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ISSN 2250-2459
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An Overview of AGC Strategies in Power System
1Naimul Hasan
1
Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, India
Abstract — This paper presents a comprehensive literature
review of the Philosophies of automatic generation control (AGC) of power systems. The Present article is aimed to highlight the various control and structural aspects of AGC used in the power systems. The AGC schemes based on power system models and control strategies are reviewed. The work on AGC incorporating parallel AC/HVDC links as system interconnection has also been reviewed. Also in this paper work reported in the literature in the area of automatic generation control has been reviewed critically.
Keywords —Adaptive control, EHVAC/DVDC transmission links Interconnected power systems, Optimal Control, Suboptimal control.
I.
I
NTRODUCTIONThe concept of AGC was first developed through a
control loop meant only for a control area. The control
objective was to drive measured control area net
interchange to a given scheduled value and to raise and
lower contact closures according to actuating signal
through governor speed changer motor was the control
mechanism. The same raise or lower pulse was
simultaneously broadcasted to each unit on control area
even though the duration of each pulse could manually be
adjusted to recognize individual size and/or ability to
regulate. Generation was blindly raised or lowered to force
net interchange to the desired value. If unit generation
output was telemetered to the dispatch office, it was
trended on a strip chart and used for area load calculation
but not used for any unit oriented control loop.
To complete the design of this early area controller, a
frequency dependent bias for the scheduled net interchange
was developed that modeled the change in actual area net
interchange caused by area governor response and load
change due to deviation from nominal frequency. This
allowed AGC (supplementary control) to position unit
governor speed changers so that when system frequency
returned to nominal, the area’s generation and load and
hence actual interchange would adjust to the proper level
via the governor control; i.e., without need for additional
supplemental control. This area tie-line bias control
mechanism has been in constant use ever since with slight
modifications for continuous time error correction.
Through the years, unit output control loops were added
to AGC, and power plant computers that control unit output
and digital governors were also added to the overall control
scheme but the basic goal of performing area closed loop
control has remain unchanged.
The AGC schemes have evolved over the past six
decades. This is based on tie-line load bias control concept,
and there are two variables of interest namely, frequency
and tie-line power exchanges. Their variations are weighted
together by a linear combination to a single variable called
ACE. The continuous advancement in the design and
implementation of AGC strategies has enabled power
engineers to deal AGC problem more efficiently and
effectively.
II.
A
NO
VERVIEWO
FAGC
S
CHEMESAlthough there is a heap of research papers available in
the literature relating AGC problem of power systems.
They dealt various aspects of AGC schemes demonstrating
the superiority of one scheme over the others. However,
there are few notable contributions of the early stages of
AGC, which have set the landmarks in the development of
AGC schemes. Therefore, it becomes necessary to cite their
contributions separately here.
Perhaps, Cohn [1-6] was the first to propose the scheme
for the control of bulk power transfer in interconnected
power systems based on tie-line bias control strategy,
particularly the considerations for deciding the frequency
bias setting and techniques for time error and inadvertent
interchange correction for large multi area power system.
Later in [7], he has presented a comprehensive study on;
extensive growth and expansion of interconnected electric
power systems, the related need to regulate generation in
the constituent areas, and the power flow between them and
equitable, reliable and economic system and area operation
pertaining to the evolution of AGC.
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Quazza [11] has proposed an approach for transient
analysis of interconnected power systems and design of
frequency and tie line power regulators. C. W. Ross [12]
reported a comprehensive direct digital load frequency
controller for power systems. The AGC regulator design
techniques using modern control theory enable the power
engineers to design optimal control system with respect to
given performance criteria. Elgerd and Fosha were the first
to present their pioneering work on optimal AGC regulator
design using this concept [28]. Carpentier [13] has added
new dimensions in potential applications of modern control
theory in AGC as opposed to conventional methods. A
paper consisting of informative and pioneering ideas
relating to AGC problem of power systems was reported by
N. Jaleeli et. al. [14].
III.
D
EVELOPMENTSI
NC
ONTROLS
YSTEMD
ESIGNC
ONCEPTSThe developments in the area of AGC of interconnected
power systems have been augmented through the
developments in control system designs. Most of the AGC
designs are based on the application of techniques
developed in the area of control system designs. These
developments in the area of control system designs are as
follows;
The first era of classical control theory, which deals with
the techniques developed before 1950. Classical control
embodies such methods as Root Locus, Bode, Nyquist and
Routh-Harwitz. These methods have in common the use of
transfer functions in the complex frequency domain,
emphasizes on the graphical techniques, the use of
feedback, and the use of simplifying assumptions to
approximate the time response. A major limitation of
classical control methods was the use of single-input,
single-output (SISO) methods. Also the use of transfer
functions and frequency domain limited to linear
time-invariant systems.
The second era of control systems is known as an era of
modern control which refers to state-space model based
methods developed in the late 1950s and early 1960s. In
modern control, system models are directly written in the
time domain. Analysis and design are also carried out in the
time domain. State space model based methods removed
the limitations of classical control. Modern control
provided a lot of insight into system structure and
properties, but it masked other important feedback
properties that could be studied and manipulated using
classical control.
During the third era of the 1970s and 1980s, a number of
methods have emerged that were considered to provide
solutions to uncertainty problem of the systems.
These techniques known as robust control are a
combination of modern state space and classical frequency
domain techniques. Other advanced techniques in control,
such as optimal and adaptive control, are also formulated in
state space. More recent trends in the science have been
towards intelligent control systems that tend to use both the
ideas of conventional control as well as methods such as
fuzzy logic, Petri nets, search and genetic algorithms and
neural networks.
Following these developments in control systems, many
AGC schemes have been proposed in the literature as their
applications to power systems.
IV.
C
LASSICALC
ONTROLB
ASEDAGC
S
CHEMESA fundamental concept in classical control is to describe
closed-loop properties in terms of open-loop properties,
which are either known or easy to measure. For instance,
Nyquist, Bode, and Root Locus plots are the examples of
classical control concept, which are drown based on
open-loop transfer function. Due to the interaction of the control
loops in a multivariable system, each
single-input/single-output (SISO) transfer function can have acceptable
properties in terms of step response and robustness, but the
coordinated control action of the system may not be
acceptable. In literature, a limited work has been reported
concerning AGC of interconnected power systems using
classical control theory [15-27]. Also the load frequency
control system is investigated using root locus techniques
by J. E. Van Ness [15] and W. R. Barcelo [16].
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V.
AGC
S
CHEMESB
ASEDO
NM
ODERNC
ONTROLC
ONCEPTSThe modern power systems are input and
multi-output type systems. The classical control theory, which is
capable to handle single-input and single-output systems,
becomes entirely powerless for such systems. One of the
developments in the field of modern control theory is in the
direction of its application in optimal control. The AGC
regulator design techniques using modern control theory
enable the power engineers to design optimal AGC with
respect to a given performance criteria. In literature,
volumes of research articles are reported using various
aspects of modern control concepts.
5.1
Optimal AGC Schemes
The application of modern control theory for designing
the more efficient AGC controllers for an interconnected
power system has been the subject of many publications
over the past three decades. Considerable interest has been
shown during the last three decades through application of
modern linear optimal control theory for arriving at more
efficient AGC regulators for interconnected power systems.
Elgerd and Fosha were the first to present their pioneering
work on optimal AGC regulator design using this concept
[28]. Since then, a wide variety of research articles on
optimal AGC of power systems have been witnessed [18,
21 29-60].
An advanced version of load frequency control law
based on optimal control strategy was developed by Glover
and Schweppe [61]. The derived control law was found
capable to reduce transient frequency oscillations and also
the number of control signals sent to powerhouses. A linear
model of an interconnected power system in discrete mode
incorporating dead band dynamics was used for the
investigation.
H.G. Kwatny et. al. [62] have proposed an optimal
tracking approach for the design of load-frequency control
system. The optimal control law is linearly proportional to
all system states as well as integral of area control error. A
new design procedure for load frequency control which
satisfies all classical requirements, as well as some
additional requirements on the feedback control structure is
given by Geromel, et al. [63].
5.2
Sub-Optimal AGC Schemes
The implementation of optimal control requires the
measurement of all the state variables of the system, which
may not always be possible in practice and such regulators
impose practical problems in implementation.
Therefore, the idea of sub-optimal AGC regulator design
was evident to circumvent this problem. Many aspects of
sub-optimal AGC regulator designs for power systems have
been considered in the publications [42, 56, 64-71].
In [72], authors have proposed a suboptimal controller
design technique such that the proportional part of the
regulator is a linear function of a smaller number of states
of the system plus integral function of the area control error
(ACE). The proposed suboptimal control law was obtained
by eigenvalues grouping technique and has shown the
feasibility of the design technique of the sub-optimal
regulator for load frequency control of power system
consisting of non-reheat reheats thermal turbines. S. S.
Choi [74] discussed a design of an LFC using the feedback
of only the directly measurable system state variables.
Sub-optimal AGC regulators based on decentralized control
strategy are also proposed in the literature to circumvent
the limitations imposed by AGC regulator designs based on
centralized control strategy. P. Kumar et. al. [70] designed
AGC regulators for hydrothermal power system based on
decentralized control strategies. O. P. Malik et. al. [71]
presented a sub-optimal load-frequency control for
hydrothermal power systems. The authors have shown that
the sub-optimal control with feedback of some, but not all,
of the remote area state variables is a feasible alternative to
the optimal control, whereas local control without feedback
of any remote state variable is inadequate for stabilizing the
system. A sub-optimal control method using the
area-decomposition technique to the multi-area power system
LFC is presented by Yoshibumi in [69].
Sub-optimal AGC schemes have also been reported
using the concept reduced order modeling of the system.
Elangovan et al. [64] proposed a method by which a
suboptimal control policy of a given linear system is
derived using its simplified model whose order is less than
that of the original system. The AGC of a multi-area
interconnected power system using reduced order model
has also been investigated in [73].
5.3
Centralized and Decentralized AGC Schemes
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The main limitation of the works presented on AGC
considering centralized control strategy is the need to
exchange information among control areas spread over
distantly connected geographical territories along with their
increased computational and storage complexities [44, 73,
77-79]. A wide range of research papers on decentralized
AGC control strategy for large scale power systems with
continuous and discrete time system models have appeared
in the literature [45,48, 50, 53, 70,71,82, 80-94].
A decentralized AGC regulator has been proposed by
Elemetwally and Rao 40 [48] assuming a constrained
structure with a minimum error excitation concept. A
decentralized sub-optimal load frequency controller
considering minimum error excitation principle for a
two-area hydrothermal power system is proposed in [88] by O.
P. Malik et al.
5.4
Intelligent AGC Schemes
A number of research articles are reported in literature
regarding the applications of neural networks in power
system control [95-110]. In the recent past, many studies
exploiting fuzzy logic concept in AGC regulator design
dealing with various aspects of fuzzy logic concept have
been appeared in literature [111-128].The frequency error
and the change in frequency error are considered as inputs.
J. Talaq et. al. [129] have proposed an adaptive fuzzy gain
scheduling scheme for conventional PI and optimal AGC
regulators. The development of AGC schemes using ANN
and fuzzy set theory to utilize the novel aspects of both in
single hybrid AGC system design for power systems has
also been mooted by researchers through articles
[130-136]. Another intelligent technique, genetic algorithms
(GAs) are the most popular and widely used to solve
complex non-linear optimization problems like other
computational intelligent systems such as neural networks
and fuzzy systems. In [137-142] the applications of GAs
for AGC of two-area interconnected power systems are
reported.
5.5
Other AGC Schemes
Besides the AGC schemes which have been overviewed
above in this chapter, there are many other important AGC
schemes which are reported in the literature
143-157[219-233]. In following paragraphs, the important and remaining
AGC schemes are reviewed in brief.
Most of the AGC schemes presented so far have been
formulated considering linear power system models.
However, like other physical systems, power systems are
also highly non-linear in nature. AGC schemes
incorporating the system non-linearities in overall system
modeling are reported in literature [144,147, 151-155].
One of the most important non-linearities in AGC of
power systems is the presence of generation rate constraints
(GRC). A due space has been given by researchers in this
area also. A considerable number of articles have been
reported to propose AGC schemes for power systems
incorporating GRCs [19, 23,24, 159, 160,146,149]. The
researchers [158] have reported their work for the dynamic
stability analysis of a two-area power system consisting of
non-reheat turbines. They have studied the damping effect
on frequency and tie line power oscillations by varying the
load characteristics and excitation stabilizer parameters.
Recently the application of superconducting magnetic
energy storage [136] and capacitive energy storage [154]
devices to improve AGC performance has been proposed.
Investigations carried by Tripathi et al [153, 154] revealed
that improved dynamic performance of the system could be
achieved by simultaneous control of steam turbine and
energy storage device. However, due to limited energy
storage capacity, cost and complicated control, these
devices may play very limited role in AGC of large
interconnected power systems.
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