknowledgements

The authors greatly appreciate the support by MOCIE through EIRC program with APSRC at KoreaUniversity.

References

[1] V. Vittal, Consequence and impact of electric utility industry restructuring on transient stability and small-signal stability analysis,Proc. IEEE 88 (2) (2000) 196–207.

[2] PSS/E-29 Program Operation Manual, Siemens Power Technologies Inc., 2002.[3] PSS/E-29 Program Application Guide, Siemens Power Technologies Inc., 2002.[4] TSAT User Manual, Powertech Labs Inc., 2004.[5] F. Milano, An open source power system analysis toolbox, IEEE Trans. Power Systems 20 (3) (2005) 1199–1206.[6] C.D. Vournas, E.G. Potamianakis, C. Moors, T.V. Cutsem, An educational simulation tool for power system control and stability,

IEEE Trans. Power Systems 19 (1) (2004) 48–55.[7] K. Schoder, Am. Hasanovic, A. Feliachi, A. Hasanovic, PAT: A power analysis toolbox for Matlab/Simulink, IEEE Trans. Power

Systems 18 (1) (2003) 42–47.[8] E. Allen, N.L. White, Y. Yoon, J. Chapman, M. Ilic, Interactive object-oriented simulation of interconnected power systems using

Simulink, IEEE Trans. Power Systems 44 (1) (2001) 87–95.[9] C.M. Ong, Dynamic Simulation of Electric Machinery using Matlab/Simulink, Prentice-Hall, New Jersey, 1998.

[10] M.P. Selvan, K.S. Swarup, Development of power flow software using design patterns, IEEE Trans. Power Systems 21 (2) (2006) 611–618.

[11] M. Larsson, ObjectStab-An educational tool for power system stability studies, IEEE Trans. Power Systems 19 (1) (2004) 56–63.[12] A.Z. Khan, F. Shahzad, A PC based software package for the equal area criterion of power system transient stability, IEEE Trans.

Power Systems 13 (1) (1998) 21–26.[13] J. Yang, M.D. Anderson, PowerGraf: An educational software package for power systems analysis and design, IEEE Trans. Power

Systems 13 (4) (1998) 1205–1210.


[14] J. Zhu, D.L. Lubkeman, Object-oriented development of software systems for power system simulations, IEEE Trans. Power Systems12 (2) (1997) 1002–1007.

[15] M. Stubbe, A. Bihain, J. Deuse, J.C. Baader, STAG-A new unified software program for the study of the dynamic behavior ofelectrical power systems, IEEE Trans. Power Systems 4 (1) (1989) 129–138.

[16] M. Pavella, Transient Stability of Power Systems (A Unified Approach to Assessment and Control), Kluwer Academic Publishers,London, 2000.

[17] B. Lee, S.H. Kwon, J. Lee, H.K. Nam, J.B. Choo, D.H. Jeon, Fast contingency screening for online transient stability monitoring andassessment of the KEPCO system, IEE Proc.-Gener. Transm. Distrib. 150 (4) (2003) 399–404.

[18] B. Stott, Power system dynamic response calculations, Proc. IEEE 67 (2) (1979) 219–241.[19] C.W. Ueberhuber, Numerical Computation 1 (Methods, Software, and Analysis), Springer, New York, 1997.[20] C.W. Ueberhuber, Numerical Computation 2 (Methods, Software, and Analysis), Springer, New York, 1997.[21] J. Machowski, J. Bialek, J.R. Bumby, Power System Dynamics and Stability, John Wiley & Sons, New York, 1994.[22] P. Kundur, Power System Stability and Control, McGraw-Hill, New York, 1994.[23] J. Arrillaga, N.R. Watson, Computer Modeling of Electrical Power Systems, John Wiley & Sons, New York, 2001.[24] P.W. Sauer, M.A. Pai, Power System Dynamics and Stability, Prentice-Hall, New Jersey, 1998.[25] P.M. Anderson, A.A. Fouad, Power System Control and Stability, IEEE Press, New York, 1994.[26] IEEE guide for synchronous generator modeling practices in stability analyses, IEEE Std 1110-1991, IEEE, New York, 1991.[27] IEEE recommended practice for excitation system models for power system stability studies, IEEE Std 421.5TM-2005, IEEE, New

York, 2005.[28] Q. Ai, D. Gu, C. Chen, New load modeling approaches based on field tests for fast transient stability calculations, IEEE Trans. Power

Systems 21 (4) (2006) 1864–1873.[29] V. Knyazkin, C.A. Canizares, L.H. Soder, On the parameter estimation and modeling of aggregate power system loads, IEEE Trans.

Power Systems 19 (2) (2004) 1023–1031.[30] Y. Wen, L. Jiang, Q.H. Wu, S.J. Cheng, Power system load modeling by learning based on system measurements, IEEE Trans. Power

Delivery 18 (2) (2003) 364–371.[31] E.H. Allen, M.D. Ilic, Interaction of transmission network and load phasor dynamics in electric power systems, IEEE Trans. Circuits

Systems 47 (11) (2000) 1613–1620.[32] IEEE Task Force Report, Load representation for dynamic performance analysis, IEEE Trans. Power Systems 8 (2) (1993) 472–482.[33] B. Choi, H. Chiang, Y. Li, Y. Chen, D. Huang, M. Lauby, Development of composite load models of power systems using on-line

measurement data, J. Electrical Eng. Technol. 1 (2) (2006) 161–169.[34] W.W. Price, K.A. Wirgau, A. Murdoch, J.V. Mitsche, E. Vaahedi, M.A. El-Kady, Load modeling for power flow and transient

stability computer studies, IEEE Trans. Power Systems 3 (1) (1988) 180–187.

Documents

A novel tool for transient stability analysis of large-scale.pdf