Implications of Frequency Bias Settings on AGC
Minh-Luan D. Ngo & Roger L. King
Department of Electrical & Computer
Engineering
Mississippi State University
Rogelio Luck
Department of Mechanical Engineering
Mississippi State University
Abstract
Reliability Council (NERC) has established two criteria for
the performance of ACE. These criteria are as follow:
This paper describes the effects the frequency bias
setting, B , har on the operation of Automatic Generation
Control systems that are operating with tie-linefrequency
bias control. Since B can not be continuously measured,
it must be estimated annually. The closer the frequency
bias setting matches the actual control area's frequency
response characteristic, the better AGC will pe,erform. In
order to minimize the estimating error of the frequency
bias setting, a better understanding of it is necessary.
1) A1 Criterion - Zero Crossing : "The A1 Criterion
requires that a control's area's ACE return to zero within
ten minutes of previously reaching zero." [41
2) A2 Criterion - Ld Compliance : "The A2 Criterion
requires that the average ACE for each of the 6 ten-minute
periods during the hour be within specific limit, referred to
as L,."[4]
Ld is calculated as follows:
L , = (0.025)AL + 5MW
Keywords: Frequency Bias,Automatic Generation Control,
Area Control Error
where AL can be one of following: [4]
1) The largest hourly load change (increasing or
decreasing) in the control's area Net Energy for Load
during peak demand.
2) The average of any ten hourly load changes (increasing
or decreasing) in the control's area Net Energy for Load
during a year.
The strategy of ACE provides a steady-state target
according to which a control area meets its own load
during normal conditions in the interconnection,
contributes to fquency regulation, and provides assistance
to extemal areas when necessary. A more detailed
discussion of AGC can be seen in [l]. If there is an overgeneration in any mea,ACE will be positive in that area,
and the action to be taken will be to reduce area
generation. On the other hand, if there is under-generation
in any area, ACE will be negative in that area, and the
action to be taken will be to increase area generation. ACE
is determined as follow:
1. Introduction
In actual power system operation, many meas are
connected to each other allowing the interchange of energy
for various reasons. However, each is responsible to meet
its native load with its own resources. In order for each
area to meets its long-term dynamic load, supplemental
control is applied to the speed governon of most
generators. The purpose of this control is to attempt to
match the moment-tu-moment load changes in the system.
The supplemental control is known as Automatic
Generation Control or AGC. AGC has the following
primary objectives: [l]
a) To maintain scheduled tie line interchanges between
areas;
b) To maintain scheduled system frequency error to zero;
c) To match generation to lod;
d) To economically dispatch area generations to minimize
operation costs.
ACB
. (2'' - T,) - 10 B (Fa - F,)
where
2. Area Control Error (ACE)
The state of the art in AGC is represented by tieline frequency bias control.[6] It is defined for a control
area as a mode of operation under AGC in which the Area
Control Error or ACE, represents the mismatch between
area load and generation. The North American Electric
a3
0094-2898/95$04.00 0 1995 IEEE
(1)
T, - actual net interchange
T, - scheduled net interchange
F. - actual frequency
F, - scheduled frequency.
B - area frequency bias constant (MWD.1 Hz numerically negative)
indicated by the additional power being exported out of
Area 1 and by the fact that the frequency is higher than the
scheduled frequency. The result is that Area 1 needs to
reduce generation and Area 2 needs to wait to see if the
problem is corrected.
As mention earlier B has to be estimated annually
because it can not be continuously measured. In equation
(2). the term lOB(f,-f,) is known as the area frequency
response. Without this term a control area will not be able
to distinguish between an internal or external disturbance.
For example, assume there are two control areas (1 and 2)
connected to each other via a tie-line as shown in Figure 1.
Also, assume both have the same the same generation and
l o d characteristics.
EXAMPLE 2
The same data in example 1 are assumed, except
fa = 59.99 Hz.
Solution
ACE1 = [110 - 1001 - lo(-100)(59.99 - 60) = 0 MW
ACE, = [-110 - (-100) - lo(-100)(59.99 - 60) = -20 MW
Figure 1
lines.
ACE, indicates that there is nothing wrong within
Area 1 and no actions is needed, However, ACE, indicates
that there is a disturbance in its area and action is needed.
The problem identified in this example is that Area 2 is
under generating. This is indicated by the additionalpower
being imported from Area 1 and by the fact that the
frequency is lower than the scheduled frequency. The
result is that Area 2 needs to increase generation and Area
Two control areas interconnected with tie-
Area 1 has agreed to sell 100 MW of power to
Area 2. Now assume Area 2 experiences a sudden load
increase of 30 MW. Since both areas have the same
generation characteristics, 15 MW of the 30 M W l o d
increase in Area 2 will be shared by Area 1. Area 1 will
now have an additional 15 M W exported via the tie lines.
Since Area 2 received an extra 15 MW from the tie lines,
it will only have to generate an additional 15 MW to
satisfy the 30 MW load increase. However, Area 1 is only
supposed to supply 100 MW, not 115 MW, to Area 2.
Now Areal has had to increase its generation by 15 MW
[3]. Now, with the area frequency response added to the
equation (2), the control areas will be able to determine if
a disturbance is intemal or external. The following two
examples will demonstrate the calculation of ACE with tieline frequency bias control.
1 needs to wait to see if the problem is corrected.
The last two examples have shown the importance
of the area frequency response term in AGC. A detail
discussion of Tie-Line Frequency Bias and the area
frequency response is the objective of the remainder of this
Paper.
2.1 Tie-Line Frequency Bias
When frequency deviates from the scheduled
frequency due to a load imbalance, all of the systems
within an interconnection area respond to stabilize the
frequency. The process of the systems responding to the
load imbalance is known as System Response to Frequency
Deviation Characteristic, SRC. In order for a unit to be
responsive to frequency deviation, the governor response’s
reserve must be available in both the raise and lower
direction. The deviated frequency will be stabilized, but it
will not be returned to the scheduled value. The control
area will monitor the frequency deviation and will take any
necessary actions to c o m t it, The control area will send
out control actions to adjust generation to return the
frequency back to the scheduled frequency. The control
area’s AGC uses SRC to determine whether the frequency
deviation is external ar internal to the area. If the deviation
is internal, the control m ’ s AGC should take action to
correct deviation. If the deviation is external, then no AGC
actions should take place. However, the control area
should continue to respond to the frequency deviation until
the external system corrects its imbalance and returns the
frequency to its scheduled value. Since the control area’s
EXAMPLE 1
The same two areas previously discussed are used.
The B term is assumed to be 100 MW/O.lHz. Area 1 has
agreed to sell 100 MW to Area 2 (Ts = 100). However,
the actual net interchange is 110 MW (”a = 110), and first,
let’s assume the actual frequency is 60.01 Hz (fa = 60.01).
Where is the disturbance?
Solution
ACE, = [110 - loo)] - 10(-100)(60.01 - 60) = 20 MW
ACE, = [-110 - (-100)l -10(-100)(60.01 - 60) = 0 MW
ACE, indicates that there is a problem in its area
and actions need to be taken to correct the problem.
However, ACE, indicates that its area has no disturbance
and no actions need to be taken. The problem identified in
this example is that Area 1 is over generating. This is
84
the system regulation directly.[5] It helps the generation in
regulating the load changes. A load change will produce
a frequency change with a magnitude that depends on the
droop characteristics of the govemor and the frequency
characteristics of the system load.
SRC is continuously changing and cannot be measured, it
must be estimated. The estimated value of SRC is known
as the Tie-Line Frequency Bias, B.[2] The closer B
matches with SRC, the better AGC will be able to
distinguish intemal and external disturbances and reduce
the number of unnecessary control actions.
NERC guidelines require that the annual estimate
of B be based on the average of the area’s SRC, fl, as
observed for past disturbances during peak hours.
Guidelines also require that the monthly average of IBI
should not be less then 1% of the control area’s annual
estimated peak loadJ41
3. Actual vs Estimated ACE
The actual errof between generation and load of an
area is the area’s actual ACE.[7] The estimated ACE is
calculated using the estimated values of the tie line
interchange, fiequency deviations from the nominal, and the
estimated frequency bias factor. It is this estimated ACE
that is used by AGC. When the fkequency bias of the
estimated ACE matches with the actual fkequency bias of
the area, the estimated ACE and the actual ACE are
identical.[3] Since the objective of AGC is to regulate
generation, its input should be the actual ACE. It can be
argued that integral action in AGC results in both actual
and estimated ACE being averaged to zero over time [7],
but the transient response of AGC can be significantly
degraded by errors in the frequency bias factor. For
example, variations in the estimated ACE can be much
larger than variations in the actual ACE, if the frequency
bias term in the estimated ACE is too large. Also, an
estimated ACE based on a constant frequency bias factor
is non-linearly related to the required change in generation
because the actual frequency bias facta is non-linearly
related to the operating state of the area, i.e., frequency and
load. Using an estimated ACE based on a constant
frequency bias setting as the system error in AGC
introduces an undesirable nonlinearity into the control
system.
In practice, the load frequency controller (AGC)
depends on the estimated ACE and, uses the system
frequency, the net tie line data, and the estimated value of
frequency bias as inputs. However, an AGC controller
based on the actual ACE would provide a better control
over the generatioddemand ratio and, therefore, have a
better control over the ACE obtained from equation (2).
2.2 System Natural Response Coefficient (p)
The value of area p can not be obtained
accurately. Area p is sensitive to the status of generation
and govemor response of on-line units, as well as the
frequency response of the total area load, all of which are
constantly varying. The number of unit governors coming
out of dead-band vary according to the upset size of the
predisturbance frequency. The coefficient, p, is negative
and is given in MWIO.1 Hz. A mathematical equation for
fl can be seen as follow: [3]
1
p . - + D
R
where
(3)
1/R - the generator regulation or droop
D - the load damping characteristic.
R is the steady state characteristic of frequency
and generated power. All of the system individual unit
droop characteristics are set to be about equal to minimize
turbine govemor oscillation. With the same droop, each
unit will share the system load change. This load change
is proportional to the individual unit’s M W rating.
The droops ideally range from 3 to 5 percent.
However, according to a recent EPRI survey, the true
measured droop characteristic of the generators actually
range from 6.9 to 12.2 percent.[8] These values are much
higher than the predicted range of 3 to 5 percent.
D is the relationship between the change in actual
load due to a change in frequency. It is expressed as
percent change in the fiial connected load divided by the
percent change in frequency.
The load damping
characteristic is an important factor on system stability. D
represents the self-regulating characteristic of load. It
means that when system load increases the frequency
decreases and the total load will respond to this effect by
a small decrease, causing the f d load to be less than that
at rated frequency. The load damping characteristic affects
4. Actual Frequency Response of a Utility
Using actual frequency data for the month of July,
1994 provided by Southem Company Services for the
Southern Electric System (SES), the estimated frequency
responses, 10B(f, - f,), were calculated. For 1994,SES
used a constant B term of 321 MW/O.lHz. The calculated
values are the average frequency responses over a thirty
days period. The calculated values of the frequency
response can be seen in Table 1.
Table 1 shows that the mean value of the
kequency response term of the ACE equation actually used
85
on the SES is less than 0.5 MW. This is as expected since
integral action of the controller should work to zefo out the
error. Note that 95% of the excursions for the month were
within 57.6 M W (i.e., two standard deviations). Note that
if the B setting was 10 percent too high (and NERC prefers
utilities to err towards supplying additional frequency
response), then the mean would worsen by 10 percent.
Also, note that two standard deviations in this case would
be 63.3 MW. Conversely, if the B setting was 10 percent
less than what is presently used we would see an
improvement in the inadvertent energy interchange due to
the system frequency contribution and an improvement in
the magnitude of the excursions.
H
1 1 I 1
Frequency Response Term of ACE
I SCS'sB 1 +lo% B I -10% B 1
I1
1
Standard
Deviation
-0.4909
-0.5399
-0.4418
28.7729
31.6509
25.8%1
characteristic of the generator.
Research is presently
ongoing to develop an on-line method of estimating a
utilities tie-line frequency bias term.
6. Acknowledgements
The research reported in this paper has been
supported by grant number ECS-92-16549from the National
Science Foundation and contract number RI' 8030-12 from
the Electric Power Research Institute. The data for the ACE
calculations was supplied by Southern Company Services.
7. References
N.Jaleeli, D.N. Ewart, and L.H. Fink, "Undemtandmg
Automatic Generation Contro1,"IEEE Transactions on
Power System, Vol. 7, No. 3 August 1992. pp. 11061122.
T. Kennedy, S. M.Hoyt, C. F. Abell, "Variable NonLmear Tie-Line Frequency Bias for Interconnected
System Control," IEEE Transactions on Power System,
Vol. 3, No. 3, August 1988, pp. 1244-1253.
A.J. Wood and B.F. Wollenberg, Power Generation,
Operation. & Control, John Wiley & Sons, 1984.
Table 1: Calculated Frequency Response with Different
B's for the SES July 1994 data.
North American Electric Reliability Council Operating
5. Conclusions
"Determination of Natural Frequency Response of a
Power System for Automatic Generation Control." A
Thesis of Jesus Jativa, University of Texas at Arlington.
The tie-line firequency bias of an interconnected
power system can be obtained through estimation of the
natural response of the system. The mismatch between
area's natural frequency response characteristic and the tieline frequency bias setting used in AGC is a major cause
of inadvertent energy interchange, system time deviation,
fighting among system control areas, and unnecessary
control actions. Therefore a better way for approximating
the B coefficient is needed to reduce the mismatch between
B and p. Also, with the introduction of Independent
Power Producers (IPP) selling power to utilities, existing
utilities have to be more concerned with the mismatch
between B and p. As more IPPs appear in the generation
mix, utilities inadvertently using power hthem may fmd
that paying power back to the grid will no longer be an
acceptable operational technique. The IPPs may very likely
ask the utility to pay back them back with money instead
of power, since the IPP does not have any native load.
A better approximation of the B coefficient is
possible, if the D coefficient from the system natural
response can be approximated through load modeling. This
is possible because D is not constant like the droop
Guides, Guide I. System Control, April 1. 1992.
"IEEE Standard Definitions of Terms For Automatic
Generation Control on Electric Power System." IEEE
Transactions on Power apparatus and System, Vol.
PAS-89. pp. 1358-1362. July/Aug. 1970.
S . Rahman and 0. Hazim, "A Generalized KnowledgeBased Short-Term Load-ForecastingTechnique," IEEE
Transactions on Power Systems, Vol. 8, N0.2, May
1993.
"Impacts of Govemor Response Changes on the
Security of North American Interconnections," EPRI
Final Report October 1992.