Abstract: This paper investigates the performance comparison of SVC (Static VAR Compensator) and DSTATCOM (Distribution Static Synchronous Compensator) to improve voltage stability in Radial Distribution System (RDS) which are efficient FACTS (Flexible AC Transmission System) devices that are capable of controlling the active and reactive power flows in a power system line by appropriately controlling parameters using ANFIS. Simulations are carried out in MATLAB/Simulink environment for the IEEE-4 bus system to test the ability of increasing load. It is found that these controllers significantly increase the margin of load in the power systems.
Abstract: This paper proposes a backward/forward sweep
method to analyze the power flow in radial distribution systems. The
distribution system has radial structure and high R/X ratios. So the
newton-raphson and fast decoupled methods are failed with
distribution system. The proposed method presents a load flow study
using backward/forward sweep method, which is one of the most
effective methods for the load-flow analysis of the radial distribution
system. By using this method, power losses for each bus branch and
voltage magnitudes for each bus node are determined. This method
has been tested on IEEE 33-bus radial distribution system and
effective results are obtained using MATLAB.
Abstract: This paper presents a simple three phase power flow
method for solution of three-phase unbalanced radial distribution
system (RDN) with voltage dependent loads. It solves a simple
algebraic recursive expression of voltage magnitude, and all the data
are stored in vector form. The algorithm uses basic principles of
circuit theory and can be easily understood. Mutual coupling between
the phases has been included in the mathematical model. The
proposed algorithm has been tested with several unbalanced radial
distribution networks and the results are presented in the article. 8-
bus and IEEE 13 bus unbalanced radial distribution system results
are in agreements with the literature and show that the proposed
model is valid and reliable.
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: This paper presents an efficient approach to feeder
reconfiguration for power loss reduction and voltage profile
imprvement in unbalanced radial distribution systems (URDS). In
this paper Genetic Algorithm (GA) is used to obtain solution for
reconfiguration of radial distribution systems to minimize the losses.
A forward and backward algorithm is used to calculate load flows in
unbalanced distribution systems. By simulating the survival of the
fittest among the strings, the optimum string is searched by
randomized information exchange between strings by performing
crossover and mutation. Results have shown that proposed algorithm
has advantages over previous algorithms The proposed method is
effectively tested on 19 node and 25 node unbalanced radial
distribution systems.
Abstract: This paper presents a simple approach for load
flow analysis of a radial distribution network. The proposed
approach utilizes forward and backward sweep algorithm
based on Kirchoff-s current law (KCL) and Kirchoff-s voltage
law (KVL) for evaluating the node voltages iteratively. In this
approach, computation of branch current depends only on the
current injected at the neighbouring node and the current in
the adjacent branch. This approach starts from the end nodes
of sub lateral line, lateral line and main line and moves
towards the root node during branch current computation. The
node voltage evaluation begins from the root node and moves
towards the nodes located at the far end of the main, lateral
and sub lateral lines. The proposed approach has been tested
using four radial distribution systems of different size and
configuration and found to be computationally efficient.
Abstract: This paper presents a new and efficient approach for
capacitor placement in radial distribution systems that determine
the optimal locations and size of capacitor with an objective of
improving the voltage profile and reduction of power loss. The
solution methodology has two parts: in part one the loss sensitivity
factors are used to select the candidate locations for the capacitor
placement and in part two a new algorithm that employs Plant growth
Simulation Algorithm (PGSA) is used to estimate the optimal size
of capacitors at the optimal buses determined in part one. The main
advantage of the proposed method is that it does not require any
external control parameters. The other advantage is that it handles the
objective function and the constraints separately, avoiding the trouble
to determine the barrier factors. The proposed method is applied to 9
and 34 bus radial distribution systems. The solutions obtained by the
proposed method are compared with other methods. The proposed
method has outperformed the other methods in terms of the quality
of solution.
Abstract: This paper presents a new and efficient approach for capacitor placement in radial distribution systems that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Plant growth Simulation Algorithm (PGSA) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately, avoiding the trouble to determine the barrier factors. The proposed method is applied to 9, 34, and 85-bus radial distribution systems. The solutions obtained by the proposed method are compared with other methods. The proposed method has outperformed the other methods in terms of the quality of solution.
Abstract: This paper presents a new method which applies an
artificial bee colony algorithm (ABC) for capacitor placement in
distribution systems with an objective of improving the voltage profile
and reduction of power loss. The ABC algorithm is a new population
based meta heuristic approach inspired by intelligent foraging behavior
of honeybee swarm. The advantage of ABC algorithm is that
it does not require external parameters such as cross over rate and
mutation rate as in case of genetic algorithm and differential evolution
and it is hard to determine these parameters in prior. The other
advantage is that the global search ability in the algorithm is implemented
by introducing neighborhood source production mechanism
which is a similar to mutation process. To demonstrate the validity
of the proposed algorithm, computer simulations are carried out on
69-bus system and compared the results with the other approach
available in the literature. The proposed method has outperformed the
other methods in terms of the quality of solution and computational
efficiency.
Abstract: This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.
Abstract: This paper presents an efficient algorithm for
optimization of radial distribution systems by a network
reconfiguration to balance feeder loads and eliminate overload
conditions. The system load-balancing index is used to determine the
loading conditions of the system and maximum system loading
capacity. The index value has to be minimum in the optimal network
reconfiguration of load balancing. A method based on Tabu search
algorithm, The Tabu search algorithm is employed to search for the
optimal network reconfiguration. The basic idea behind the search is
a move from a current solution to its neighborhood by effectively
utilizing a memory to provide an efficient search for optimality. It
presents low computational effort and is able to find good quality
configurations. Simulation results for a radial 69-bus system with
distributed generations and capacitors placement. The study results
show that the optimal on/off patterns of the switches can be identified
to give the best network reconfiguration involving balancing of
feeder loads while respecting all the constraints.
Abstract: To minimize power losses, it is important to
determine the location and size of local generators to be placed in
unbalanced power distribution systems. On account of some inherent
features of unbalanced distribution systems, such as radial structure,
large number of nodes, a wide range of X/R ratios, the conventional
techniques developed for the transmission systems generally fail on
the determination of optimum size and location of distributed
generators (DGs). This paper presents a simple method for
investigating the problem of contemporaneously choosing best
location and size of DG in three-phase unbalanced radial distribution
system (URDS) for power loss minimization and to improve the
voltage profile of the system. Best location of the DG is determined
by using voltage index analysis and size of DG is computed by
variational technique algorithm according to available standard size
of DGs. This paper presents the results of simulations for 25-bus and
IEEE 37- bus Unbalanced Radial Distribution system.
Abstract: This paper discusses a genetic algorithm (GA) based optimal load shedding that can apply for electrical distribution networks with and without dispersed generators (DG). Also, the proposed method has the ability for considering constant and variable capacity deficiency caused by unscheduled outages in the bulked generation and transmission system of bulked power supply. The genetic algorithm (GA) is employed to search for the optimal load shedding strategy in distribution networks considering DGs in two cases of constant and variable modelling of bulked power supply of distribution networks. Electrical power distribution systems have a radial network and unidirectional power flows. With the advent of dispersed generations, the electrical distribution system has a locally looped network and bidirectional power flows. Therefore, installed DG in the electrical distribution systems can cause operational problems and impact on existing operational schemes. Introduction of DGs in electrical distribution systems has introduced many new issues in operational and planning level. Load shedding as one of operational issue has no exempt. The objective is to minimize the sum of curtailed load and also system losses within the frame-work of system operational and security constraints. The proposed method is tested on a radial distribution system with 33 load points for more practical applications.
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: This paper presents a novel approach for optimal
reconfiguration of radial distribution systems. Optimal
reconfiguration involves the selection of the best set of branches to
be opened, one each from each loop, such that the resulting radial
distribution system gets the desired performance. In this paper an
algorithm is proposed based on simple heuristic rules and identified
an effective switch status configuration of distribution system for the
minimum loss reduction. This proposed algorithm consists of two
parts; one is to determine the best switching combinations in all loops
with minimum computational effort and the other is simple optimum
power loss calculation of the best switching combination found in
part one by load flows. To demonstrate the validity of the proposed
algorithm, computer simulations are carried out on 33-bus system.
The results show that the performance of the proposed method is
better than that of the other methods.
Abstract: Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.