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IEE 2nd International Conference on Advances n Power System Control, Operation and Management, December 1993 Hong Kong

Effects of the Excitation System Parameterson Power System Transient Stability Studies

Jiang Jianminhu Shouzhen, Shen Shande, Chen HoulianDepartment of Electrical Engineering

Tsinghua UniversityBeijing 100084 China

AbstractThe excitation system parameters of large

synchronous generators have great effects on power systemstability studies. It is pointed out in this paper that by usingthe excitation system parameters identified from the fielddata by means of modern identification technology canrepresent the actual responses of the excitation systemmore accurately. Therefore, it is necessary to adopt theparameters identified from the field data in real power sys-tem stability studies. The comparison results of three kindsof excitation system models, i.e. the electromagnetic forceE', constant model, typical parameter model, and real

model identified from field dat a, are also presented.The results demonstrate that the adjusting effects may

be exaggerated by using the E , constant model in powersystem stability studies to represent the conventionalexcitation system with time constant t =0.5 , conceal thestability risk, while for fast response excitation system, thetransient stability limits may be reduced by using E , con-stant model, and thus conceal the potential of stability lim-its.

The optimization of the excitation system parametersand their effects on power system transient stability studiesare also given in this paper.1. Introduction

By using the excitation system model and itsparameters identified from the field data by means of sys-tem identification technology in power system transientstability studies, the effects of excitation system on thetransient process can be more accurately represented. Itwill contribute to improve the accuracy of power systemanalysis, to optimize the type selection and adjustment ofthe excitation system equipment, and to improve the levelof economic and secure operation.

In power system transient stability studies, the classictransient electromagnetic force E , constant model isadopted to approximate the adjusting effects of theexcitation system considering lacking of adequate modeland its parameters. Bur this classic E , constant modelcannot directly include the effects of adjusting block of theexcitation system. It becomes even worse considering that,with the enlargement of generator capacity and power sys-tem size, simplified mathematical model is no t adequa te forthe analysis of generator-network characteristics. Thus itwill leads to a hidden peril in power system secure opera-

Northeast ElectricPower Bureau

Shenyang, China

tion o r reduce economic efficiency. Using the model and itsparameters obtained from field data in power system calcu-lation, the transi ent process of the real power system can bemore accurately represented a nd will alleviate the blindnessin power system planning, design and operation.

With the development of high-speed high-gainexcitation system, it becomes more necessary to make themgive full play in improving the stability potential, and ob-tain more appropriate excitation system equipmentscheme. Different kinds of excitation systems, differentparameter settings and installation place can affect thepower system transient in different ways. Therefore, it isimportant to carry out studies on excitation systemparameter identification.

In recent years, with the fast development of systemidentification theory and the wide application in power sys-tems, more and more accurate excitation systemparameters are obtained from field data. In this paper,large amounts of transient stability simulation studies arecarried out under various kinds of fault conditions to ana-lysis the behaviour and effects of excitation system undervarious disturbance levels.

In this paper, the comparison results of E , constantmodel, typical designing parameter model and the actualmodel obtained from field data in power system transientstability studies are given with emphasis on thei r effects ontransient stability. Several important conclusions are alsopresented. The effects of excitation system parameters onpower system stability studies are also given.2. Calculation results2 1 Studying electric power system configuration

North China Electric Power System:The Central Shanxi subsystem remains unchanged

while other regions are simplified as depicted in Figure(a). The permanent three phase to ground fault is takenplace on the 500KV line from Shaner power plant toHouchun substation. Three kinds of excitation systemmodels are a l l adopted in power system transient stabilitycalculation.

East China Electric Power System:The Pingwei power plant is connected to the main part

of the system through a 500KV line, which can be repre-sented as a single-generator to infinite bus system asshown in Figure (b). The excitation system of the600MW generating unit is of brushless rotating a.c. kindand belongs to fast response type.

The Huaibei power plant, locats on the verge of the532

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East China system, is connected to the main systemthrough long transmission lines, and operats in the integralelectromagnetic loop. Therefore, the swing angle of thegenerating unit almost always becomes the main indicatorof system stability. The excitation system of the 200MWgenerating unit is independent excitation systeme a.c. kindwhose response characteristics belongs to common type.The single phase to ground compound fault and threephase to ground short circuit fault is taken place at the out-let of Huaibei power plant.

Northeast China Electric Power System:Tongliao power plant is connected to the main system

through 200KM transmission lines with 220KV voltagesand is a terminal plant. Several kinds of faults are simu-lated to analysis the conventional excitation system of200MW generating unit.

Model initialtype swing

2 2 calculation resultsThe transient stability limits are calculated according

to various kinds of different system configurations andthey are shown in Table 1.

The real obtained excitation system parameters areadopted for the conventional excitation system of theHuaibei power plant and for the fast response typeexcitation system of the Pingwei power plant.

first second thirdswing swing swing

convent ionalE6I constant excitation excitationfast

Is h e ~ ~ ~ O u 350MW 370MW 410MW

It can be seen from Table 1 that the selection of theexcitation system models can play an important role intransient stability studies. Under some conditions, about10 percent transient stability limit increment can be ob-tained by using'fast response excitation system model com-paring with the conventional excitation system model.

The North China system will lost stability when thepower flow of the Shenhou line exceeds 350MW if the ef-fects of the excitation system in the Shanxi subsystem areneglected. But it can be raised to 370MW which is about5.7 percent u p if the conventional excitation sys tems are in-cluded. If considering the fast response excitation systems,17 percent increment can be expected which amounts to410MW. As for Pingwei power plant, when the fast re-sponse excitation systems are considered, the power flow ofthe Fenyao line can be increased by 11 perecnt. while forthe Huaibei power plant, when the fast response excitationsystems are considered, the power flow of the Huaixu linecan be increased by 4 percent. But when the actually ob-tained excitation system parameters are adopted in powersystem stability studies, the obtained stability limit is sameas that obtained by using the Eq constant model.

Table 2shows part of the results of the transient sta-bility studies under different fault conditions in NortheastChina Power System when considering different models.

It can be seen that the transient stability limit can be

increased by 4-6 percent if the actual excitation systemmodel obtained from field data is used in power systemtransient stability instead of the typical Eq constantmodel when the fault is taken place in the outlet ofTongliao power plant. As for the three phase to groundshort circuit fault, the critical clearing time can be increasedby 0.02 .

Table 2 Result of transient stability acalculation

728757

increment 40 M W 29percentage 5 39 4 02

364 87

E', model

actual model

fast modcl

0 8 1 6

O / R 1 6

O / R 1 6

3 0 / 145 3

4 5 / 182

22 5 131 8

9 7 5 / 3 7 2 decay1

/ 1 0 2 . 5 / 1 2 1 . 6 ~ 1 7 2 . 5 / 1 2 0 . 7 1

constantic actual model

Fig. 2 Power angle curve in three phase shortfault for Huen-Hou line

Table 3 and Fig 2shows that the first swing angle ofthe actual system is about 10 degree smaller than that ofthe simulation re:sults when typical E , constant modelsare used. Therefore, when the generator to network ispoorly interconnected and the fault is severe, thesimulation results may hidden the phenomena of lostingsynchronization. B ut if the excitation system is changed in-to a fast type, better stability results can be expected.3. Analysis

When the actual excitation system models obtainedfrom field data are used in real power system stability stud-ies, more accurate results, some of which even contradictedwith the traditional ideas about the power systems, can beobtained. Some conclusions are given as following:

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3.1. The results cannot always be pessimistic when E ,, con-stant models are used in transient stability studies.It is common idea that when E , constant models

are used in power system transient stab ility studies, the sw-ing condition of the power angle is less severe than that in-cluding the effects of actual excitation systems, a nd stabili-ty limit obtained by using E , constant models is of somesecure margin as for the latter case, thus cannot bringabout risk to power system stability. But from the resultsof transient stability studies of several different power sys-tems, we find that when typical E , constant models areused in power system transient stability studies, the magni-tude of the first swing angle may be IO degree smaller thanthat when the actual excitation system models obtainedfron field data are used, and this can be seen from Figure 1and Table 3. The large amounts of simulation results dem-onstrate that when E , constant models are used to rep-resent the convantional excitation systems under large dis-turbance , the adjusting effects in the initial stage is optimis-tic. This contradiction idea makes it necessary to revalutethe effects of classic models and the related power systemstability criterion.

In conventional transient stability programs, thesynchronous machine models included are of followingform to represent the variations of Eq:

Where T s the time constan t of d-axis.If the actual value of T / d t is not used and a very

large value is given, then d E , turns to be zero and (1)deteriate into the E , constant model.

After the disturbance took place, the excitation systemreceives the severe variations of terminal voltage of thegenerating unit and induces reinforced exciting in order tomaintain or increase the transient electromagnetic forceE ,. This makes the electromagnetic power of the gener-

ating unit restores to prefault level or even larger and re-duces the deficiency between prime mover and generator.Thus restrain acceleration of the rotor and fluctuation ofthe power angle. This is the principle of which the excitaionsystem can help to improve the power system transient sta-bility.

As for conventional excitation systems, the time con-stant is comparatively large, thus in the initial stage afterthe disturbance took place, it will not bring its adjusting ef-fects into play, and E , decreases until attains to its ex-tremity at 0.52 . Afterwards, the excitation system makes

increase steadyly and exceeds the prefault level. Itbrings about large errors when using the Eq' constantmodels to represent the conventional excitation systems,especially for the first swing which is critical for transientstability, and exaggerates the adjusting effects of theexcitation systems, therefore conceals the potential risk. ASfor the fault which can be cleared once, such as opening aline, the error is considerablely small, but for the com-pound faults, such a s reclosing after single phase to groundfault, this error is very large.

This phenomena has also been put forward in [I] Af-ter careful studying on the transient process represented by

E ,

the detailed models and E , constant models, Andersonpointed out that when the detailed models are used, themagnitude of the first swing is more larger than that when3 2 The stability limit may be reduced when E , constant

models are used in transient stability studies insteadedof fast response excitation system:Large amounts of simulation studies demonstrate that

the stability limits may be reduced when E , constantmodels are used, especially for the fast response excitationsystems, which can be clearly seen from Table 1 and Table3.

After the disturbance occured, the fast responseexcitation system brings its adjusting effects into play andreduces the swing angle. In following swing process, itmakes the power system approach stability. Therefore, us-ing the E , constant model to represent this kind ofexcitation systems is obviously leads to lower transmissioncapacity. F or example, in Table 1 and 3, the stabili ty limitscan be increased by 5-10 percent. If the real power systemsare operated under such assumptions, considerable eco-nomic benefits can be obtained.

E, constant models are used.

4. The influence of excitation system parameter optimizationon transient stab ility studies:

Different excitation system parameters will lead to dif-ferent simulation results in transient stability studies.Therefore, appropriate adjustment of excitation systemparameters is of some importance in actual power systemoperation. The main parameters of excitation systems areas followings:

(1). Regulator gain, K : Its influence is comparativelysmall, and increasing its value helps to reduce the swingangle.

(2). Excitor time constant TE:ts influence is great,and decreasing its value helps to maintain stability.

(3). Gain of volatage regulator ,ErdmPx:ts influence isgreat, and increasing its value helps to maintain stabili ty.(4). Negative feedback coefficient, K : It must be

presetted to an appropriate value, and too large its valuemay leads to certain bad influences.

( 5 ) . Excitor saturation coefficient S Decreasingits value helps to improve the adjusting effects of theexcitation system on stability.

In optimizing the excitation system parameters, fairlygood adjusting effects can not be at tained if merely adjust acertain parameter, thus it is necessary to consider itcomprehensively. For example, when T increases to 300and T, reduces to 0.0175 , the studying system will loststability. But if K r is changed from 0.247 to 0.017 it willmaintain stability.

Note: K is gain of the voltage regulator. T, is thetime constant of PID block.

Table 4lists some of the comparative results of differ-ent excitation system parameters on stability limits. It canbe seen that if these two parameters are optimized, the sta-bility limits can be increased by 5.6 percent.

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Table 4 The comparison results of optimizedexcitation system parameters and Elq

constant model o n stability limitsAdflslablc parameters

Slnbilily limit

actual modcl 0 9 310 006 149

5. Conclusions(1) The transient process of actual power system can

be accurately represented by using actual excitation modelsobtained from field data. Thus, it is necessary to adoptmore realistic models in power system stability studies, andto make it.

(2) The stability limits may be overstated if the Eqconstant models are used to represent the conventionalexcitation systems, and their adjusting effects may be exag-gerated, especially in the first swing.

(3) The adjusting effects of the fast responseexcitation system is better than those of the Eq' constantmodel and conventional excitation system. The stabilitylimits may be decreased if the adjusting effects of the fastresponse excitation systems are neglected, thus reduce theeconomic benefits.

4) The method of optimizing the excitation systemparameters is a powerful tool for obtaining great economicbenefits while maintaining security with small investments.It is necessary to promote the development of the technol-ogy of optimizing excitation system parameters incoorporation with system identification theory.

Than ks for J iang Shanli, Chen Minhao, W u Qilin.

REF ERENCES(11 P. M. Anderson, Power System Control and

Stability-, 1979.3.

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