Abstract: Flexible AC Transmission Systems (FACTS) is
granting a new group of advanced power electronic devices emerging
for enhancement of the power system performance. Unified Power
Flow Controller (UPFC) is a recent version of FACTS devices for
power system applications. The back-up energy supply system
incorporated with UPFC is providing a complete control of real and
reactive power at the same time and hence is competent to improve
the performance of an electrical power system. In this article, backup
energy supply unit such as superconducting magnetic energy storage
(SMES) is integrated with UPFC. In addition, comparative
exploration of UPFC–battery, UPFC–UC and UPFC–SMES
performance is evaluated through the vibrant simulation by using
MATLAB/Simulink software.
Abstract: This paper discusses the design and analysis of a
hybrid PV-Fuel cell energy system destined to power a DC load. The
system is composed of a photovoltaic array, a fuel cell, an
electrolyzer and a hydrogen tank. HOMER software is used in this
study to calculate the optimum capacities of the power system
components that their combination allows an efficient use of solar
resource to cover the hourly load needs. The optimal system sizing
allows establishing the right balance between the daily electrical
energy produced by the power system and the daily electrical energy
consumed by the DC load using a 28 KW PV array, a 7.5 KW fuel
cell, a 40KW electrolyzer and a 270 Kg hydrogen tank. The variation
of powers involved into the DC bus of the hybrid PV-fuel cell system
has been computed and analyzed for each hour over one year: the
output powers of the PV array and the fuel cell, the input power of
the elctrolyzer system and the DC primary load. Equally, the annual
variation of stored hydrogen produced by the electrolyzer has been
assessed. The PV array contributes in the power system with 82%
whereas the fuel cell produces 18%. 38% of the total energy
consumption belongs to the DC primary load while the rest goes to
the electrolyzer.
Abstract: Power systems are operating under stressed condition
due to continuous increase in demand of load. This can lead to
voltage instability problem when face additional load increase or
contingency. In order to avoid voltage instability suitable size of
reactive power compensation at optimal location in the system is
required which improves the load margin. This work aims at
obtaining optimal size as well as location of compensation in the 39-
bus New England system with the help of Bacteria Foraging and
Genetic algorithms. To reduce the computational time the work
identifies weak candidate buses in the system, and then picks only
two of them to take part in the optimization. The objective function is
based on a recently proposed voltage stability index which takes into
account the weighted average sensitivity index is a simpler and faster
approach than the conventional CPF algorithm. BFOA has been
found to give better results compared to GA.
Abstract: Wind energy offers a significant advantage such as no
fuel costs and no emissions from generation. However, wind energy
sources are variable and non-dispatchable. The utility grid is able to
accommodate the variability of wind in smaller proportion along with
the daily load. However, at high penetration levels, the variability can
severely impact the utility reserve requirements and the cost
associated with it. In this paper the impact of wind energy is
evaluated in detail in formulating the total utility cost. The objective
is to minimize the overall cost of generation while ensuring the
proper management of the load. Overall cost includes the curtailment
cost, reserve cost and the reliability cost, as well as any other penalty
imposed by the regulatory authority. Different levels of wind
penetrations are explored and the cost impacts are evaluated. As the
penetration level increases significantly, the reliability becomes a
critical question to be answered. Here we increase the penetration
from the wind yet keep the reliability factor within the acceptable
limit provided by NERC. This paper uses an economic dispatch (ED)
model to incorporate wind generation into the power grid. Power
system costs are analyzed at various wind penetration levels using
Linear Programming. The goal of this study is show how the
increases in wind generation will affect power system economics.
Abstract: This paper presents a methodology using
Gravitational Search Algorithm for optimal placement of Phasor
Measurement Units (PMUs) in order to achieve complete
observability of the power system. The objective of proposed
algorithm is to minimize the total number of PMUs at the power
system buses, which in turn minimize installation cost of the PMUs.
In this algorithm, the searcher agents are collection of masses which
interact with each other using Newton’s laws of gravity and motion.
This new Gravitational Search Algorithm based method has been
applied to the IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test
systems. Case studies reveal optimal number of PMUs with better
observability by proposed method.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: This paper presents small signal stability study carried
over the 140-Bus, 31-Machine, 5-Area MEPE system and validated
on free and open source software: PSAT. Well-established linearalgebra
analysis, eigenvalue analysis, is employed to determine the
small signal dynamic behavior of test system. The aspects of local
and interarea oscillations which may affect the operation and
behavior of power system are analyzed. Eigenvalue analysis is carried
out to investigate the small signal behavior of test system and the
participation factors have been determined to identify the
participation of the states in the variation of different mode shapes.
Also, the variations in oscillatory modes are presented to observe the
damping performance of the test system.
Abstract: One of the major difficulties introduced with wind
power penetration is the inherent uncertainty in production originating
from uncertain wind conditions. This uncertainty impacts many
different aspects of power system operation, especially the balancing
power requirements. For this reason, in power system development
planing, it is necessary to evaluate the potential uncertainty in future
wind power generation. For this purpose, simulation models are
required, reproducing the performance of wind power forecasts.
This paper presents a wind power forecast error simulation models
which are based on the stochastic process simulation. Proposed
models capture the most important statistical parameters recognized
in wind power forecast error time series. Furthermore, two distinct
models are presented based on data availability. First model uses
wind speed measurements on potential or existing wind power plant
locations, while the seconds model uses statistical distribution of wind
speeds.
Abstract: The most important component affecting the
efficiency of photovoltaic power systems are solar panels. In other
words, efficiency of these systems are significantly affected due to
the being low efficiency of solar panel. Thus, solar panels should be
operated under maximum power point conditions through a power
converter. In this study, design of boost converter has been carried
out with maximum power point tracking (MPPT) algorithm which is
incremental conductance (Inc-Cond). By using this algorithm,
importance of power converter in MPPT hardware design, impacts of
MPPT operation have been shown. It is worth noting that initial
operation point is the main criteria for determining the MPPT
performance. In addition, it is shown that if value of load resistance is
lower than critical value, failure operation is realized. For these
analyzes, direct duty control is used for simplifying the control.
Abstract: At present, the evaluation of voltage stability
assessment experiences sizeable anxiety in the safe operation of
power systems. This is due to the complications of a strain power
system. With the snowballing of power demand by the consumers
and also the restricted amount of power sources, therefore, the system
has to perform at its maximum proficiency. Consequently, the
noteworthy to discover the maximum ability boundary prior to
voltage collapse should be undertaken. A preliminary warning can be
perceived to evade the interruption of power system’s capacity. The
effectiveness of line voltage stability indices (LVSI) is differentiated
in this paper. The main purpose of the indices used is to predict the
proximity of voltage instability of the electric power system. On the
other hand, the indices are also able to decide the weakest load buses
which are close to voltage collapse in the power system. The line
stability indices are assessed using the IEEE 14 bus test system to
validate its practicability. Results demonstrated that the implemented
indices are practically relevant in predicting the manifestation of
voltage collapse in the system. Therefore, essential actions can be
taken to dodge the incident from arising.
Abstract: This paper investigates the joint effect of the
interconnected (n,k)-star network topology and Multi-Agent
automated control on restoration and reconfiguration of power
systems. With the increasing trend in development in Multi-Agent
control technologies applied to power system reconfiguration
in presence of faulty components or nodes. Fault tolerance is
becoming an important challenge in the design processes of the
distributed power system topology. Since the reconfiguration of a
power system is performed by agent communication, the (n,k)-star
interconnected network topology is studied and modeled in this
paper to optimize the process of power reconfiguration. In this paper,
we discuss the recently proposed (n,k)-star topology and examine its
properties and advantages as compared to the traditional multi-bus
power topologies. We design and simulate the topology model for
distributed power system test cases. A related lemma based on the
fault tolerance and conditional diagnosability properties is presented
and proved both theoretically and practically. The conclusion is
reached that (n,k)-star topology model has measurable advantages
compared to standard bus power systems while exhibiting fault
tolerance properties in power restoration, as well as showing
efficiency when applied to power system route discovery.
Abstract: Today’s modern interconnected power system is
highly complex in nature. In this, one of the most important
requirements during the operation of the electric power system is the
reliability and security. Power and frequency oscillation damping
mechanism improve the reliability. Because of power system
stabilizer (PSS) low speed response against of major fault such as
three phase short circuit, FACTs devise that can control the network
condition in very fast time, are becoming popular. But FACTs
capability can be seen in a major fault present when nonlinear models
of FACTs devise and power system equipment are applied. To realize
this aim, the model of multi-machine power system with FACTs
controller is developed in MATLAB/SIMULINK using Sim Power
System (SPS) blockiest. Among the FACTs device, Static
synchronous series compensator (SSSC) due to high speed changes
its reactance characteristic inductive to capacitive, is effective power
flow controller. Tuning process of controller parameter can be
performed using different method. But Genetic Algorithm (GA)
ability tends to use it in controller parameter tuning process. In this
paper firstly POD controller is used to power oscillation damping.
But in this station, frequency oscillation dos not has proper damping
situation. So FOD controller that is tuned using GA is using that
cause to damp out frequency oscillation properly and power
oscillation damping has suitable situation.
Abstract: In this paper an isolated wind-diesel hybrid power
system has been considered for reactive power control study having
an induction generator for wind power conversion and synchronous
alternator with automatic voltage regulator (AVR) for diesel unit is
presented. The dynamic voltage stability evaluation is dependent on
small signal analysis considering a Static VAR Compensator (SVC)
and IEEE type -I excitation system. It's shown that the variable
reactive power source like SVC is crucial to meet the varying
demand of reactive power by induction generator and load and to
acquire an excellent voltage regulation of the system with minimum
fluctuations. Integral square error (ISE) criterion can be used to
evaluate the optimum setting of gain parameters. Finally the dynamic
responses of the power systems considered with optimum gain setting
will also be presented.
Abstract: There are a variety of reference current identification
methods, for the shunt active power filter (SAPF), such as the
instantaneous active and reactive power, the instantaneous active and
reactive current and the synchronous detection method are evaluated
and compared under ideal, non sinusoidal and unbalanced voltage
conditions. The SAPF performances, for the investigated
identification methods, are tested for a non linear load. The
simulation results, using Matlab Power System Blockset Toolbox
from a complete structure, are presented and discussed.
Abstract: Distributed Generation (DG) can help in reducing the
cost of electricity to the costumer, relieve network congestion and
provide environmentally friendly energy close to load centers. Its
capacity is also scalable and it provides voltage support at distribution
level. Hence, DG placement and penetration level is an important
problem for both the utility and DG owner. DG allocation and capacity
determination is a nonlinear optimization problem. The objective
function of this problem is the minimization of the total loss of the
distribution system. Also high levels of penetration of DG are a new
challenge for traditional electric power systems. This paper presents a
new methodology for the optimal placement of DG and penetration
level of DG in distribution system based on General Algebraic
Modeling System (GAMS) and Genetic Algorithm (GA).
Abstract: Renewable energy is derived from natural processes
that are replenished constantly. Included in the definition is
electricity and heat generated from solar, wind, ocean, hydropower,
biomass, geothermal resources, and bio-fuels and hydrogen derived
from renewable resources. Each of these sources has unique
characteristics which influence how and where they are used. This
paper presents the modeling the simulation of solar and hydro hybrid
energy sources in MATLAB/SIMULINK environment. It simulates
all quantities of Hybrid Electrical Power system (HEPS) such as AC
output current of the inverter that injected to the load/grid, load
current, grid current. It also simulates power output from PV and
Hydraulic Turbine Generator (HTG), power delivered to or from grid
and finally power factor of the inverter for PV, HTG and grid. The
proposed circuit uses instantaneous p-q (real-imaginary) power
theory.
Abstract: Ancillary services are support services which are
essential for humanizing and enhancing the reliability and security of
the electric power system. Reactive power ancillary service is one of
the important ancillary services in a restructured electricity market
which determines the cost of supplying ancillary services and finding
of how this cost would change with respect to operating decisions.
This paper presents a new formation that can be used to minimize the
Independent System Operator (ISO)’s total payment for reactive
power ancillary service. The modified power flow tracing algorithm
estimates the availability of reserve reactive power for ancillary
service. In order to find optimum reactive power dispatch,
Biogeography based optimization method (BPO) is proposed. Market
Reactive Clearing Price (MRCP) is then estimated and it encourages
generator companies (GENCOs) to participate in an ancillary service.
Finally, optimal weighting factor and real time utilization factor of
reactive power give the minimum ISO’s total payment. The
effectiveness of proposed design is verified using IEEE 30 bus
system.
Abstract: Economic Dispatch (ED) is one of the most
challenging problems of power system since it is difficult to determine
the optimum generation scheduling to meet the particular load demand
with the minimum fuel costs while all constraints are satisfied. The
objective of the Economic Dispatch Problems (EDPs) of electric
power generation is to schedule the committed generating units
outputs so as to meet the required load demand at minimum operating
cost while satisfying all units and system equality and inequality
constraints. In this paper, an efficient and practical steady-state genetic
algorithm (SSGAs) has been proposed for solving the economic
dispatch problem. The objective is to minimize the total generation
fuel cost and keep the power flows within the security limits. To
achieve that, the present work is developed to determine the optimal
location and size of capacitors in transmission power system where,
the Participation Factor Algorithm and the Steady State Genetic
Algorithm are proposed to select the best locations for the capacitors
and determine the optimal size for them.
Abstract: In development of floating photovoltaic generation
system, finding a suitable place of installation is as important as
development of economically feasible and stable structure. Especially
since floating photovoltaic system has its facility floating on water
surface, it is extremely important to review the effects of weather
conditions such as wind, water flow and floating matters, various
factors (such as fogs) that can reduce generation efficiency, possibility
of connection with power system, and legal restrictions. The method of
investigating suitable area and resource for development of
tracking-type floating photovoltaic generation system was proposed in
this paper, which can be used for development of floating and ocean
photovoltaic system in the future.
Abstract: This paper aims at finding a suitable neural network
for monitoring congestion level in electrical power systems. In this
paper, the input data has been framed properly to meet the target
objective through supervised learning mechanism by defining normal
and abnormal operating conditions for the system under study. The
congestion level, expressed as line congestion index (LCI), is
evaluated for each operating condition and is presented to the NN
along with the bus voltages to represent the input and target data.
Once, the training goes successful, the NN learns how to deal with a
set of newly presented data through validation and testing
mechanism. The crux of the results presented in this paper rests on
performance comparison of a multi-layered feed forward neural
network with eleven types of back propagation techniques so as to
evolve the best training criteria. The proposed methodology has been
tested on the standard IEEE-14 bus test system with the support of
MATLAB based NN toolbox. The results presented in this paper
signify that the Levenberg-Marquardt backpropagation algorithm
gives best training performance of all the eleven cases considered in
this paper, thus validating the proposed methodology.