Abstract: In power systems, protective relays must filter their
inputs to remove undesirable quantities and retain signal quantities of
interest. This job must be performed accurate and fast. A new
method for filtering the undesirable components such as DC and
harmonic components associated with the fundamental system
signals. The method is s based on a dynamic filtering algorithm. The
filtering algorithm has many advantages over some other classical
methods. It can be used as dynamic on-line filter without the need of
parameters readjusting as in the case of classic filters. The proposed
filter is tested using different signals. Effects of number of samples
and sampling window size are discussed. Results obtained are
presented and discussed to show the algorithm capabilities.
Abstract: Fuzzy Load forecasting plays a paramount role in the operation and management of power systems. Accurate estimation of future power demands for various lead times facilitates the task of generating power reliably and economically. The forecasting of future loads for a relatively large lead time (months to few years) is studied here (long term load forecasting). Among the various techniques used in forecasting load, artificial intelligence techniques provide greater accuracy to the forecasts as compared to conventional techniques. Fuzzy Logic, a very robust artificial intelligent technique, is described in this paper to forecast load on long term basis. The paper gives a general algorithm to forecast long term load. The algorithm is an Extension of Short term load forecasting method to Long term load forecasting and concentrates not only on the forecast values of load but also on the errors incorporated into the forecast. Hence, by correcting the errors in the forecast, forecasts with very high accuracy have been achieved. The algorithm, in the paper, is demonstrated with the help of data collected for residential sector (LT2 (a) type load: Domestic consumers). Load, is determined for three consecutive years (from April-06 to March-09) in order to demonstrate the efficiency of the algorithm and to forecast for the next two years (from April-09 to March-11).
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: In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.
Abstract: With continuous rise of oil price, how to develop alternative energy source has become a hot topic around the world. This study discussed the dynamic characteristics of an island power system operating under random wind speed lower than nominal wind
speeds of wind turbines. The system primarily consists of three diesel engine power generation systems, three constant-speed variable-pitch wind turbines, a small hydraulic induction generation system, and lumped static loads. Detailed models based on Matlab/Simulink were developed to cater for the dynamic behavior of the system. The results suggested this island power system can operate stably in this operational mode. This study can serve as an important reference for planning, operation, and further expansion of island power systems.
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: The steady-state operation of maintaining voltage
stability is done by switching various controllers scattered all over
the power network. When a contingency occurs, whether forced or
unforced, the dispatcher is to alleviate the problem in a minimum
time, cost, and effort. Persistent problem may lead to blackout. The
dispatcher is to have the appropriate switching of controllers in terms
of type, location, and size to remove the contingency and maintain
voltage stability. Wrong switching may worsen the problem and that
may lead to blackout. This work proposed and used a Fuzzy CMeans
Clustering (FCMC) to assist the dispatcher in the decision
making. The FCMC is used in the static voltage stability to map
instantaneously a contingency to a set of controllers where the types,
locations, and amount of switching are induced.
Abstract: The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.
Abstract: In this paper, a new K-means clustering based
approach for identification of voltage control areas is developed.
Voltage control areas are important for efficient reactive power
management in power systems operating under deregulated
environment. Although, voltage control areas are formed using
conventional hierarchical clustering based method, but the present
paper investigate the capability of K-means clustering for the
purpose of forming voltage control areas. The proposed method is
tested and compared for IEEE 14 bus and IEEE 30 bus systems. The
results show that this K-means based method is competing with
conventional hierarchical approach
Abstract: Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).
Abstract: This paper reviews the optimization available
transmission capability (ATC) of power systems using a device of
FACTS named SSSC equipped with energy storage devices. So that,
emplacement and improvement of parameters of SSSC will be
illustrated. Thus, voltage magnitude constraints of network buses,
line transient stability constraints and voltage breakdown constraints
are considered. To help the calculations, a comprehensive program in
DELPHI is provided, which is able to simulate and trace the
parameters of SSSC has been installed on a specific line.
Furthermore, the provided program is able to compute ATC, TTC
and maximum value of their enhancement after using SSSC.
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: This paper proposes a Particle Swarm Optimization
(PSO) based technique for the optimal allocation of Distributed
Generation (DG) units in the power systems. In this paper our aim is
to decide optimal number, type, size and location of DG units for
voltage profile improvement and power loss reduction in distribution
network. Two types of DGs are considered and the distribution load
flow is used to calculate exact loss. Load flow algorithm is combined
appropriately with PSO till access to acceptable results of this
operation. The suggested method is programmed under MATLAB
software. Test results indicate that PSO method can obtain better
results than the simple heuristic search method on the 30-bus and 33-
bus radial distribution systems. It can obtain maximum loss reduction
for each of two types of optimally placed multi-DGs. Moreover,
voltage profile improvement is achieved.
Abstract: The rapidly increasing costs of power line extensions
and fossil fuel, combined with the desire to reduce carbon dioxide
emissions pushed the development of hybrid power system suited for
remote locations, the purpose in mind being that of autonomous local
power systems. The paper presents the suggested solution for a “high
penetration" hybrid power system, it being determined by the
location of the settlement and its “zero policy" on carbon dioxide
emissions. The paper focuses on the technical solution and the power
flow management algorithm of the system, taking into consideration
local conditions of development.
Abstract: In the LFC problem, the interconnections among some areas are the input of disturbances, and therefore, it is important to suppress the disturbances by the coordination of governor systems. In contrast, tie-line power flow control by TCPS located between two areas makes it possible to stabilize the system frequency oscillations positively through interconnection, which is also expected to provide a new ancillary service for the further power systems. Thus, a control strategy using controlling the phase angle of TCPS is proposed for provide active control facility of system frequency in this paper. Also, the optimum adjustment of PID controller's parameters in a robust way under bilateral contracted scenario following the large step load demands and disturbances with and without TCPS are investigated by Particle Swarm Optimization (PSO), that has a strong ability to find the most optimistic results. This newly developed control strategy combines the advantage of PSO and TCPS and has simple stricture that is easy to implement and tune. To demonstrate the effectiveness of the proposed control strategy a three-area restructured power system is considered as a test system under different operating conditions and system nonlinearities. Analysis reveals that the TCPS is quite capable of suppressing the frequency and tie-line power oscillations effectively as compared to that obtained without TCPS for a wide range of plant parameter changes, area load demands and disturbances even in the presence of system nonlinearities.
Abstract: Voltage collapse is instability of heavily loaded electric
power systems that cause to declining voltages and blackout. Power
systems are predicated to become more heavily loaded in the future
decade as the demand for electric power rises while economic and
environmental concerns limit the construction of new transmission
and generation capacity. Heavily loaded power systems are closer to
their stability limits and voltage collapse blackouts will occur if
suitable monitoring and control measures are not taken. To control
transmission lines, it can be used from FACTS devices.
In this paper Harmony search algorithm (HSA) and Genetic
Algorithm (GA) have applied to determine optimal location of
FACTS devices in a power system to improve power system stability.
Three types of FACTS devices (TCPAT, UPFS, and SVC) have been
introduced. Bus under voltage has been solved by controlling reactive
power of shunt compensator. Also a combined series-shunt
compensators has been also used to control transmission power flow
and bus voltage simultaneously.
Different scenarios have been considered. First TCPAT, UPFS, and
SVC are placed solely in transmission lines and indices have been
calculated. Then two types of above controller try to improve
parameters randomly. The last scenario tries to make better voltage
stability index and losses by implementation of three types controller
simultaneously. These scenarios are executed on typical 34-bus test
system and yields efficiency in improvement of voltage profile and
reduction of power losses; it also may permit an increase in power
transfer capacity, maximum loading, and voltage stability margin.
Abstract: Nowadays, power systems, energy generation by wind
has been very important. Noting that the production of electrical
energy by wind turbines on site to several factors (such as wind speed
and profile site for the turbines, especially off the wind input speed,
wind rated speed and wind output speed disconnect) is dependent. On
the other hand, several different types of turbines in the market there.
Therefore, selecting a turbine that its capacity could also answer the
need for electric consumers the efficiency is high something is
important and necessary. In this context, calculating the amount of
wind power to help optimize overall network, system operation, in
determining the parameters of wind power is very important.
In this article, to help calculate the amount of wind power plant,
connected to the national network in the region Manjil wind,
selecting the best type of turbine and power delivery profile
appropriate to the network using Monte Carlo method has been.
In this paper, wind speed data from the wind site in Manjil, as minute
and during the year has been. Necessary simulations based on
Random Numbers Simulation method and repeat, using the software
MATLAB and Excel has been done.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: At any point of time, a power system operating
condition should be stable, meeting various operational criteria and it
should also be secure in the event of any credible contingency. Present
day power systems are being operated closer to their stability limits
due to economic and environmental constraints. Maintaining a stable
and secure operation of a power system is therefore a very important
and challenging issue. Voltage instability has been given much
attention by power system researchers and planners in recent years,
and is being regarded as one of the major sources of power system
insecurity. Voltage instability phenomena are the ones in which the
receiving end voltage decreases well below its normal value and does
not come back even after setting restoring mechanisms such as VAR
compensators, or continues to oscillate for lack of damping against the
disturbances. Reactive power limit of power system is one of the major
causes of voltage instability. This paper investigates the effects of
coordinated series capacitors (SC) with static VAR compensators
(SVC) on steady-state voltage stability of a power system. Also, the
influence of the presence of series capacitor on static VAR
compensator controller parameters and ratings required to stabilize
load voltages at certain values are highlighted.
Abstract: The presence of harmonic in power system is a major
concerned to power engineers for many years. With the increasing
usage of nonlinear loads in power systems, the harmonic pollution
becomes more serious. One of the widely used computation
algorithm for harmonic analysis is fast Fourier transform (FFT). In
this paper, a harmonic analyzer using FFT was implemented on
TMS320C6713 DSK. The supply voltage of 240 V 59 Hz is stepped
down to 5V using a voltage divider in order to match the power
rating of the DSK input. The output from the DSK was displayed on
oscilloscope and Code Composer Studio™ software. This work has
demonstrated the possibility of analyzing the 240V power supply
harmonic content using the DSK board.