Influence of the Frequency and Voltage Dependence of Load Part Systems on the Control Behaviour of Power Systems During Emergency Conditions

Copyright © IFAC 12th Triennial World Congress, Sydney, Australia, 1993

INFLUENCE OF THE FREQUENCY AND VOLTAGE DEPENDENCE OF LOAD PART SYSTEMS ON THE CONTROL BEHAVIOUR OF POWER SYSTEMS DURING EMERGENCY CONDITIONS E. Welfonder, R. Hall and R. Neifer Department of Power Generation and Automatic Control, University of StuIIgart, PfafJenwaldring 9, D-7000 StuIIgartllO, Germany

Abstract. For the investigation of the frequency and voltage dependencc of the load self-acting data acquisition systems have been installed and operated for more than two years in eight load part systems in Germany and Francc. The data acquisition systems and the evaluation procedure developped for this purpose are descrihed as well as the identified load parameters. Furtheron there will be shown the great influenee of the freljueney and voltage dependence of the load on the control behaviour of isolated and interconnected power systems especially during emergency conditions. Keywords. Load self-regulation effect, power system control, load identification, digital data acquisition systems.

connected power systems . For still being able to investigate the frequency and voltage dependence of load part systems a special data acquisition and evaluation method has been dcvclopped by the authors. This method uses the 'natural' frequency and voltage deviations occuring sporadically during normal power system operation for the identification of load part systems.

1. INTRODUCTION In electrical power systems small malfunctions are mainly corrected by the turbine and the generator actuators of the power plants . However when the actuators reach their limitations, especially in case of strong malfunctions, only the load self-regulation effect remains active. This effect means that the active power consumption decreases as well with falling frequency as with falling voltage. Reactive power is also reduced with falling voltage but increased with falling frequency. But also during normal operating conditions the load selfregulation effect has a stabilizing influence on the system dynamics, e.g. on the damping of occuring power system oscillations . In spite of the importance of the load self-regulation effect there are existing nearly no reliable values on the quantity of the frequency and voltage dependcncc of the active and reactive power consumption. Most of the results published up to now are related to single consumers (Concordia and Ihara, 1982; EPRI, 1981). But applying synthetical methods to estimate the behaviour of whole load part systems is difficult because of the lack of knowledge on the consumers' configuration which also depends on scason and daytime (EPRI, 1987; ReiHing, 1983). But also the experimental identification of load part systems is combined with difficulties. A major problem is the generation of sufficient strong voltage and frequency deviations to stimulate thc load part systems which is to be investigated. Further problems are caused by the strong active and reactive power noise, which is superposed to thc system output signals . This noise oecurs from the continuous switching of consumers in the load part system. Changes in voltage may be gcncrated in a comparatively simple way (Ohyama er al., 1985), e.g. by switching off or on shunt reactors, because changcs in reactive power effect only a small region around the switching location and therefore induce regionally significant changes in voltage. Contrary to this the magnitude of fn;queney changes depend on the percentage of the active power changes in the whole power system. Therefore a stimulation of sufficiently high frequency deviations is not possible without impairing the power supply security, especially in casc of large intcr-

This paper describes the developped data acquisition and evaluation method as well as the identification results achieved by applying the method to eight load part systems . Based on these results the importance of the load self-regulation effect on the system control behaviour will be proved quantitativly. ") MODELLING OF THE VOLTAGE AND FREQUENCY DEPENDENCE OF LOAD PART SYSTEMS The great number of consumers being in operation in electrical load part systems can bc devided into five main groups: - uncontrolled-ohmic, -inductive, -capacitive and -motoric load portions as well as - a controlled load portion. From the view of power system control load part systems are dynamic loads fed from the 110, 220 or 380 kV level of the high voltage transmission network. Including the influence of the underlaying distrihution network in the ohmic, inductive and capacitive load portions a simplified load model can be derived as shown in Fig. 1.

tlf(t) t.u (t)

IndUl t tve

COpollt lv e

rnotOfll

y

' '--y--'

uncon tr o lled

controlled

If'k" tlP.(t) 1 . If'Mo·tlP_(t) l Iflto .tl0 L(t)I·IO, o· (;0c(t)l· I0Mo .(;O . (t)1

Fig. I.

789

.

P"' '''o Q"""o

Main load portion of a load part system

A good approach for the uncontrolled motoric portion load is found using a model of the asynchronous motor (Hall, 1993). As shown in Fig. 2a in case of a stepwise frequency decrease by -~f ~ the power consumption reduccs transiently about from ~pw (-0) over ~Pw(+O) to ~Pw(oo)1) This is caused by the rotation-speed dependent power consumption of the driven working machines as shown in Fig . 2c .

liQ _

a) Frequenc y depen d ence

Q"'f -

p

with

Cl!

TAM

ao f ~ (+O) f~ (-O)

kMqf , k Mqu ' kLqu T Mqf f'

b) Vol t aae depen d ence

c) Sp eed depen dent po wer and torq ue character is t ic

a = d p /dn

Worki n g m ac hines with !ransIQ1Qr i ~ mo t ion

fl - dm /d n

I

0

for lillrJ.i.o..Il. flo ws eg cal end e r

2

1

for 1ill!llil.ffit fl o w s eg cen tr ifugal pu m ps, fans

3

2

e .g. co n veyors. cr a ne s , e l evato r s

Fig. 2. Frequency and voltage dependence of the active power consumption of asynchronous motors driving different types of working machines

Using the equations for the active and reactive power consumption of the different load portions, linearizing on frequency and voltage, relating on the initial state and transforming into the Laplace-space one gets the following transfer functions:

For this purpose the line frequency and voltage - as input signals of the load part system to the investigated - and the active and reactive power as the resulting output signals are recorded by the self-acting data acquisition systems. The signals are sampled with a rate of 10 Hz and stored firstly in a ring buffer. At the same time frequency and voltage gradients are computed and tested whether the given trigger-thresholds for amplitude and time are overridden as shown in Fig. 3. In such a case the signals f(t), U (t) as well as P(t) and Q(t) are stored for the intervalllo-30s ~ t ~ 1o+60s on a harddisk.

.

Tpf

kpu

...---'----,

b) .Y2lliW

o)~

200 GW

2 GW power s ystem.

Interconnected Isolated

Tpu

t.u

M [mHz]

,..A-..

20

PRo+(a-l)ooPMO aP_ T,wPMO MO +s _ _ __ 2 +s2TI Po Po Po flU lif + I + s T) I + s T) 10

not stored

-"

"Fa

t [s]

( la) I)

-0,5

Per-Unit variables are defined as follows :

f'

=

f.; "

/JI

=

J:!. ,,' M;

load dependent parameters (Hall, 1993)

The object of the developped data acquisition and evaluation estimation method is the identification of load part systems on the basis of "natural" switching actions in the grid .

A voltage step by -~u...r- also leads to a reduction of the active and reactive power consumptions due to the quadratic power/voltage-relation of uncontrolled consumcrs . This fact is also demonstrated by the example of an asynchronous motor in Fig . 2b. Contrary to this, controlled consumers show - at least in stationary operation - a constant active and reactive power consumption . Short transient power deviations can be included in the uncontrolled motoric load portion .

Po

}

3 . AUTOMATIC MEASUREMENT OF "FREQUENC¥AND VOLTAGE-TRIALS"

(qualitative illustration)

liP

asynchronousmotor

Qo = QLO + Q co + QMO + Qcontr 0 will become zero in the case that load part systems are ideally compensated. As to be seen from eq . (1) the part transfer functions have a PDTI-behaviour. The denominator time constant with TI = ao . T AM is very small and can generally be chosen to TI = O. ls . This is admissible because the energy of the dela yed D-power pu Is is independent 0 f T 1 . Therefore only the numerator parameters kxy and T xy have to be identified .

f'

kpf

}

Therein the occuring power deviations are related - in case of the active power to the stationary initial state P ref = Po = PRO + P MO + PcontrO (2a) and - in case of reactive power to the stationary load of the consumers which are still not compensated, thus e.g. for cos ~L = 0 .78 to a reactive power reference of Qref = 0 .8 ' Po· (2b) Such a load-dcpcndent choice of the reference value is necessary because the stationary reactive power

p

~

dp/dn·, s. Fig. 2 l!cceleration time constant nominal slip

=

~

liT:

p - p. q =

- Po'

stored

~.; "= -u ,<, u.

Fig . 3. Criteria for the recording of measured signals

790

Corresponding to the activated trigger gradient thc stored data block is called "frequcncy trial" or "voltage trial".

load part system

III

urban network with industry

0,7

F

50 - 120

!1ay rc uthl D !mmcnreuth

25 - 90

urban network with industry and rural env ironment

D

25 - 75

urban network

D

25 - 140

LF !.,ouis!crt

Only components as - the frequency measuring board with a resolution of 0.4 mHz and - the filtering board to supress high frcquent noisc portions and to protect the inputs of the AID-converter board against voltage spikes as well as the measuring software have been developped by the authors . 23DV-l

evaluation range la)

load structure

IMWI

The digital data acquisition systems arc based on standard PCs which were expanded by the required process interfaces, see Fig . 4. As far as possible commercial components are used like: - a 16-bit-A/D-converter board and - a real time clock board .

11OOV- or

load range

ilK !1crlin-"

2

2,5

~reu7.berg

Ill) !!e i![clberg

2

urban network with service and commerc ial bU8iness

1111 !!amburgSlid

D

270 - 630

urban network with indu.try, among others: .... 200 MW electrolytical alu-plant

2

ilK !!eilbronnl

[)

75 - 260

rurnl environment with industry

I

D

50 - 160

ruml enviro nment. among others : .... plants for water supply with temporary 30 MW pwnp power

2

PE .!:ad erbom-Sud

70 - 255

industrial area with rural cnv iroruncnt

2

H ooll - ultl~pt'rldonl tH I It'I UIl\

~e~c~.

U, P, 0

~upfc rLcll

KN Stockach ~O!!.tan7.)

D

!ilsen

Isolated power system of West-Berlin LPO = 2GW

II

Fig . 5 . Characterization of the load part systems

FIQ 4

~-:ol ::ll- J"/.J<..-t

tiard ....or(' slfur l ur .. 01 Ihp 'iI'It o £h nq 0010

toq~

o;ys

T

Fig . 4. Hardware structure of the self acting data acquisition systems

J

0'

\ J

'

/'.-~_

c'

-.J _

I

\ J

-01!)

I

-.

"

+---r--.---'--~---

...L

The high resolution of the data acquisition boards is necessary, because in normal case - when frequency deviations of only fl.i = 50mHz/50Hz = 1%0 occur - the resulting power deviations arc in thc range of pcr millcs only . The data acquisition systems have been connected by means of isolation amplifiers to thc mcasuring equipments inside the substations feeding the invcstigated load part systems . In case of decentral supply of a load part system separate data acquisition systems are necessary for each feeder. The recorded data are synchronized using the stored time marks derived from the official german radio clock signal DCF77 by the realtime clock board ,

_.1 _

...L

tJ. f meas I::::.U mpo -:.

6PuSObl. ~ yslem

Load por t

6Pmeos

..

- ) tJ.O meos .,

f

4. IDENTIFIED LOAD PART SYSTEMS

tJ.(J nOISE' ---

L

As to be seen in Fig. 5 seven load part systems of different size in Germany and one in France have been investigated up to now . Fig. 6 shows as an example two of the acquired trials in a per-unit scale. It is conspicuous that the power plots nit) and qi(t) are quite different. This is partly caused by the different voltage and frequency signals, which stimulate the resulting usable output signals but mainly by the strong power pertubations fl.Pzi(t) and fl.q.i(t) which arc superposed to the usable output signals .

,

'-- 1% 1

For the identification powerful load part systems have been selected because the superposed load noise decreases in the mean with I~, i.c . with thc squareroot of the load . Nevertheless the load powcr noise is about 0.75%,,1' in rural load networks and can grow up to 1.5 %I'P in industrial networks .

60uOOblP

)

UO

T

",J

0

0

, L

~QI%I

-~l

OS

~~,...: l r, t)

20 l le.1

-.

J

0

20 l Isl

Fig . 6. Example for recorded measurings, load part system "PE" 791

T ~

...L

5 .3 Cyclic noise reduction and identification method

5 . EVALUATION METHOD

Due to the fact that the intensity of the frequency input signals is only in range of 0.1 % whereas the intensity of the voltage input signals is about 1% the evaluation of the frequency trials has to be done most carefully. Therefore the general procedure of the "cyclic noise reduction" is explained by the way of the active power/frequency transfer behaviour Fp~s).

5. 1 Identification of the different part transfer functions

For a simple and efficient evaluation the four part transfer functions, which are derived from eq. (1) and grafically illustrated in Fig . 7, are to be identified seperatly . This is permissible because on the one hand the p-canonical structure of the load model causes that the active power behavior (continuously lined) and the reactive power behaviour (dashed lined) are completely decoupled. 6. _ f _m_e_a.s_ _

--l~ F. ( ) _ kpr + sTpr pr s -

L'

(

)

s

" Pll

Evaluation step 0 Firstly a rough identification of each frequency trial is carried out to find out the noise/signal ratio of each trial. Therefore the Pl!Iameter ~r j is varied to minimize the mean quadratic error c ~, see Fig. 8, using the yet identified parameter values of the voltage dependence and rough values for the time constants .

6.P mod

l +sT 1

= k »u+ sTpu

1 +sT 1

6f~

I~t

, _. _- - - , 6. u

~

L'

( .) = kq u+sT'l u

('q u L _

m ea s

s

_

_

1+ sT _

_1.

f--

~

€ (t )

6f; ( I )

\

.,,~6.Q mod

Fig. 7. Load model structure On the other hand the fact is used that the recorded trials can be devided into two groups with different input stimulations: - 'Voltage trials' which are the result of reactive power system disturbances have strong deviations in voltage but no changes in frequency and - 'frequency trials' which are caused by active power system disturbances and show approximately as great frequency deviations as voltage deviations. Therefore voltage parameters can bc identified from the voltage trials without knowledge of the frequency parameters. To identify the frequency parameters from the frequency trials thc voltage parameters yet identified have to be used.

Fig. 8 . Estimation of the pertubation level for single frequency trials The mean quadratic error ~ gives an estimation of p; err j . Relating it on the stationary frequency deviation Llf j (00) the cffective factor of the noise/signal ratio results to Llk

5.2 Ensemble averaging The main procedure to reduce the noise/signal ratio superposed to the output signals is the ensemble averaging. Therein the disturbed measuring signals of the frequency or voltage trials respectively - recorded under same conditions - are averaged without any loss of the usable input/output information by:

-

Lax .(t ) _ i I

-'

Evaluation step 1

(3a)

Ll~1 (I) + Ll~2 (I )

with X .(I) - -, X. -,

Lllf • (I ), 1I(r ), p(1 ), q(t ) {

X. -,

(4)

i

To reduce the noise/signal ratio a cyclic ensemble averaging is performed using at each time the first "i" sorted frequency trials, i.e.

N

..!.N

Pz-if, Llf • (00)

which corresponds to the standard deviation of the identified parameter values k j • For the elimination of frequency trials with strong noise/signal ratio the trials are sorted on increasing values of Ll~rr j , see. Fig 9a. The corresponding rough parameters values k; are shown in Fig. 9b, forming a totally unusable cloud of points. -+ From this bad parameter behaviour it is to be seen that an identification of single frequency trials without using ensemble averaging is impossible in practice.

Generally the identification method is based on a discrete least squares algorithm .

Ai (t) =

=

-if,

beginning with

Ll!2 (t )

over

Ll!i (I) = . . .

until

Ll!N(/) =

Ll~1 (t ) + .

(3b)

Xi = reference value for trial i. With this ensemble averaging the noise influence is generally reduced by the factor of I/VN' because of the stocastical independence of the individual noise signals.

2

N

As shown in Fig . 9d the parameter values identified in this way deviate much less. The remaining noise factor Llk ZI - shown in Fig. 9c - has a distinct minimum in the range of 55 5 il 5 160 averaged frequency trials. It is obvious, that the parameter value k I estimated over this range has the smallest noise influence and therefore is the best.

The noise signals however do not contain only high frequency portions but also low frequency portions. To have an efficient noise reduction on the one hand - as many trials as possible have to be averaged and on the other hand - those trials which are extremely disturbed have to be eliminated.

Evaluation step 2 The evaluation of an already nearly true parameter k I 1.15% in step 1 offers the possiblility to eliminate all those frequency trials which are strongly disturbed and therefore

792

a) Single perturbation level t.kZi Cl) Avp.ras,wd frequency trio ls

increasing sorled

,of~----\

t.kzi

20

;'

"

;"

10

-12J

,

,

o L -_

_ _ _ _ _ ------,- _

,

6u

.

JI

o

, evalUAtion atep I

,

evalUAtion atep 11

I

b) Para meter values ki, identified for every trial X, (t)

kll(i)

-

k,

I

10

, .,.. ." . ,

.t :.

"

M"

.',

: ,

0"0

ot;·:'..~ ·";::;":S:::;:'-~.'-~·q~'. ;:'c'."c::::"':::":;..-' 1 kI

..<.: .......:-.'.:.:-:,.: .'; :.: iIT

- 10 "

r - ...... - - - -

. " -,

. ,

, ,

-2 0

r•.-.

l.J) Ave r aged VOltage tri als

20

-- 2 0

,',

I

c ) Total perturbation level evalualed by ensemble 8VCTl1ging of i tr iu ls xi (l)

Fig. 10.

,

" "- ' , ... I ~-r, 't.k -Zll ;

O. 35

o

as Nu = 106 voltage trials . It is obvious that the ensemble averaged input and output signals are smoothed very much and do now allow an accurate identification of the load parameters. This can be seen among others by the - dashed lined - active and reactive power signal curves, simulated by the identified load model. The evaluated parameter values are presented in Fig . 11 completely for the load part system PE and in Fig. 12 and 13 partially for the most important parameters of all of the investigated load pa rt systems.

30 80133

d) Parameter valu es evalualed by e nsemble uveraging of

kI( i )

I

lrill ls xi ( l)

kll(i)

1.15

1. 2

O h-~----~-----4I

t. i I

I

o

I

I

,

,

,

/?J';'-:k11 I t.ill

I Nil

6 . 1 Frequency dependence of load part systems

ill

For the frequency parameters, i.e. the gains k"f and k f but also the time constants Tpf and T qf , a remarkabte dependence on the load characteristic can be noticed. This fact is caused in accordance to eq. (1) by the different portions of ohmic load PRO and motoric load P MO which change with day-, week- and season-time. Therein the increase of the motoric load portion is marked in Fig. 11 and 12 by dashed arrows. The daytime dependence is based on the fact, that within the majority 0 f the load part systems the motoric load portion is greater at daytime than during the night. Contrary to this the mostly lower parameter values in the evening are caused by the enhanced ohmic load portion due to lighting, TV, cooking and electrical heating, but also because the load range "evening" contains the weekend days with strongly reduced industrial production. In an equal way the reduced frequency dependence during winter load range can be explained by the increase of ohmic load due to electrical heating and lighting. Averaging the parameter values identified for the differcnt load part systems one gets.: as shown in the lower part of Fig . 13 - a mean value of k pf l: "" 1%1% for the frequency dependence of active power. The maximal frequency depcndence results for working days 1£ k pf D = 1,2 %1 %, the minimal value for the winter time to k pfw =O ,6%1%.

Fig. 9. Cyclic method for noise reduction and parameter identification outside of a given reasonable parameter interval of

k:r-t.r,::s;

k; ::s;

Ensemble averaged measuring signals (-----) and identified model signals (- - -) "PE"

k: r + Ak: .

With the remaining frequency trials a new eyelie ensemble averaging and identification is done, which leads to the paramters k n(i) shown in Fig . 9d. These parameter values are nearly constant in a wide range of 30 to 80 trials . So the final parameter value can be determined to kl/ = 1.2 %1% With this step by step evaluation method all of the four part transfer functions can be identified . In each evaluation step the dynamic parameters T xy are identified, too . 6 . IDENTIFICATION RESULTS The results which are achieved by the evaluation of the eight load part systems will be presented subsequently in a compressed form . Fig . lOa and b show the ensemble averaged measurings of evaluation step 2 regarding N f = 133 frequency trials as well

6 .2 Voltage dependence of load part systems The voltage dependence of the activ£. power consumption has been evaluated in the mean to k pu l:= 1%1% what's

793

a) Gains

b) Time constants

IEQ] [ill]

Tpt

-1,8

T qf

[sI

III U

c::

III

"c::

III

0-

III

">.

kqf 1

u

c::

0.1

-1.8

-4 .1

( ?/ ?l 0 +--""-t--r---'-T777r-r---.-r-

III

(sI 2.0

;:l

- I

0"

III

....

- 2

(,.,

-3

Mark of parameters appearing in fig. 11. 12, resp. 13

Tpu III

( sI

U

c::

III

"c:: III

0 .1

0-

0 .1

0 ,1

0 .1

0 .1

0.1

O~~~~~~~~~~---

Mark of parameters appearing in fig. 12 and 13

III

"

kqu

III

Tqu

(:r./ :r.l

tU) (\)

(sI 2

!:! o

>

o

Fig. 11 :

w

Co mplete pa r a m e l e r values of lhe load part sysle m "PE" a) Fre quency dependence

(h ] !!llhl

b) Vcllalle dependence

2'+--~~------~"nin,

16+-------. Fr

kpf (:>:/? l

81

HD

HH

Sa

So

12

{d J

IWI

LF

It ~ o~

0 .6

~

~

n 1 - l.~,",8 ~ ~L O_·'...L:0=.2=,-_,-.: ..>.L_L~_ · 6. . J. . o_4--,

HO

0'

~

HK

0,6

~

kpt· ~

L: PE

o

Cro "

O.g

.

o

[

N

-

u o

~

-3.0

~ ~ ~__

l A.

1,1

o

o

o 1,1

o

0 ,9

o

0,6

1,2

U -.-~2,,2 U

0, 8

1,1

D

- 1,0

0,9

0 2.3 0

'

-3, 0

~

~

KN

~L--_-L!_~-L_ _'---L~~2~_L~ _·-Lo_.-9-,

-2 ,5

0,8

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1.1

61

u u

-2,6

~

0.8

Q.u,

t o.1

1.5

u

1,1

81

BK

[Ij

_

kpf,u

- 2,2

0,8

~~

2

Pl

_

0.9

PE

kqu

kqf

kpf

§.ummer

~b1JL O_'8. . .L_'.2. . .L_". . .L_""~,",.1",,,--_L[k_ l5--,=0='2: :1 ~ 08

8K

!inter

··k.nd

Worktna ~·Y

Wo

. I

c) Self rellula lion effect of the load

o

n 0 n ,l

0, 8

o

~ ~ __

PE 1,7

Fig. 12 : Day ti m e - a n d seasondepe n de n t k p t - va lu es o f a ll loa d pa r t sys t e m s

1,1

____~[]~____~ ____ ~__~LJL-~LJ~

1,0

w

0,5

Cl

o o o 1, 0

2

0 ,9

1,1

·n

~ Fi g. 13

794

-2. 3

1,5

o D D 1,0

1,2

D w

Mea n ga in va lue s of a ll loa d part systems, d ay Ume- a nd s e a son-independent

nearly equal for all load part systems, sce Fig . 13, and only shows little dependence on the load characteristic as to be seen in the lower half of Fig . 11 . The only exception is the load part system HH. There the small voltage dependence of 0.6%/% is caused by the mainly industrial load configuration with a great portion of controlled consumers . The vol~e dependence of the reactive power results in the mean to k 1:= 1.7%/%. However the values for the single load part systems differ - as to be seen by Fig . 13 - due to the degree of reactive power compensation. In case of optimal compensation the factor kqu will become zero, as to be seen by eq. (lb) . Also the very small values of the voltage dependent time constants in Fig . lIb arc in agreement with eq. (I).

0) Bloc k di ag ram

d em an d ed s pin n ing re s erve

HP turb in€'

6 .3 Self-regulation effect of the load As in case of decreasing frequency the load part systems consume more reactive power - sce the negative ~Ival~es in Fig. 11 and 13 - additional voltage drops occur With decreasing frequency at the input of the load part systems. This effect can distinctively be seen by the ensemble averaged curves of the frequency trials in Fig . lOa . Attaching this change in voltage - also caused by the consumers - to the original change in frequency the resulting overall input/output behaviour ~f.u = t.P/t.f, that means without elimination of the voltage influence t.U, corresponds to the load self-regulation effect. Averaging all of the load part systems the mean value results to k pf.u = 1.5%/% , sec Fig . 13e . This value is 0.5%/% greater than the "pure" voltage corrected frequency dependence of active power ~f= I %/%. But also when the frequency dependence of the active power is lower, e.g. in winter..:.. this additional frequency influence is active and leads to k pf.u w= 1.2 %/% in comparison to the pure frequency dependence of k pfW =0.6%/%.

reh eoter / LP turbine

regional po wer sys tem

b ) Ma xim al frequ en c y dr op

0.2G W 20GW

O.15G W

2.0GW

nat ional gri d 1.25 GW 50GW

2. 5 GW 50G W

5GW 50G W

3.75 GW 50GW

/':,.~

/':,. f mox

[mH zJ

2.5

~

7.5

5.0

10.0 [%]

0 15285

-380

-500

'D
.2

6 Ul

c 0

7. IMPORTANCE OF THE LOAD SELF-REGULATION EFFECT ON THE SYSTEM CONTROL BEHAVIOUR

·.9

- 1000 After the experimental parameter identification of the frequency and voltage dependence has been performed for the different load part systems the influence of the load behaviour on the system control shall be considered .

-

I kpf.u= I 0

7.1 Influence of the active power/frequency behaviour on interconnected as well as on isolated power systems

- 1500

",

st ep 1

\

\

\1

}

v

C

:J

CJ" .~ C

re

c

;:

Ul

CL

'2 ~% %

with spinn ing reserve accord ing t o DVG

Due to the DVG and UCPTE agreements (DVG-Berieht, 1991; Hagenmeyer, 1986) on "system orientated criteria for the behaviour of power plants" each westcuropean utility in the operation of the interconnected power system should be able to activate a power reserve of 1.25 % PN within 5 seconds and 2.5% P N within 30 seconds.

Fig. 14 .

Influence of the self-regulation effect on the interception of the line frequency at t.fmax

by the primary controlled power plants . The self-regulation effect of the load will become important in case of stronger system incidents when the power plants reach their power generation limitations leading to greater frequency drops. Therefore frequency drops of t.fmax < 1-IOOmHz I oeeuring in the westeuropean power system during normal operation only lead to a load reduction of t.PL = k..f,u . t.fma/fO = 0,25 to 0,375%, for a . self-regulation eft'~et of ~f.u = I to ~ .5% %. . However during the great system ll1cldent 111 France 111 February 1985 with a power deficit of about t.Pt. = 5 GW / 180 GW eo 2.8% the consumers participated with t.PL, = 0.76 to 1.15% in the interception of the line frequency at t.fmax= -0.38Hz corresponding to the upper equation (Welfonder et al., 1987).

If such a mean second reserve power of 2.5 % is hold ready by throttling the HP-turbine valves in the steam power plants their efficiency will be reduced by about 0.25%, and due to this the power generating costs will increase by about I Mill . Dollars per GW and year. Additional costs do occur as the throttled steam power plants can't be operated with full load furtheron. Therefore the utilities don't hold ready more second reserve power than required . The frequency behaviour fulfilling the agreement is demonstrated in Fig . 14b as a function of the deficit power and the load self-regulation effect. The drawn maximum frequency drops t.fmax have been evaluated by simulation on the basis of a simple summarie dynamic model, shown in Fig. 14a.

In case of severe power system disturbances of ~4% - e .g . occuring in case of part system separation or when a power plant breaks down during isolated operation - the load will participate with t.PL =2 to 3 in an interception of the line frequency at t.fmax=-IOOmHz .

As to be seen from this grafic, small power deficits in the westeuropean interconnel·ted power system, e.g. sudden switching off onc or two power plants, arc mainly regulated 795

a) Power system configuration

7.2 Influence of the damping of power system oscillations

Bayreuth (BI)

Load part systems do also participate in damping power system oscillations and this in two different ways . On the one hand the consumed active power changes - corresponding to the load self-regulation effect ~r.u - proportionally with the motion of the line frequency. Due to this the active power consumption acts 90° advance and therefore with a damping influence on the occuring generator power movement. On the other hand benefit is made from the dependence of the consumed active power on voltage k"u when using power system stabilizers. In this case the ac[uators on the generator side and - in case of static V AR compensators those in the network too are activated by additional signals in such a way that the voltage and therefore the active power consumption is changed - if possible also 90° advance - to the oceuring generator power movement.

• Investigated load port s ys tems

The significance of the load part system behaviour to the damping of system oscillations shall be demonstrated at the example of an oscillation oecured on January, 5th 1990 in the UCPTE power system . This event has been recorded by all of the installed data acquisition systems (Welfonder, 1992) and has been simulated by means of the detailed westeuropean power system model of the University of Stuttgart (Welfonder er al. , 1987), see Fig. 8 . When applying the identified realistic frequency and voltage dependent load behaviour the power oscillation cuts out - in agreement with the measurements - with a damping factor of d "" -0.05 1/s, see Fig. 15a and bl . However using idealistic loads, i.e. pure impedance loads with ~r=O and ~u=2%/% at all of the 689 load nodes regarded in the westeuropean power system model then a positive damping factor of d ",,0.05 occurs leading to an instable oscillation, see Fig. 15bll .

b) Damping

Measuring Simulation - -

2) Idealized load 1) Real is tic load stot. consumer d~ . consumer (only volt .-dep.) (frequ .- o. volt.-dep.)

6~ ~

1 v

F-\-+,r++-t+H~:O

~ + ,05

...... x..... x.....x...... x..... .

7.3 Influence on the reactive power/voltage behaviour Also in case of stronger regional deficits of the reactive power the load part systems participate in the interception of the voltage especially when the overexcitation limiters of the generators have become active. Then in case of a voltage reduction, of e.g . .:iu =-10% and a load factor of kqu = 1,7%/% the reactive power consumption decreases by .:i'lL = k u . .:iu = -17% . For details on t11e regulation of the tap changing transformers on the generation side as well as for the required blocking of the tap changing transformers on the load side sec (Welfonder, 1992).

Fig . 15 .

Damping of the oscillations in the westeuropean power system for different load types

9. REFERENCES Concordia, C . and A. Ihara (1982) . Load Representation in Power System Stability Studies. IEEE Trans. PAS-lOl, No. 4. DVG-Bericht (1991). Das versorgungsgerechte Verhalten der thermischen Kraftwerke. DVG Heidelberg. EPRI (1981) . Determining Load Characteristics for Transient Performance. Final Report EPRI Project 849-1. EPRI (1987). Load Mode1ing for Power Flow and Transient Stability Computer Studies. EPRI-Project 849-7 . Hagenmeyer, E. (1986). Operational Objectives and Criteria for Power System Operation. ELECTRA Nr. 108, S. 127-156. Hall, B. (1993) . Expcrimentelle Untersuchungzur frequenzund spannungsabhiingigenLeistungsaufnahmeelektrischer Verbraucherteilnetze. Dissertation University of Stuttgart. Ohyama, T., A. Watanabe, K. Nishimura and S. Tsuruta (1985) . Voltage Dependence of Composite Load in Power Systems. IEEE Trans. PAS 104, No. 11. Reil\ing, Th. (1983) . Dynamische Modelle der Lasten elektrischer Energieiibertragungssysteme. Dissertation University of Dortmund. Wc1fonder, E., Th. Schiifer and H.P. Asal (1987). Control Behaviour of the West European Power System Simulated on the Basis of a Detailed Dynamic Model. 10th IFAC World Congress, Munich, Germany Wclfonder. E. (1992) . Constrained Control Concepts in Power Plants and Power Systems for Avoiding Emergency Conditions . IFAC Symposium on "Control of Power Plant and Power Systems", Munich, Germany.

8. SUMMARY Based on the experimental investigation carried out during several years in eight load part systems reliable parameter values for the frequency and voltage dependence of the active and reactive power consumption could be determined. The self-regulation effect of the load is about 1.5 %/% averaged over all the year and about 1.2%/% during the winter time, caused by the enhanced ohmic load portion. This frequency and voltage dependence of the load part systems reaches dominating influence whenever being active alone and not additionally to the power plant control. This happens generally in case of great active or reactive power deficits when the turbine and generator actuators are blocked after reaching their limitations and therefore great frequency or voltage deviations respectively are induced; but it will also happen during normal operating conditions, in case of power system oscillations. Then the turbine actuators are mostly too slow for damping the oseillatoric motion and the generator actuators activated by hard tuned voltage controllers do even work in the opposite sense causing a destabilizing effect. In both cases the existing frequency and voltage dependence of the load part systems is very useful for stable power system operation .

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