Abstract: This paper presents a procedure for modeling and tuning the parameters of Thyristor Controlled Series Compensation (TCSC) controller in a multi-machine power system to improve transient stability. First a simple transfer function model of TCSC controller for stability improvement is developed and the parameters of the proposed controller are optimally tuned. Genetic algorithm (GA) is employed for the optimization of the parameter-constrained nonlinear optimization problem implemented in a simulation environment. By minimizing an objective function in which the oscillatory rotor angle deviations of the generators are involved, transient stability performance of the system is improved. The proposed TCSC controller is tested on a multi-machine system and the simulation results are presented. The nonlinear simulation results validate the effectiveness of proposed approach for transient stability improvement in a multimachine power system installed with a TCSC. The simulation results also show that the proposed TCSC controller is also effective in damping low frequency oscillations.
Abstract: A considerable progress has been achieved in transient
stability analysis (TSA) with various FACTS controllers. But, all
these controllers are associated with single transmission line. This
paper is intended to discuss a new approach i.e. a multi-line FACTS
controller which is interline power flow controller (IPFC) for TSA of
a multi-machine power system network. A mathematical model of
IPFC, termed as power injection model (PIM) presented and this
model is incorporated in Newton-Raphson (NR) power flow
algorithm. Then, the reduced admittance matrix of a multi-machine
power system network for a three phase fault without and with IPFC
is obtained which is required to draw the machine swing curves. A
general approach based on L-index has also been discussed to find
the best location of IPFC to reduce the proximity to instability of a
power system. Numerical results are carried out on two test systems
namely, 6-bus and 11-bus systems. A program in MATLAB has
been written to plot the variation of generator rotor angle and speed
difference curves without and with IPFC for TSA and also a simple
approach has been presented to evaluate critical clearing time for test
systems. The results obtained without and with IPFC are compared
and discussed.
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: To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.
Abstract: Based on the component approach, three kinds of
dynamic load models, including a single –motor model, a two-motor
model and composite load model have been developed for the
stability studies of Khuzestan power system. The study results are
presented in this paper. Voltage instability is a dynamic phenomenon
and therefore requires dynamic representation of the power system
components. Industrial loads contain a large fraction of induction
machines. Several models of different complexity are available for
the description investigations. This study evaluates the dynamic
performances of several dynamic load models in combination with
the dynamics of a load changing transformer. Case study is steel
industrial substation in Khuzestan power systems.
Abstract: This paper aims to select the optimal location and
setting parameters of TCSC (Thyristor Controlled Series
Compensator) controller using Particle Swarm Optimization (PSO)
and Genetic Algorithm (GA) to mitigate small signal oscillations in a
multimachine power system. Though Power System Stabilizers
(PSSs) are prime choice in this issue, installation of FACTS device
has been suggested here in order to achieve appreciable damping of
system oscillations. However, performance of any FACTS devices
highly depends upon its parameters and suitable location in the
power network. In this paper PSO as well as GA based techniques are
used separately and compared their performances to investigate this
problem. The results of small signal stability analysis have been
represented employing eigenvalue as well as time domain response in
face of two common power system disturbances e.g., varying load
and transmission line outage. It has been revealed that the PSO based
TCSC controller is more effective than GA based controller even
during critical loading condition.
Abstract: Small signal stability causes small perturbations in the
generator that can cause instability in the power network. It is
generally known that small signal stability are directly related to the
generator and load properties. This paper examines the effects of
generator input variations on power system oscillations for a small
signal stability study. Eigenvaules and eigenvectors are used to
examine the stability of the power system. The dynamic power
system's mathematical model is constructed and thus calculated using
load flow and small signal stability toolbox on MATLAB. The power
system model is based on a 3-machine 9-bus system that was
modified to suit this study. In this paper, Participation Factors are a
means to gauge the effects of variation in generation with other
parameters on the network are also incorporated.
Abstract: Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.
Abstract: The paper presents an investigation in to the effect of neural network predictive control of UPFC on the transient stability performance of a multimachine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers, and an improved damping of the power oscillations as compared to the conventional PI controller.
Abstract: Kuwait-s electric power system is vertically integrated
organization owned and operated by the government. For more than
five decades, the government of Kuwait has provided relatively
reliable electric services to consumers with subsidized electric
service fees. Given the country-s rapid socio-economical
development and consequently the increase of electricity demand, a
question that inflicts itself: Is it necessary to reform the power system
to face the fast growing demand? This paper recommends that the
government should consider the private sector as a partner in
operating the power system. Therefore, power system restructuring is
needed to allow such partnership. There are challenges that prevent
such restructuring. Abstract recommendations toward resolving these
challenges are proposed.
Abstract: Optimal load shedding (LS) design as an emergency plan is one of the main control challenges posed by emerging new uncertainties and numerous distributed generators including renewable energy sources in a modern power system. This paper presents an overview of the key issues and new challenges on optimal LS synthesis concerning the integration of wind turbine units into the power systems. Following a brief survey on the existing LS methods, the impact of power fluctuation produced by wind powers on system frequency and voltage performance is presented. The most LS schemas proposed so far used voltage or frequency parameter via under-frequency or under-voltage LS schemes. Here, the necessity of considering both voltage and frequency indices to achieve a more effective and comprehensive LS strategy is emphasized. Then it is clarified that this problem will be more dominated in the presence of wind turbines.
Abstract: In this paper, an improved technique for contingency
ranking using artificial neural network (ANN) is presented. The
proposed approach is based on multi-layer perceptrons trained by
backpropagation to contingency analysis. Severity indices in dynamic
stability assessment are presented. These indices are based on the
concept of coherency and three dot products of the system variables.
It is well known that some indices work better than others for a
particular power system. This paper along with test results using
several different systems, demonstrates that combination of indices
with ANN provides better ranking than a single index. The presented
results are obtained through the use of power system simulation
(PSS/E) and MATLAB 6.5 software.
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.
Abstract: This paper presents Genetic Algorithm (GA) based
approach for the allocation of FACTS (Flexible AC Transmission
System) devices for the improvement of Power transfer capacity in an
interconnected Power System. The GA based approach is applied on
IEEE 30 BUS System. The system is reactively loaded starting from
base to 200% of base load. FACTS devices are installed in the
different locations of the power system and system performance is
noticed with and without FACTS devices. First, the locations, where
the FACTS devices to be placed is determined by calculating active
and reactive power flows in the lines. Genetic Algorithm is then
applied to find the amount of magnitudes of the FACTS devices. This
approach of GA based placement of FACTS devices is tremendous
beneficial both in terms of performance and economy is clearly
observed from the result obtained.
Abstract: The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the proposed approach is faster than conventional controllers. The performance of HNF controller has been compared with that of both conventional Proportional Integral (PI) controller as well as Fuzzy Logic Controller (FLC) both in the absence and presence of Generation Rate Constraint (GRC). System performance is examined considering disturbance in each area of interconnected power system.
Abstract: This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.
Abstract: In this paper variation of spot price and total profits of
the generating companies- through wholesale electricity trading are
discussed with and without Central Generating Stations (CGS) share
and seasonal variations are also considered. It demonstrates how
proper analysis of generators- efficiencies and capabilities, types of
generators owned, fuel costs, transmission losses and settling price
variation using the solutions of Optimal Power Flow (OPF), can
allow companies to maximize overall revenue. It illustrates how
solutions of OPF can be used to maximize companies- revenue under
different scenarios. And is also extended to computation of Available
Transfer Capability (ATC) is very important to the transmission
system security and market forecasting. From these results it is
observed that how crucial it is for companies to plan their daily
operations and is certainly useful in an online environment of
deregulated power system. In this paper above tasks are demonstrated
on 124 bus real-life Indian utility power system of Andhra Pradesh
State Grid and results have been presented and analyzed.
Abstract: Static Var Compensator (SVC) is a shunt type FACTS
device which is used in power system primarily for the purpose of
voltage and reactive power control. In this paper, a fuzzy logic based
supplementary controller for Static Var Compensator (SVC) is
developed which is used for damping the rotor angle oscillations and
to improve the transient stability of the power system. Generator
speed and the electrical power are chosen as input signals for the
Fuzzy Logic Controller (FLC). The effectiveness and feasibility of
the proposed control is demonstrated with Single Machine Infinite
Bus (SMIB) system and multimachine system (WSCC System)
which show improvement over the use of a fixed parameter
controller.
Abstract: The security of power systems against malicious cyberphysical
data attacks becomes an important issue. The adversary
always attempts to manipulate the information structure of the power
system and inject malicious data to deviate state variables while
evading the existing detection techniques based on residual test. The
solutions proposed in the literature are capable of immunizing the
power system against false data injection but they might be too costly
and physically not practical in the expansive distribution network.
To this end, we define an algebraic condition for trustworthy power
system to evade malicious data injection. The proposed protection
scheme secures the power system by deterministically reconfiguring
the information structure and corresponding residual test. More
importantly, it does not require any physical effort in either microgrid
or network level. The identification scheme of finding meters being
attacked is proposed as well. Eventually, a well-known IEEE 30-bus
system is adopted to demonstrate the effectiveness of the proposed
schemes.
Abstract: The main objective of Automatic Generation Control (AGC) is to balance the total system generation against system load losses so that the desired frequency and power interchange with neighboring systems is maintained. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This paper deals with a novel approach of artificial intelligence (AI) technique called Hybrid Neuro-Fuzzy (HNF) approach for an (AGC). The advantage of this controller is that it can handle the non-linearities at the same time it is faster than other conventional controllers. The effectiveness of the proposed controller in increasing the damping of local and inter area modes of oscillation is demonstrated in a two area interconnected power system. The result shows that intelligent controller is having improved dynamic response and at the same time faster than conventional controller.