21
Chapter-1
INTRODUCTION
22
1.1 HIGH VOLTAGE DIRECT CURRENT TRANSMISSION
With the increase in size and complexity of Power Systems, the
problems associated with long AC bulk power transmission like
reactive power support, system stability etc have also increased. A
search for more efficient mode of transmission has led to the
development of DC transmission.
The DC transmission requires conversion of power at its two ends.
Conversion from AC to DC will take place at the sending end rectifier
station and conversion back to AC will take place at the receiving end
inverter station. The converters are static, using high power thyristors
and the physical process of conversion is such that the same station
can switch from rectifier to inverter by simple control action, thus
facilitating the power reversal.
Advantages offered by HVDC Transmission over AC transmission are
as follows [1]:
•
No reactive line/cable losses
Long cables possible, lines cheaper
•
No synchronizing power
Easy to connect AC systems
•
Controllability
Perfect for power transactions
•
SSC does not increase
Upgrading of AC breakers not necessary
23
With system interconnections, following are the possible advantages
with HVDC:
•
Interconnector rating is determined based on the real demand of
transmission capacity with DC. Rating of AC interconnector
must be higher than the real demand on power exchange.
•
Increment in power transfer is easily possible with DC.
•
System operator alone can determine the power exchange
between the two systems.
•
Power oscillation damping and voltage control can be obtained
with DC.
•
DC acts as a shield against stability problems, voltage collapse
and cascading blackouts.
•
Under emergency conditions, pre-determined mutual support
between the systems is possible.
Conventional applications of HVDC transmission are as follows:
1. For transmitting power through large water bodies spanning
30Km or more. For such distances AC transmission is
impossible because of the high capacitance of the cable which
requires intermediate compensation stations.
2. For asynchronous interconnections. For inter connecting two or
more AC systems which are operating at different nominal
frequencies and for stability reasons.
24
3. For transmitting bulk power through long overhead lines. HVDC
transmission is economical as compared with AC transmission
for distances exceeding 600 km.
For
the
above
transmission
is
mentioned
an
conventional
economical
and
applications,
eco-friendly
option.
HVDC
With
development in HVDC technology, liberalization of electricity industry
around the world, and the efforts to preserve the environment are
demanding HVDC systems as the preferred alternative to high voltage
AC systems in many other situations [2]. Details are as follows:
•
Transmission of power over small distances (less than 60 Km)
and at lower power levels (less than 200MW) is economical with
the new technologies such as polyethylene DC cables and VSC
based HVDC systems.
•
With liberalization of electricity industry, transmission has
become a contracted service and there is no scope for deviation
from contracted technical and economic norms. Better control of
the power lines is possible with HVDC and is therefore a better
alternative for providing transmission services on contractual
basis.
25
•
The concept of trading to the electricity sector resulted with
liberalization. This has resulted in bi-directional power transfers
based on market conditions. Bi-directional power flows are
possible with HVDC systems.
•
When the transmission service was owned by the government,
land acquisition and obtaining rights-of-way was relatively
easier. With deregulation, acquiring land and/or obtaining
rights-of-way has become a significant portion of the project’s
costs. Since HVDC transmission requires much less land/rightof-way for a given power rating, it is more economical than AC
transmission.
•
To build a power link in environmentally sensitive areas such as
national parks and protected sanctuaries, HVDC transmission
systems is the only alternative because of its lower foot print.
1.2
POWER SYSTEM STABILITY
For a given initial operating condition, power system stability is
defined as the ability of an electric power system to regain a state of
operating equilibrium after being subjected to a physical disturbance,
with most system variables bounded so that practically the entire
system remains intact [3].
The power system is a highly nonlinear system which operates in a
constantly changing environment; loads, generator outputs and
operating parameters change continuously. When subjected to a
26
disturbance, the stability of the system depends not only on the type
of disturbance but also on the initial operating condition. Stability of
an electric power system is thus a property of the system motion
around an initial operating condition. At the equilibrium point all the
opposing forces that exist in the system are equal.
Power systems are subjected to a wide variety of disturbances. Small
load changes occur continuously. The system must be able to adjust
to these changing conditions and operate satisfactorily. It must also
be able to withstand to severe disturbances, such as a short circuit on
a transmission line or loss of a large generator. A large disturbance
may lead to the isolation of the faulted elements. For a given physical
disturbance, a power system may be stable for an operating point and
unstable for another. Design of power systems to be stable for every
possible disturbance is impractical and uneconomical. Selection of
these design contingencies is based on their probability of occurrence.
The response of the power system to a disturbance may involve much
of the equipment. For example, a fault on a critical element followed
by its isolation by protective relays will cause variations in power
flows, network bus voltages, and machine rotor speeds. Power systems
experience fluctuations of small magnitudes continuously. When a
power system is subjected to a specified disturbance, it is assumed
27
that the system is initially in a true steady-state operating condition
for assessing its stability.
The ability of synchronous machines of an interconnected power
system to remain in synchronism after being subjected to a
disturbance is termed as rotor angle stability. It depends on the ability
to restore equilibrium between electromagnetic torque and mechanical
torque of each synchronous machine in the system. Increasing
angular swings of some generators is an indication of instability of the
system and this may lead to their loss of synchronism with other
generators.
Loss of synchronism can occur between one system and the rest of the
system, or between groups of machines, with synchronism maintained
within each group after separating from each other.
1.2.1 control Strategies for Improvement of System Stability
Numerous control schemes have been proposed to arrest loss of
synchronism phenomena. They can be broadly classified into two
groups, i.e., preventive control and emergency control. Preventive
control anticipates events to ensure that the power system is to
withstand the most severe disturbances; emergency control is
executed immediately after the disturbance. To design effective
emergency control schemes much research has been carried out. As
28
an example, load shedding scheme based on the topological and
dynamic characterization of stability boundary is proposed in [4] for
an emergency generator. On-line emergency control strategy for
generator shedding based on PMU measurements is proposed in [5].
Generation rescheduling and/or generation tripping developed in [6] is
also an emergency control scheme. Generation shedding based on real
time closed loop emergency control schemes are presented in [7]-[8].
Corrective actions based on equal area type criteria together with realtime measurements are computed in the above mentioned methods.
To maintain stability, emergency control techniques involve actions on
generators and loads. Fast valving and braking resistors [9], fast
excitation controllers [10], or tie-line reactance controllers [11] could
also be used as means for emergency control of transient stability. In
this context, FACTS devices such as TCSC, UPFC etc. [12]-[27] also
play a vital role in the improvement of system stability.
In power systems where HVDC links have been installed, a better
alternative could be to use the converter controls as emergency
control means. As AC/DC conversion involves no inertia and power
settings of HVDC links can be changed quasi-instantaneously [28],
modulating of active power flow through the HVDC-links has been
proposed to improve power system stability. Modulation techniques
for stability purpose are presented in [29]-[37].
29
1.2.2
DC Power Modulation
With HVDC systems rapid control of transmitted power is possible.
They have a significant impact on the stability of the associated AC
power systems. Proper design of the HVDC controls is essential to
ensure satisfactory performance of the overall AC/DC system like
damping of power swings, enhancement of dynamic stability and
optimal
power
flow
control
[38-61]. The principle involved is to
control DC power in response to signals from the AC network. The
control of DC power acts in a similar way to a phase angle
regulating
transformer
of
an
AC
system
which
can influence
power flow with just voltage magnitude control. Dynamic control of
HVDC
systems can
be realized
only
with
the
availability
of
suitable overall control strategies and this thesis deals with the
derivation
of such
strategies. The impact of traditional HVDC
controls on stability and some new control strategies in the analysis of
stability problems are primarily studied in this thesis.
1.3 ENHANCEMENT OF STABILITY USING HVDC CONTROLS
1.3.1 Introduction
In improving the performance of large interconnected power systems,
the controllability of HVDC link plays an important role. To achieve
the desired results, control systems must perform appropriately for
various disturbances and system conditions. In the following sections,
the basic control philosophy and the auxiliary controls that can be
30
used with HVDC systems for improving the system performance are
discussed.
1.3.2
Basic Control Principles
The HVDC system is basically constant-current controlled for the
following two important reasons:
•
To limit over current and minimize damage due to faults.
•
To prevent the system from running down due to fluctuations of
the ac voltages.
It is because of the high-speed constant current control characteristic
that the HVDC system operation is very stable [1]. The following are
the significant aspects of the basic control system shown in Fig 1.1,
the details of which are explained as under:
Fig 1.1: Basic control scheme for HVDC system
31
a) The rectifier is provided with a current control and an α-limit
control. The minimum α reference is set at about 50 so that
sufficient positive voltage across the valve exists at the time of
firing, to ensure successful commutation. In the current control
mode, a closed loop regulator (which is a proportional plus
integral regulator also termed as Type-0 controller) controls the
firing angle and hence the dc voltage to maintain the direct
current equal to the current order. Tap changer control of the
converter transformer brings α within the range of 100 to 200. A
time delay is used to prevent unnecessary tap movements
during excursions of α.
b) The inverter is provided with a constant extinction angle (CEA)
control and current control. In the CEA control mode, γ is
regulated to a value of about 150. This value represents a tradeoff between acceptable VAR consumption and a low risk of
commutation failure. Tap changer control is used to bring the
value of γ close to the desired range of 150 to 200.
c) Under normal conditions, the rectifier is on current control
mode and the inverter is on CEA control mode. If there is a
reduction in the ac voltage at rectifier end, the rectifier firing
angle decreases until it hits the αmin limit.
At this point, the
rectifier switches to αmin control and the inverter will assume
current control. These are illustrated in Fig 1.2.
32
Fig 1.2: Actual converter control steady state characteristics
d) To ensure satisfactory operation and equipment safety, several
limits are recognized in establishing the current order as shown
in Fig 1.3 i.e., maximum current limit, minimum current limit,
and voltage-dependent current-order limit (VDCOL) and are
briefed as follows:
i)
Maximum current limit:
The maximum current limit is usually limited to 1.2 to 1.3
times normal full-load current, to avoid thermal damage
to valves.
ii)
Minimum current limit:
At low values of current, the ripple in the current may
cause it to be discontinuous or intermittent. This is
objectionable because of the high voltages (Ldi/dt)
induced in the transformer windings and the DC reactor
33
by the high rate of change of current at the instants of
interruption.
At low values of direct current, the overlap is small.
Operation is objectionable even with continuous current if
the overlap is too small. With a very small overlap, the two
jumps in direct current at the beginning and end of
commutation merge to form one jump twice as large,
resulting in an increased stress on the valves. It may also
cause flashover of protective gaps placed across the
terminals of each bridge.
iii)
Voltage-dependent current-order limit (VDCOL) :
Under low voltage conditions, it may not be desirable or
possible to maintain rated direct current or power for the
following reasons:
When voltage at one converter drops by more than about
30%, the reactive power demand of the remote converter
increases, and this may have an adverse effect on the ac
system. A higher α or γ at the remote converter necessary
to control the current causes the increase in reactive
power.
The
reduced
ac
system
voltage
levels
also
significantly decrease the reactive power supplied by the
filters and capacitors, which often supply much of the
reactive power absorbed by the converters. At reduced
34
voltages, there are also risks of commutation failure and
voltage instability.
These problems associated with operation under lowvoltage conditions may be prevented by using a “voltagedependent current-order limit”. This limit reduces the
maximum allowable direct current when the voltage drops
below a predetermined value. The VDCOL characteristics
may be a function of the ac commutating voltage or the dc
voltage.
Fig 1.3: Steady-state V-I characteristic with VDCOL, minimum
current limit and firing angle limits
Higher-level controls may be used, in addition to the above basic
controls, to improve AC/DC system interaction and enhance AC
system performance. All schemes used to date have used the above
modes of operation for the rectifier and the inverter. However, there
are some situations that may warrant serious investigation of a
35
control scheme in which the inverter is operated continuously in
current control mode and the rectifier in α-minimum control mode.
1.3.3 Enhancement of AC System Performance using HVDC
Controls
In a DC transmission system, the basic controlled quantity is the
direct current, controlled by the action of the rectifier with the direct
voltage maintained by the inverter. A DC link controlled in this
manner buffers one AC system from disturbances on the other.
However, it does not allow the flow of synchronizing power which
assists in maintaining stability of AC systems. The converters appear
to the AC systems as frequency-insensitive loads and this may
contribute to negative damping of system swings [1]. Also, the DC
links may contribute to voltage collapse during swings by drawing
excessive reactive power.
Supplementary controls are needed to exploit the controllability of DC
links for enhancing the AC system dynamic performance. There are a
variety of such higher level controls used in practice whose
performance
objectives change
with the
characteristics of the
associated AC systems. Reasons for using supplementary controls for
DC links are as follows:
36
•
Improvement of oscillation damping
•
Improvement of transient stability.
•
System disturbance isolation.
•
Frequency control of small isolated systems.
•
Dynamic voltage support and Reactive power regulation.
HVDC links can be controlled in a number of ways by adding
supplementary control schemes to the basic control structure. The
purposes of these supplementary control schemes are multiple and in
general they have been developed to satisfy the particular condition of
each HVDC project [62-64]. Therefore, there is no general control
scheme
applicable
to
all
systems.
The
supplementary
control
structure associated with the HVDC link is helpful in improving the
damping of the overall system.
With proper design of supplementary control loop of the HVDC link,
the damping ratio of the system can be increased to a safe value,
which cannot be attained solely using power system stabilizers. The
electromechanical inter-area oscillations can be reduced effectively
with power modulation through the HVDC link.
The control signals used tend to be unique to each system under
consideration. Generalized control schemes applicable to all systems
have not been developed so far. To modulate the DC quantities, the
37
supplementary controls make use of signals derived from the AC
system. The modulating signals derived from the AC system can be
system frequency, voltage magnitude and angle, and line flows. The
control signal selection depends on the system characteristics and the
desired results.
In order to augment transient stability limit large signal modulation is
used, thereby improving system security. Large changes in the power
flow in the DC link are required to compensate for tripping of loads,
generators or AC ties. The limits imposed by ratings of the link usually
do not curtail the benefits of power modulation, while overload
capability in DC links is useful. Hence, significant improvements can
be expected out of the use of DC links in emergency control. The rapid
response of DC link controllers helps in arresting large deviations in
the frequency by matching generation with the load in the area in
which the DC link is connected [65]. Some of the aspects in the
application of power modulation in a DC link are discussed in the
following sections.
1.3.4
Control Signals
In large multi machine power systems, there are many modes of
generator rotor oscillations. The stabilizing control is used to damp
one or more of the predominant modes of oscillation. The controller
can introduce new undamped modes if proper care is not taken at the
38
design stage. By increasing the bandwidth of the controller some of
the difficulties can be overcome but it can lead to noise interference. It
is desirable to obtain control signals locally. Control signals that can
be used for supplementary controllers are as follows:
•
Rotor frequency of adjacent generator
•
Converter bus frequency
•
Parallel AC tie line power or current
•
Phase angle changes in the AC system [66].
In the case of a single machine system, the above signals work
satisfactorily. An ideal control signal should have only the components
of oscillation which are to be damped. The extraneous components
such as at supply frequency and harmonics, sub-synchronous
frequency oscillations, local mode oscillations when the damping is
desired
for
inter-area
modes,
can
pose
problems.
These
are
suppressed by suitably designed band pass or notch filters. Control
signals derived from relative power angle deviation, relative speed
deviation, and acceleration of the various machines in the system may
be used for DC power modulation with multi machine systems.
Different combinations of these signals may also be employed
depending on the type of system. This means it involves derivation of
signals from local as well as remote machines. Fig 1.4 illustrates the
application of the above control signals for a typical ac-dc system.
39
Fig 1.4: AC-DC system controller showing the modulated converters
1.3.5
Types of Controllers
The evolution of present day control strategies adopted for power
system applications can be traced from conventional or classical
control strategies followed by optimal, robust, adaptive and intelligent
control techniques. Characteristic features of these controllers are
explained below.
1.3.5.1
Conventional Control Strategies
The design objective of a linear controlled process is to have the
controlled variables behave in certain desirable ways. The problem
involves the determination of the control signal, u(t), over the
prescribed time interval so that the design objectives are all satisfied.
40
One of the commonly used controllers is a PID controller, which
applies a signal to the process that is a linear combination of
proportional, integral and derivative of the actuating signal. Since
these signal components are easily realized and visualized in the time
domain methods, PID controllers [67] are commonly designed using
time-domain methods. The integral and derivative components of the
PID controller have individual performance implications.
The PD controller is an anticipatory control i.e., by knowing the slope,
the controller can anticipate direction of the error and use it to better
control the process. The function of derivative control is to measure
the instantaneous slope of error signal, e(t), and take a proper
corrective action before the excessive overshoot actually occurs.
Intuitively, derivative control affects the steady-state error of a system
only if the steady-state error varies with time.
The PI controller improves the relative stability and steady-state error
at the same time, but the rise time is increased.
The problem of
selecting a proper combination of KI and KP is more acute than in the
case of the PD controller. Best features of each of the PI and PD
controllers are utilized in the PID controller.
41
For the design of controllers in power systems which are basically
non-linear, the classical control theory using frequency domain
methods can be employed by linearizing the system around an
operating point. The objective of damping controllers is to provide
adequate damping torque on the rotor at the dominant mode of
oscillation, without sacrificing synchronous torque. The optimization
of the controller performance is done by trial and error. The main
objective in the design of controllers is to adjust the proportional,
integral and the derivative gains of the plant to operate reliably under
all possible operating conditions.
The time-domain representation of each of the above mentioned linear
controllers are given by the following equations:
• PI controller
u = KP e+KI ∫edt
(1.1)
• PD controller
u = KP e+KD
(1.2)
• PID controller
u=KP e+KI ∫edt+ KD
(1.3)
Where KP, KI and KD are proportional, integral and derivative gains, e
is the error signal and u is the control signal.
1.3.5.2 Optimal Controller
The optimal control theory is essentially based on minimizing a
chosen performance index subject to constraints in the system. In
most of the applications of the optimal control theory to power
42
system problems, a linearized system model is considered. These
control strategies are optimal only for the linear system and not
for the actual nonlinear system. The optimal control theory has been
applied to the design of HVDC modulation controllers [68]-[72].
However, the optimal controller designed for one operating condition
may not work satisfactorily for other operating condition. Besides
such controls need accurate mathematical model of the power
systems.
Consider a large-scale linear system given by (1.4)
= A x(t) +
(1.4)
where, x(0) = x0
x(t) Є Rn is a state vector, ui(t) Є Rmi is a control vector, and
= m.
The information available to the local controller is
assumed to be
yi(t) = Cix(t) , i = 1,2,.......,k
where, yi(t) Є Rri is a local output vector, and
(1.5)
=r.
The response y(t) is due to nonzero initial conditions that are caused
by disturbances. The primary objective of the design is to damp out
the response due to initial conditions quickly without excessive
overshoot and oscillations.
43
The local control ui(t) and the local output Yi(t ) are related by the
following expression:
ui(t ) = EiYi(t ) , i = 1, 2 ..............k
(1.6)
where, Ei is a time-invariant gain matrix.
Method I:
The first method is based upon computing the complete state
feedback and
reducing it to a
specific control action along with a
decentralized structure. In this case the performance index of the
following form is introduced.
dt
J=
(1.7)
where Q = Q′ ≥0, R=diag (Ri)>0, i=1,2,…......,k; and to determine
the optimal control law which minimizes (1.7) subject to dynamic
constraints :
= A x(t) + Bu(t)
where ,
B=[B1, B2,.....Bk]
(1.8)
&
U′= [Ul′, U2′,.......Uk′ ]
The solution is given by (1.9).
u(t) = F x(t)
F = R-1B′ K
(1.9)
Where, K is the positive definite solution of the algebraic Riccati
equation:
A′K + KA - KBR-1B′K + Q = 0
(1.10)
44
Having the full state feedback, the next step is to reduce this to
a specified decentralized structure, i.e., a control given by (1.6).
Method II:
The second method is based on minimization of the de-centralized
quadratic performance index
dt
J=
(1.11)
Q = Q′ ≥ 0, R i =Ri ′ > 0, and i = 1, 2,.....,k
Both approaches lead to the control law of the form
ui(t ) = Eiлi x(t )
(1.12)
where, the values of the matrices Ei and лi depend on the specific
approach chosen.
1.3.5.3
Robust Controller
The main objective of a control engineer is to design a system that
works satisfactorily in real environment. The control system must be
able to withstand to the changing operating conditions as they are
likely to change with time. Robustness is the particular property of a
control system to operate properly in realistic conditions i.e., the
controller must perform satisfactorily for a family of plants. A robust
controller is a controller that can satisfactorily control a class of
system with specified uncertainties in the process model, and the
problem of designing controllers that satisfy robust stability and
performance requirements is called robust control.
45
For satisfactory operation of modern power systems, controllers have
to guarantee robustness over a wide range of system operating
conditions. Hence, robustness is one of the major issues in the design
of power system controllers. Attempts have been made to apply robust
control theory to the design of HVDC modulation controllers [73]-[79].
Apart from linear, optimal and robust controllers, adaptive controllers
can also be employed which are known to give better performance.
1.3.5.4 Adaptive Controller
An adaptive controller is defined as a controller with adaptable
parameters and a mechanism for adjusting the parameters. Adaptive
control theory is an attractive control technique for HVDC systems
because the dynamic response of the HVDC system changes with
variations in the operating conditions.
References [80]-[84] report the investigations carried out with adaptive
techniques which use modern control theory for developing the
necessary modulation signals to respective control strategies. In the
design of the controller, these techniques need accurate mathematical
models of the system under consideration. It becomes difficult to
develop precise mathematical models for the practical power systems
as they are complex and highly non-linear. Hence, mathematical
based schemes face some disadvantages. In order to overcome these
46
disadvantages, many applications of artificial intelligence have been
investigated in different areas of power systems.
1.3.5.5 Intelligent Control Schemes
The extensive application of AI techniques to a wide range of power
system problems has been witnessed in the literature. These
techniques fall into four categories: expert systems, artificial neural
networks, fuzzy sets, and heuristic search. ANN applications are more
numerous than fuzzy sets or heuristic search and expert system
applications are more advanced than the other categories.
Expert systems: These systems are computer programs that possess
expertise in a given area. This expert knowledge is normally stored in
one of many forms, including rules, decision trees, models, and
frames. Many of the expert systems abilities like decision making,
archiving knowledge, heuristics or judgment, matches with different
application areas of power systems. Expert systems are particularly
useful for these problems when a large amount of data must be
processed in a short time period.
Knowledge acquired from human experience can be used to solve
complex problems of power systems and in taking decisions on its
planning, design and operation with the aid of expert systems. They
are best suited for real time control and operations planning. Design
47
of HVDC controls [85]-[88] is one such area where expert systems find
application.
Artificial Neural Networks : (ANNs) are biologically inspired systems
that transform a set of inputs into a set of outputs through a network
of neurons, each of which generates one output as a function of its
inputs. The inputs and outputs are usually normalized, and the
output is a nonlinear function of the inputs that is controlled by
weights
on
the
inputs.
The
network
can
be
supervised
or
unsupervised and it learns these weights during training. Numerous
ways of connecting the network and its training methods are available.
The power system problems that are best suited for ANN applications
are classification or encoding of an unspecified nonlinear function.
ANNs have the ability to generate quick results soon after receiving
the inputs. This feature of ANNs is best suited for real time operation
of power systems. Also they are most suitable for finding quick
approximations
of
complex
numerical
calculations
and
to
classification related problems. ANNs also have been applied to the
design of HVDC modulation controllers [89]-[91].
Heuristic Search: Simulated annealing and Genetic algorithms are
two forms of heuristic search, which solves optimization problems by
randomly generating new solutions and retaining the better ones. In
48
searching
processes,
generation
of
solution
is
important.
The
generated solution should lead to a better solution which can
minimize the chances of settling around a local minimum. Both the
above mentioned techniques can be applied to optimization problems
with arbitrary objective functions and constraints. These search
techniques find application in HVDC controls [92]-[94].
Fuzzy Logic: Compared with the traditional logic systems, fuzzy logic
is very close to human thinking and natural language. Fuzzy control
which is based on this fuzzy logic, provides an effective means of
extracting the inexact nature of the real system. FL controller is
based on a set of linguistic control rules and is related by the dual
concepts of fuzzy implication and the compositional inference rule.
The above mentioned controller provides a sequence of operations to
be performed to convert the linguistic control strategy based on expert
knowledge into an automatic control strategy. The results obtained by
the FLC are more accurate than those obtained by the conventional
controllers.
These fuzzy logic based controllers are well suited for
applications involving complex analyses or when the available source
of information involves uncertainty or inexactness.
Fuzzy logic is appropriate in many areas of power systems where the
available information involves uncertainty. With fuzzy logic both the
input and output data are translated to symbolic form from numeric
49
form and the control knowledge is specified as fuzzy rules. Fuzzy logic
theory is used for real-time control operations and operations
planning.
In the design of a fuzzy logic controller, mathematical model of the
system is not needed. To generate a desired control objective, it
requires a qualitative knowledge on the behavior of the system. And it
is very easy to add expert / heuristic knowledge about the system
behavior into the controller structure. The change in parameters or
operating conditions will not affect the performance of the fuzzy logic
controller. The applications of FL based controllers in the power
systems have been an active research area for the last two decades
[95, 96].
To modulate the DC power, Fuzzy logic based controllers can be
applied to HVDC systems. This can be achieved in response to a
control signal derived from the AC system. The effectiveness of the
control can be enhanced by increased overload rating of the converters
which permit short – term overloads. Thus, the rapid controllability of
power in a DC link can be used to advantage in improving the
transient stability of the AC system in which the DC link is embedded.
The power flow can even be reversed in a short time (less than
0.25sec).
50
1.4
THESIS OBJECTIVE
For a power system with an embedded HVDC link, the fast acting
converter
control offers a
feature for hierarchical control
of
the
system following a system disturbance.
Many
researchers
investigated
the
fuzzy
logic-based
controller
applications in the HVDC transmission systems [97-108], but the
application of such a controller in the HVDC systems has been
studied in a limited manner mostly confining to SMIB systems. The
objective of this research work is to develop fuzzy logic based control
schemes for more general multi machine power systems, which are
simple and effective in damping the oscillations.
1.5
WORK PRESENTED IN THE THESIS
The work presented in this thesis mainly focuses on application of
different types of auxiliary controllers employing different types of
control signals derived from the ac system. Studies are made on single
machine infinite bus system as well as on multi machine system.
Initially, a single machine system is considered with parallel AC and
DC transmission link, having a Type–0 Auxiliary controller and a
Proportional Integral type current controller for the HVDC system. The
control signals derived from variation of active power in the parallel
AC line, generator speed deviation, generator power angle deviation
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and generator acceleration. These are used individually and in
combination. The signals derived from the machines and their
combinations may be viewed as P, D, P-D, P-I and P-I-D controllers
derived from speed deviation.
Later, a typical multi machine system is considered with similar
current controller for the HVDC system and auxiliary controllers with
control signals derived from local as well as remote machines. The
signals used are average of relative power angles, average of relative
speed variations and average accelerations of different generators. In
addition, the signal derived from adjacent AC line power flow is also
used. These signals are used individually and in combination. In both
the above cases, the gains associated with the error signals are chosen
by trial and error.
Finally, application of Fuzzy Logic based modulation controllers have
been studied for multi machine system. This study has been carried
out in two ways:
In the first case, fuzzy logic approach has been used to tune the gains
of PID controller. The gains of the three error signals are adjusted in
every sampling interval in accordance to a set of linguistic control
rules and in conjunction with fuzzy logic. In the second case, the
inputs to the fuzzy logic modulation controller are taken as error and
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its derivative and the output of this controller is used as the auxiliary
signal. The error signal used in this case is the average of relative
speed deviations of all the machines in the system. The performance
of this controller is compared with the conventional PID controller.
1.6 OUTLINE OF THE THESIS
Chapter wise summary of the work done in the thesis is briefly given
below:
In chapter 1, the salient features of HVDC transmission highlighting
its role in the improvement of AC system stability are presented.
Literature survey reviewing different DC power modulation controllers
is presented.
In chapter 2, transient stability analysis of AC-DC system is
discussed. AC/DC load flow study which is a prerequisite for the
transient stability analysis is discussed in detail. Eliminated variable
method which dispenses with the DC variables thereby modifying the
AC Jacobean matrix is used in the load flow study. Models of
Generators, Loads and HVDC systems used in the stability study are
described.
In chapter 3, a single machine infinite bus system with parallel AC
and DC transmission link is considered and applications of different
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types of auxiliary controllers for improvement of system stability are
discussed. In this analysis different control signals derived from
generator speed deviation, generator power angle deviation, deviation
of generator accelerating power and variation of power in the parallel
AC line are used individually and in combination. The gains
associated with these control signals are chosen by trial and error.
In chapter 4, the analysis carried out in chapter 3 is extended to a
multi machine system with an embedded DC link. Effects of different
control signals like average of relative power angles, average of relative
speed variations, average accelerations of different generators and
variation of adjacent AC line power flow are analyzed individually and
in combination. In this analysis also, the gains associated with the
control signals are chosen by trial and error.
In chapter 5, Fuzzy Logic Controller application has been studied for
the multi machine system presented in chapter 4. A variable gain
Fuzzy Logic controller is developed for the system which adjusts the
gains associated with the control signals in every sampling interval in
accordance to a set of linguistic control rules and in conjunction with
fuzzy logic. The performance of this controller is compared with that
obtained in chapter 4.
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In chapter 6, a new fuzzy logic control scheme is developed for the
same multi machine system presented in chapters 4 and 5. This
scheme makes use of average of relative angular speeds of all the
machines and its derivative as inputs and output as auxiliary
stabilizing signal. The performance of this controller is analyzed.
Conclusions arrived from the above analysis on single and multi
machine ac-dc systems are presented in chapter 7.