Abstract: Power-system stability improvement by simultaneous tuning of power system stabilizer (PSS) and a Static Var Compensator (SVC) based damping controller is thoroughly investigated in this paper. Both local and remote signals with associated time delays are considered in the present study. The design problem of the proposed controller is formulated as an optimization problem, and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. The proposed stabilizers are tested on a weakly connected power system subjected to different disturbances. Nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance conditions.
Abstract: This paper presents the coordinated controller design of static synchronous compensator (STATCOM) and power system stabilizers (PSSs) for power system stability improvement. Coordinated design problem of STATCOM-based controller with multiple PSSs is formulated as an optimization problem and optimal controller parameters are obtained using bacteria foraging optimization algorithm. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. The nonlinear simulation results show that coordinated design of STATCOM-based controller and PSSs improve greatly the system damping oscillations and consequently stability improvement.
Abstract: An adaptive dynamic cerebellar model articulation
controller (DCMAC) neural network used for solving the prediction
and identification problem is proposed in this paper. The proposed
DCMAC has superior capability to the conventional cerebellar model
articulation controller (CMAC) neural network in efficient learning
mechanism, guaranteed system stability and dynamic response. The
recurrent network is embedded in the DCMAC by adding feedback
connections in the association memory space so that the DCMAC
captures the dynamic response, where the feedback units act as
memory elements. The dynamic gradient descent method is adopted to
adjust DCMAC parameters on-line. Moreover, the analytical method
based on a Lyapunov function is proposed to determine the
learning-rates of DCMAC so that the variable optimal learning-rates
are derived to achieve most rapid convergence of identifying error.
Finally, the adaptive DCMAC is applied in two computer simulations.
Simulation results show that accurate identifying response and
superior dynamic performance can be obtained because of the
powerful on-line learning capability of the proposed DCMAC.
Abstract: This paper presents a simple method for estimation of
additional load as a factor of the existing load that may be drawn
before reaching the point of line maximum loadability of radial
distribution system (RDS) with different realistic load models at
different substation voltages. The proposed method involves a simple
line loadability index (LLI) that gives a measure of the proximity of
the present state of a line in the distribution system. The LLI can use
to assess voltage instability and the line loading margin. The
proposed method also compares with the existing method of
maximum loadability index [10]. The simulation results show that the
LLI can identify not only the weakest line/branch causing system
instability but also the system voltage collapse point when it is near
one. This feature enables us to set an index threshold to monitor and
predict system stability on-line so that a proper action can be taken to
prevent the system from collapse. To demonstrate the validity of the
proposed algorithm, computer simulations are carried out on two bus
and 69 bus RDS.
Abstract: Load balancing in distributed computer systems is the
process of redistributing the work load among processors in the
system to improve system performance. Most of previous research in
using fuzzy logic for the purpose of load balancing has only
concentrated in utilizing fuzzy logic concepts in describing
processors load and tasks execution length. The responsibility of the
fuzzy-based load balancing process itself, however, has not been
discussed and in most reported work is assumed to be performed in a
distributed fashion by all nodes in the network. This paper proposes a
new fuzzy dynamic load balancing algorithm for homogenous
distributed systems. The proposed algorithm utilizes fuzzy logic in
dealing with inaccurate load information, making load distribution
decisions, and maintaining overall system stability. In terms of
control, we propose a new approach that specifies how, when, and by
which node the load balancing is implemented. Our approach is
called Centralized-But-Distributed (CBD).
Abstract: One of the factors to maintain system survivability is
the adequate reactive power support to the system. Lack of reactive
power support may cause undesirable voltage decay leading to total
system instability. Thus, appropriate reactive power support scheme
should be arranged in order to maintain system stability. The strength
of a system capacity is normally denoted as system loadability. This
paper presents the enhancement of system loadability through
optimal reactive power planning technique using a newly developed
optimization technique, termed as Multiagent Immune Evolutionary
Programming (MAIEP). The concept of MAIEP is developed based
on the combination of Multiagent System (MAS), Artificial Immune
System (AIS) and Evolutionary Programming (EP). In realizing the
effectiveness of the proposed technique, validation is conducted on
the IEEE-26-Bus Reliability Test System. The results obtained from
pre-optimization and post-optimization process were compared
which eventually revealed the merit of MAIEP.
Abstract: Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, real-coded genetic algorithm (RCGA) optimization technique is applied to design robust power system stabilizer for both singlemachine infinite-bus (SMIB) and multi-machine power system. The design problem of the proposed controller is formulated as an optimization problem and RCGA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.
Abstract: This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.
Abstract: Three service providers in competition, try to optimize
their quality of service / content level and their service access
price. But, they have to deal with uncertainty on the consumers-
preferences. To reduce their uncertainty, they have the opportunity
to buy information and to build alliances. We determine the Shapley
value which is a fair way to allocate the grand coalition-s revenue
between the service providers. Then, we identify the values of β
(consumers- sensitivity coefficient to the quality of service / contents)
for which allocating the grand coalition-s revenue using the Shapley
value guarantees the system stability. For other values of β, we prove
that it is possible for the regulator to impose a per-period interest rate
maximizing the market coverage under equal allocation rules.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.
Abstract: This paper shows how we can integrate
communication modeling into the design modeling at early stages of
the design flow. We consider effect of incorporating noise such as
impulsive noise on system stability. We show that with change of the
system model and investigate the system performance under the
different communication effects. We modeled a unmanned aerial
vehicle (UAV) as a demonstration using SystemC methodology.
Moreover the system is modeled by joining the capabilities of UML
and SystemC to operate at system level.
Abstract: The main objective of this paper is to investigate the
enhancement of power system stability via coordinated tuning of
Power System Stabilizers (PSSs) in a multi-machine power system.
The design problem of the proposed controllers is formulated as an
optimization problem. Chaotic catfish particle swarm optimization
(C-Catfish PSO) algorithm is used to minimize the ITAE objective
function. The proposed algorithm is evaluated on a two-area, 4-
machines system. The robustness of the proposed algorithm is
verified on this system under different operating conditions and
applying a three-phase fault. The nonlinear time-domain simulation
results and some performance indices show the effectiveness of the
proposed controller in damping power system oscillations and this
novel optimization algorithm is compared with particle swarm
optimization (PSO).
Abstract: FACTS devices are used to control the power flow, to
increase the transmission capacity and to optimize the stability of the
power system. One of the most widely used FACTS devices is
Unified Power Flow Controller (UPFC). The controller used in the
control mechanism has a significantly effects on controlling of the
power flow and enhancing the system stability of UPFC. According
to this, the capability of UPFC is observed by using different control
mechanisms based on P, PI, PID and fuzzy logic controllers (FLC) in
this study. FLC was developed by taking consideration of Takagi-
Sugeno inference system in the decision process and Sugeno-s
weighted average method in the defuzzification process. Case studies
with different operating conditions are applied to prove the ability of
UPFC on controlling the power flow and the effectiveness of
controllers on the performance of UPFC. PSCAD/EMTDC program
is used to create the FLC and to simulate UPFC model.
Abstract: this paper focuses on designing of PSS and SVC
controller based on chaos and PSO algorithms to improve the
stability of power system. Single machine infinite bus (SMIB) system
with SVC located at the terminal of generator has been considered to
evaluate the proposed controllers where both SVC and PSS have the
same controller. The coefficients of PSS and SVC controller have
been optimized by chaos and PSO algorithms. Finally the system
with proposed controllers has been simulated for the special
disturbance in input power of generator, and then the dynamic
responses of generator have been presented. The simulation results
showed that the system composed with recommended controller has
outstanding operation in fast damping of oscillations of power system.
Abstract: This paper discusses aspects of re-design of loadshedding
schemes with respect to actual developments in the Kosovo
power system. Load-shedding is a type of emergency control that is
designed to ensure system stability by reducing power system load to
match the power generation supply. This paper presents a new
adaptive load-shedding scheme that provides emergency protection
against excess frequency decline, in cases when the Kosovo power
system might be disconnected from the regional transmission
network. The proposed load-shedding scheme uses the local
frequency rate information to adapt the load-shedding pattern to suit
the size and location of the occurring disturbance. The proposed
scheme is tested in a software simulation on a large scale PSS/E
model which represents nine power system areas of Southeast Europe
including the Kosovo power system.
Abstract: To achieve the desired specifications of gain and
phase margins for plants with time-delay that stabilized with FO-PID
controller a lead compensator is designed. At first the range of
controlled system stability based on stability boundary criteria is
determined. Using stability boundary locus method in frequency
domain the fractional order controller parameters are tuned and then
with drawing bode diagram in frequency domain accessing to desired
gain and phase margin are shown. Numerical examples are given to
illustrate the shapes of the stabilizing region and to show the design
procedure.
Abstract: Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.
Abstract: This paper shows a new method for design of fuzzy observers for Takagi-Sugeno systems. The method is based on Linear matrix inequalities (LMIs) and it allows to insert H constraint into the design procedure. The speed of estimation can tuned be specification of a decay rate of the observer closed loop system. We discuss here also the influence of parametric uncertainties at the output control system stability.
Abstract: Recent medical studies have investigated the importance of enteral feeding and the use of feeding pumps for recovering patients unable to feed themselves or gain nourishment and nutrients by natural means. The most of enteral feeding system uses a peristaltic tube pump. A peristaltic pump is a form of positive displacement pump in which a flexible tube is progressively squeezed externally to allow the resulting enclosed pillow of fluid to progress along it. The squeezing of the tube requires a precise and robust controller of the geared motor to overcome parametric uncertainty of the pumping system which generates due to a wide variation of friction and slip between tube and roller. So, this paper proposes fuzzy adaptive controller for the robust control of the peristaltic tube pump. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good control performance, accurate dose rate and robust system stability, of the developed feeding pump is confirmed through experimental and clinic testing.
Abstract: Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to design a robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and PSO is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. Further, all the simulations results are compared with a conventionally designed power system stabilizer to show the superiority of the proposed design approach.