This document discusses a heuristic-based multi-objective approach for network reconfiguration of distribution systems. The approach considers four objectives: minimizing real power loss, deviation in bus voltages, branch current violation, and load balancing among feeders. It uses fuzzy sets to model the imprecise nature of the objectives. Heuristic rules are incorporated to minimize the number of tie-switch operations needed. An improved Fast Decoupled load flow algorithm is proposed to deal with reconfiguration problems in single and multi-feeder networks effectively.
Power consumption is an important metric tool in the context of the wireless sensor networks
(WSNs). In this paper, we described a new Energy-Degree (EDD) Clustering Algorithm for the
WSNs. A node with higher residual energy and higher degree is more likely elected as a
clusterhead (CH). The intercluster and intracluster communications are realized on one hop.
The principal goal of our algorithm is to optimize the energy power and energy load among all
nodes. By comparing EDD clustering algorithm with LEACH algorithm, simulation results
have showen its effectiveness in saving energy.
Power quality disturbances classification using complex wavelet phasor space ...journalBEEI
Power quality disturbances (PQD) degrades the quality of power. Detection of these PQDs in real time using smart systems connected to the power grid is a challenge due to the integration of energy generation units and electronic devices. Deep learning methods have shown advantages for PQD classification accurately. PQD events are non-stationary and occur at discrete events. Pre-processing of power signal using dual tree complex wavelet transform in localizing the disturbances according to time-frequency-phase information improves classification accuracy.Phase space reconstruction of complex wavelet sub bands to 2D data and use of fully connected feed forward neural network improves classification accuracy. In this work, a combination of DTCWT-PSR and FC-FFNN is used to classify different complex PSDs accurately.The proposed algorithm is evaluated for its performance considering different network configurations and the most optimum structure is developed. The classification accuracy is demonstrated to be 99.71% for complex PQDs and is suitable for real time activity with reduced complexity.
This paper investigates about the possibility to reduce power consumption in Neural Network using approximated computing techniques. Authors compare a traditional fixed-point neuron with an approximated neuron composed of approximated multipliers and adder. Experiments show that in the proposed case of study (a wine classifier) the approximated neuron allows to save up to the 43% of the area, a power consumption saving of 35% and an improvement in the maximum clock frequency of 20%.
Power consumption is an important metric tool in the context of the wireless sensor networks
(WSNs). In this paper, we described a new Energy-Degree (EDD) Clustering Algorithm for the
WSNs. A node with higher residual energy and higher degree is more likely elected as a
clusterhead (CH). The intercluster and intracluster communications are realized on one hop.
The principal goal of our algorithm is to optimize the energy power and energy load among all
nodes. By comparing EDD clustering algorithm with LEACH algorithm, simulation results
have showen its effectiveness in saving energy.
Power quality disturbances classification using complex wavelet phasor space ...journalBEEI
Power quality disturbances (PQD) degrades the quality of power. Detection of these PQDs in real time using smart systems connected to the power grid is a challenge due to the integration of energy generation units and electronic devices. Deep learning methods have shown advantages for PQD classification accurately. PQD events are non-stationary and occur at discrete events. Pre-processing of power signal using dual tree complex wavelet transform in localizing the disturbances according to time-frequency-phase information improves classification accuracy.Phase space reconstruction of complex wavelet sub bands to 2D data and use of fully connected feed forward neural network improves classification accuracy. In this work, a combination of DTCWT-PSR and FC-FFNN is used to classify different complex PSDs accurately.The proposed algorithm is evaluated for its performance considering different network configurations and the most optimum structure is developed. The classification accuracy is demonstrated to be 99.71% for complex PQDs and is suitable for real time activity with reduced complexity.
This paper investigates about the possibility to reduce power consumption in Neural Network using approximated computing techniques. Authors compare a traditional fixed-point neuron with an approximated neuron composed of approximated multipliers and adder. Experiments show that in the proposed case of study (a wine classifier) the approximated neuron allows to save up to the 43% of the area, a power consumption saving of 35% and an improvement in the maximum clock frequency of 20%.
Microgrids are the solution to the growing demand for energy in the recent times. It has the potential to improve local reliability, reduce cost and increase penetration rates for distributed renewable energy generation. Inclusion of Renewable Energy Systems(RES) which have become the topic of discussion in the recent times due to acute energy crisis, causes the power flow in the microgrid to be bi-directional in nature. The presence of the RES in the microgrid system causes the grid to be reconfigurable. This reconfiguration might also occur due to load or utility grid connection and disconnection. Thus conventional protection strategies are not applicable to micro-grids and is hence challenging for engineers to protect the grid in a fault condition. In this paper various Minimum Spanning Tree(MST) algorithms are applied in microgrids to identify the active nodes of the current topology of the network in a heuristic approach and thereby generating a tree from the given network so that minimum number of nodes have to be disconnected from the network during fault clearance. In the paper we have chosen the IEEE-39 and IEEE-69 bus networks as our sample test systems.
Optimal Placement of Dynamic Voltage Restorer in Distribution Systems for Vol...IJERA Editor
This paper deals with Dynamic Voltage Restorer (DVR) allocation in radial distribution systems by injecting series voltage. The DVR is used to inject both real and reactive powers into the system for voltage profile improvement and active and reactive power loss minimization. The objective of this paper is to identify the optimal location and series voltage of DVR using Particle Swarm Optimization (PSO) algorithm. The proposed method is tested on standard IEEE 33-bus system and the results are presented.
E NERGY D EGREE D ISTANCE C LUSTERING A LGORITHM FOR W Snsijwmn
Energy consumption is an important parameter in th
e context of the wireless sensor networks (WSNs).
Several factors can cause energy over consumption s
uch as mobility, node position (relay or gateway),
retransmissions... In this paper, we described a ne
w Energy-Degree Distance(EDD) Clustering Algorithm
for the WSNs. A node with higher residual energy,
higher degree and closer to the base station is mor
e
likely elected as a clusterhead (CH). The inter clu
ster and intra cluster communications are realized
on one
hop. The principal goal of our algorithm is to min
imize the energy consumption and balance energy
consumption among all nodes. By comparing EDD clust
ering algorithm with LEACH algorithm,
simulation results have shown its effectiveness i
n saving energy
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Network Reconfiguration of Distribution System for Loss Reduction Using GWO A...IJECEIAES
This manuscript presents a feeder reconfiguration in primary distribution networks with an objective of minimizing the real power loss or maximization of power loss reduction. An optimal switching for the network reconfiguration problem is introduced in this article based on step by step switching and simultaneous switching. This paper proposes a Grey Wolf Optimization (GWO) algorithm to solve the feeder reconfiguration problem through fitness function corresponding to optimum combination of switches in power distribution systems. The objective function is formulated to solve the reconfiguration problem which includes minimization of real power loss. A nature inspired Grey Wolf Optimization Algorithm is utilized to restructure the power distribution system and identify the optimal switches corresponding minimum power loss in the distribution network. The GWO technique has tested on standard IEEE 33-bus and 69-bus systems and the results are presented.
Modeling of RF Power Amplifier with Memory Effects using Memory PolynomialIJERA Editor
Power Amplifier is one of the most important component in a communication system. It is inherently non-linear and having memory effects. But current communication systems require highly linear response as nonlinearities contribute to gain compression and produce harmonic distortion. But for linearization of power amplifier, it is necessary to model PA's memory behavior accurately. So in this paper, a memory polynomial based power amplifier model is presented which takes into account its memory effects for wideband applications. This paper also presents a comparison of proposed model with actual RF power amplifier in terms of power spectral density and AM/AM characteristics. Simulation results shows its efficiency and accuracy.
Transforming an Existing Distribution Network Into Autonomous MICRO-GRID usin...IJERA Editor
A distribution network with renewable and fossil-based resources can be operated as a micro-grid, in autonomous or nonautonomous modes. Autonomous operation of a distribution network requires cautious planning. In this context, a detailed methodology to develop a sustainable autonomous micro-grid is presented in this paper. The proposed methodology suggests novel sizing and siting strategies for distributed generators and structural modifications for autonomous micro-grids. This paper introduces the Particle Swarm Optimization (PSO) algorithm to solve the optimal network reconfiguration problem for power loss reduction. The PSO is a relatively new and powerful intelligence evolution method for solving optimization problems. It is a population-based approach. The PSO was inspired from natural behavior of the bees on how they find the location of most flowers. The proposed PSO algorithm is introduced with some modifications such as using an inertia weight that decreases linearly during the simulation. This setting allows the PSO to explore a large area at the start of the simulation.
Wideband characteristics of density tapered array antennas IJECEIAES
In this paper, wideband characteristics of density tapered arrays are clarified by comparing directly the array factors and radiation patterns of 3 tapered arrays structures with array factors and radiation patterns of equally spaced arrays. Calculated results for a density tapered distribution array consisting of 30 elements claims that the array can perform within a bandwidth of 2.5:1 with grating lobe levels lower than -7.8 dB. Additionally, this paper shows a method of determining the effectiveness of unequal spacing arrays in the design of actual antennas. This method is based on the calculation and analysis of input impedance of array elements caused by mutual coupling effects among array elements.
Performance Evaluation of Quarter Shift Dual Tree Complex Wavelet Transform B...IJECEIAES
In this paper, multifocus image fusion using quarter shift dual tree complex wavelet transform is proposed. Multifocus image fusion is a technique that combines the partially focused regions of multiple images of the same scene into a fully focused fused image. Directional selectivity and shift invariance properties are essential to produce a high quality fused image. However conventional wavelet based fusion algorithms introduce the ringing artifacts into fused image due to lack of shift invariance and poor directionality. The quarter shift dual tree complex wavelet transform has proven to be an effective multi-resolution transform for image fusion with its directional and shift invariant properties. Experimentation with this transform led to the conclusion that the proposed method not only produce sharp details (focused regions) in fused image due to its good directionality but also removes artifacts with its shift invariance in order to get high quality fused image. Proposed method performance is compared with traditional fusion methods in terms of objective measures.
Distribution Network Reconfiguration Using Binary Particle Swarm Optimization...journalBEEI
Power losses and voltage drop are existing problems in radial distribution networks. This power losses and voltage drop affect the voltage stability level. Reconfiguring the network is a form of approach to improve the quality of electrical power. The network reconfiguration aims to minimize power losses and voltage drop as well as decreasing the Voltage Stability Index (VSI). In this research, network reconfiguration uses binary particle swarm optimization algorithm and Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method to analyze the radial system power flow. This scheme was tested on the 33-bus IEEE radial distribution system 12.66 kV. The simulation results show that before reconfiguration, the active power loss is 202.7126 kW and the VSI is 0.20012. After reconfiguration, the active power loss and VSI decreased to 139.5697 kW and 0.14662, respectively. It has decreased the power loss for 31.3136% significantly while the VSI value is closer to zero.
A hybrid approach for ipfc location and parameters optimization for congestio...eSAT Journals
Abstract
The deregulated power system operation with competitive electricity market environment has been created many challenging tasks to the system operator. The competition with strategic bidding has been resulted for randomness in generation schedule, load withdrawal and power flows across the network. The economic efficiency of electricity market is mainly dependent on network support. In the event of congestion, it is required to alter the base case market settlement and hence the economic inefficiency in terms of congestion cost can occur. In order to anticipate congestion and its consequences in operation, this paper has been considered Interline Power Flow Controller (IPFC).This article proposed a tactical approach for optimal location and then its parameters in Decoupled Power Injection Modeling (DPIM) are optimized using Gravitational Search Algorithm (GSA). The case studies are performed on IEEE 30-bus test system and the results obtained are validating the proposed approach for practical implementations.
Keywords: Deregulated power system, competitive electricity market, congestion management, IPFC, Gravitational Search Algorithm (GSA)
Optimal Capacitor Placement in Distribution System using Fuzzy TechniquesIDES Editor
To improve the overall efficiency of power system,
the performance of distribution system must be improved. It
is done by installing shunt capacitors in radial distribution
system. The problem of capacitor allocation in electric
distribution systems involves maximizing “energy and peak
power (demand) loss reductions” by means of capacitor
installations. As a result power factor of distribution system
improves. There is also lots of saving in terms of money. A 10
bus radial distribution system is taken as the model. Then a
load flow programs is executed on MATLAB. Then by using
load flow data & fuzzy techniques the determination of suitable
location of capacitor placement and its size is done. Shunt
capacitors to be placed at the nodes of the system will be
represented as reactive power injections. Fuzzy techniques have
advantages of simplicity, less computations & fast results. The
same techniques can be applied to complex distribution systems
& dynamic loads.
Microgrids are the solution to the growing demand for energy in the recent times. It has the potential to improve local reliability, reduce cost and increase penetration rates for distributed renewable energy generation. Inclusion of Renewable Energy Systems(RES) which have become the topic of discussion in the recent times due to acute energy crisis, causes the power flow in the microgrid to be bi-directional in nature. The presence of the RES in the microgrid system causes the grid to be reconfigurable. This reconfiguration might also occur due to load or utility grid connection and disconnection. Thus conventional protection strategies are not applicable to micro-grids and is hence challenging for engineers to protect the grid in a fault condition. In this paper various Minimum Spanning Tree(MST) algorithms are applied in microgrids to identify the active nodes of the current topology of the network in a heuristic approach and thereby generating a tree from the given network so that minimum number of nodes have to be disconnected from the network during fault clearance. In the paper we have chosen the IEEE-39 and IEEE-69 bus networks as our sample test systems.
Optimal Placement of Dynamic Voltage Restorer in Distribution Systems for Vol...IJERA Editor
This paper deals with Dynamic Voltage Restorer (DVR) allocation in radial distribution systems by injecting series voltage. The DVR is used to inject both real and reactive powers into the system for voltage profile improvement and active and reactive power loss minimization. The objective of this paper is to identify the optimal location and series voltage of DVR using Particle Swarm Optimization (PSO) algorithm. The proposed method is tested on standard IEEE 33-bus system and the results are presented.
E NERGY D EGREE D ISTANCE C LUSTERING A LGORITHM FOR W Snsijwmn
Energy consumption is an important parameter in th
e context of the wireless sensor networks (WSNs).
Several factors can cause energy over consumption s
uch as mobility, node position (relay or gateway),
retransmissions... In this paper, we described a ne
w Energy-Degree Distance(EDD) Clustering Algorithm
for the WSNs. A node with higher residual energy,
higher degree and closer to the base station is mor
e
likely elected as a clusterhead (CH). The inter clu
ster and intra cluster communications are realized
on one
hop. The principal goal of our algorithm is to min
imize the energy consumption and balance energy
consumption among all nodes. By comparing EDD clust
ering algorithm with LEACH algorithm,
simulation results have shown its effectiveness i
n saving energy
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Network Reconfiguration of Distribution System for Loss Reduction Using GWO A...IJECEIAES
This manuscript presents a feeder reconfiguration in primary distribution networks with an objective of minimizing the real power loss or maximization of power loss reduction. An optimal switching for the network reconfiguration problem is introduced in this article based on step by step switching and simultaneous switching. This paper proposes a Grey Wolf Optimization (GWO) algorithm to solve the feeder reconfiguration problem through fitness function corresponding to optimum combination of switches in power distribution systems. The objective function is formulated to solve the reconfiguration problem which includes minimization of real power loss. A nature inspired Grey Wolf Optimization Algorithm is utilized to restructure the power distribution system and identify the optimal switches corresponding minimum power loss in the distribution network. The GWO technique has tested on standard IEEE 33-bus and 69-bus systems and the results are presented.
Modeling of RF Power Amplifier with Memory Effects using Memory PolynomialIJERA Editor
Power Amplifier is one of the most important component in a communication system. It is inherently non-linear and having memory effects. But current communication systems require highly linear response as nonlinearities contribute to gain compression and produce harmonic distortion. But for linearization of power amplifier, it is necessary to model PA's memory behavior accurately. So in this paper, a memory polynomial based power amplifier model is presented which takes into account its memory effects for wideband applications. This paper also presents a comparison of proposed model with actual RF power amplifier in terms of power spectral density and AM/AM characteristics. Simulation results shows its efficiency and accuracy.
Transforming an Existing Distribution Network Into Autonomous MICRO-GRID usin...IJERA Editor
A distribution network with renewable and fossil-based resources can be operated as a micro-grid, in autonomous or nonautonomous modes. Autonomous operation of a distribution network requires cautious planning. In this context, a detailed methodology to develop a sustainable autonomous micro-grid is presented in this paper. The proposed methodology suggests novel sizing and siting strategies for distributed generators and structural modifications for autonomous micro-grids. This paper introduces the Particle Swarm Optimization (PSO) algorithm to solve the optimal network reconfiguration problem for power loss reduction. The PSO is a relatively new and powerful intelligence evolution method for solving optimization problems. It is a population-based approach. The PSO was inspired from natural behavior of the bees on how they find the location of most flowers. The proposed PSO algorithm is introduced with some modifications such as using an inertia weight that decreases linearly during the simulation. This setting allows the PSO to explore a large area at the start of the simulation.
Wideband characteristics of density tapered array antennas IJECEIAES
In this paper, wideband characteristics of density tapered arrays are clarified by comparing directly the array factors and radiation patterns of 3 tapered arrays structures with array factors and radiation patterns of equally spaced arrays. Calculated results for a density tapered distribution array consisting of 30 elements claims that the array can perform within a bandwidth of 2.5:1 with grating lobe levels lower than -7.8 dB. Additionally, this paper shows a method of determining the effectiveness of unequal spacing arrays in the design of actual antennas. This method is based on the calculation and analysis of input impedance of array elements caused by mutual coupling effects among array elements.
Performance Evaluation of Quarter Shift Dual Tree Complex Wavelet Transform B...IJECEIAES
In this paper, multifocus image fusion using quarter shift dual tree complex wavelet transform is proposed. Multifocus image fusion is a technique that combines the partially focused regions of multiple images of the same scene into a fully focused fused image. Directional selectivity and shift invariance properties are essential to produce a high quality fused image. However conventional wavelet based fusion algorithms introduce the ringing artifacts into fused image due to lack of shift invariance and poor directionality. The quarter shift dual tree complex wavelet transform has proven to be an effective multi-resolution transform for image fusion with its directional and shift invariant properties. Experimentation with this transform led to the conclusion that the proposed method not only produce sharp details (focused regions) in fused image due to its good directionality but also removes artifacts with its shift invariance in order to get high quality fused image. Proposed method performance is compared with traditional fusion methods in terms of objective measures.
Distribution Network Reconfiguration Using Binary Particle Swarm Optimization...journalBEEI
Power losses and voltage drop are existing problems in radial distribution networks. This power losses and voltage drop affect the voltage stability level. Reconfiguring the network is a form of approach to improve the quality of electrical power. The network reconfiguration aims to minimize power losses and voltage drop as well as decreasing the Voltage Stability Index (VSI). In this research, network reconfiguration uses binary particle swarm optimization algorithm and Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method to analyze the radial system power flow. This scheme was tested on the 33-bus IEEE radial distribution system 12.66 kV. The simulation results show that before reconfiguration, the active power loss is 202.7126 kW and the VSI is 0.20012. After reconfiguration, the active power loss and VSI decreased to 139.5697 kW and 0.14662, respectively. It has decreased the power loss for 31.3136% significantly while the VSI value is closer to zero.
A hybrid approach for ipfc location and parameters optimization for congestio...eSAT Journals
Abstract
The deregulated power system operation with competitive electricity market environment has been created many challenging tasks to the system operator. The competition with strategic bidding has been resulted for randomness in generation schedule, load withdrawal and power flows across the network. The economic efficiency of electricity market is mainly dependent on network support. In the event of congestion, it is required to alter the base case market settlement and hence the economic inefficiency in terms of congestion cost can occur. In order to anticipate congestion and its consequences in operation, this paper has been considered Interline Power Flow Controller (IPFC).This article proposed a tactical approach for optimal location and then its parameters in Decoupled Power Injection Modeling (DPIM) are optimized using Gravitational Search Algorithm (GSA). The case studies are performed on IEEE 30-bus test system and the results obtained are validating the proposed approach for practical implementations.
Keywords: Deregulated power system, competitive electricity market, congestion management, IPFC, Gravitational Search Algorithm (GSA)
Optimal Capacitor Placement in Distribution System using Fuzzy TechniquesIDES Editor
To improve the overall efficiency of power system,
the performance of distribution system must be improved. It
is done by installing shunt capacitors in radial distribution
system. The problem of capacitor allocation in electric
distribution systems involves maximizing “energy and peak
power (demand) loss reductions” by means of capacitor
installations. As a result power factor of distribution system
improves. There is also lots of saving in terms of money. A 10
bus radial distribution system is taken as the model. Then a
load flow programs is executed on MATLAB. Then by using
load flow data & fuzzy techniques the determination of suitable
location of capacitor placement and its size is done. Shunt
capacitors to be placed at the nodes of the system will be
represented as reactive power injections. Fuzzy techniques have
advantages of simplicity, less computations & fast results. The
same techniques can be applied to complex distribution systems
& dynamic loads.
Novel Artificial Control of Nonlinear Uncertain System: Design a Novel Modifi...Waqas Tariq
This research is focused on novel particle swarm optimization (PSO) SISO Lyapunov based fuzzy estimator sliding mode algorithms derived in the Lyapunov sense. The stability of the closed-loop system is proved mathematically based on the Lyapunov method. PSO SISO fuzzy compensate sliding mode method design a SISO fuzzy system to compensate for the dynamic model uncertainties of the nonlinear dynamic system and chattering also solved by nonlinear fuzzy saturation like method. Adjust the sliding function is played important role to reduce the chattering phenomenon and also design acceptable estimator applied to nonlinear classical controller so PSO method is used to off-line tuning. Classical sliding mode control is robust to control model uncertainties and external disturbances. A sliding mode method with a switching control low guarantees the stability of the certain and/or uncertain system, but the addition of the switching control low introduces chattering into the system. One way to reduce or eliminate chattering is to insert a nonlinear (fuzzy) boundary like layer method inside of a boundary layer around the sliding surface. Classical sliding mode control method has difficulty in handling unstructured model uncertainties. One can overcome this problem by applied fuzzy inference system into sliding mode algorithm to design and estimate model-free nonlinear dynamic equivalent part. To approximate a time-varying nonlinear dynamic system, a fuzzy system requires a large amount of fuzzy rule base. This large number of fuzzy rules will cause a high computation load. The addition of PSO method to a fuzzy sliding mode controller to tune the parameters of the fuzzy rules in use will ensure a moderate computational load. The PSO method in this algorithm is designed based on the PSO stability theorem. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov.
ECONOMIC LOAD DISPATCH USING PARTICLE SWARM OPTIMIZATIONMln Phaneendra
In this ppt particle swarm optimization (PSO) is applied to allot the active power among the generating stations satisfying the system constraints and minimizing the cost of power generated.The viability of the method is analyzed for its accuracy and rate of convergence. The economic load dispatch problem is solved for three and six unit system using PSO and conventional method for both cases of neglecting and including transmission losses. The results of PSO method were compared with conventional method and were found to be superior.
Design Optimization of Energy and Delay Efficient Wireless Sensor Network wit...IOSR Journals
Abstract: In WSN sensors are randomly deployed in the sensor field which brings the coverage problem and limited energy resources. Hence energy and coverage problem are very scarce resources for such sensor systems and has to be managed wisely in order to extend the life of the sensors and maximizing coverage for the duration of a particular mission. In past a lot of cluster based algorithm and techniques were used. In this paper we propose combination of PSO based algorithm and cluster based Least Spanning Tree algorithm, which are very effective alone for WSN, and we also obtain life of sensor node and data transmission by LST based PSO algorithm. These techniques effectively overcome the problems of low energy and coverage of sensor range. Keywords: Energy efficient clustering, Least Spanning Tree algorithm, PSO algorithm, Wireless Sensor Networks.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
Particle Swarm Optimization based Network Reconfiguration in Distribution Sys...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
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The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
International Journal of Computational Engineering Research(IJCER) ijceronline
nternational Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Network loss reduction and voltage improvement by optimal placement and sizin...nooriasukmaningtyas
Minimization of real power loss and improvement of voltage authenticity of
the network are amongst the key issues confronting power systems owing to
the heavy demand development problem, contingency of transmission and
distribution lines and the financial costs. The distributed generators (DG) has
become one of the strongest mitigating strategies for the network power loss
and to optimize voltage reliability over integration of capacitor banks and
network reconfiguration. This paper introduces an approach for the
optimizing the placement and sizes of different types of DGs in radial
distribution systems using a fine-tuned particle swarm optimization (PSO).
The suggested approach is evaluated on IEEE 33, IEEE 69 and a real
network in Malaysian context. Simulation results demonstrate the
productiveness of active and reactive power injection into the electric power
system and the comparison depicts that the suggested fine-tuned PSO
methodology could accomplish a significant reduction in network power loss
than the other research works.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
Distribution network reconfiguration for loss reduction using PSO method IJECEIAES
In recent years, the reconfiguration of the distribution network has been proclaimed as a method for realizing power savings, with virtually zero cost. The current trend is to design distribution networks with a mesh network structure, but to operate them radially. This is achieved by the establishment of an appropriate number of switchable branches which allow the realization of a radial configuration capable of supplying all of the normal defects in the box of permanent defect. The purpose of this article is to find an optimal reconfiguration using a Meta heuristic method, namely the particle swarm optimization method (PSO), to reduce active losses and voltage deviations by taking into account certain technical constraints. The validity of this method is tested on a 33-IEEE test network and the results obtained are compared with the results of basic load flow.
A hybrid approach of artificial neural network-particle swarm optimization a...IJECEIAES
This paper proposes an under-frequency load shedding (UFLS) method by using the optimization technique of artificial neural network (ANN) combined with particle swarm optimization (PSO) algorithm to determine the minimum load shedding capacity. The suggested technique using a hybrid algorithm ANN-PSO focuses on 2 main goals: determine whether process shedding plan or not and the distribution of the minimum of shedding power on each demand load bus in order to restore system’s frequency back to acceptable values. In the hybrid algorithm ANN-PSO, the PSO algorithm takes responsible for searching the optimal weights in the neural network structure, which can help to optimize the network training in terms of training speed and accuracy. The distribution of shedding power at each node considering the primary control and secondary control of the generators’ unit and the phase electrical distance between the outage generators and load nodes. The effectiveness of the proposed method is experimented with multiple generators outage cases at various load levels in the IEEE-37 Bus scheme where load shedding cases are considered compared with other traditional technique.
Reliability improvement and loss reduction in radial distribution system wit...IJECEIAES
Studies on load flow in electrical distribution system have always been an area of interest for research from the previous few years. Various approaches and techniques are brought into light for load flow studies within the system and simulation tools are being used to work out on varied characteristics of system. This study concentrates on these approaches and the improvements made to the already existing techniques considering time and the algorithms complexity. Also, the paper explains the network reconfiguration (NR) techniques considered in reconfiguring radial distribution network (RDN) to reduce power losses in distribution system and delivers an approach to how various network reconfiguration techniques support loss reduction and improvement of reliability in the electrical distribution network.
Static VAR Compensators (SVCs) is a Flexible Alternating Current Transmission System (FACTS) device that can control the power flow in transmission lines by injecting capacitive or inductive current components at the midpoint of interconnection line or in load areas. This device is capable of minimizing the overall system losses and concurrently improves the voltage stability. A line index, namely SVSI becomes indicator for the placement of SVC and the parameters of SVCs are tuned by using the multi-objective evolutionary programming technique, effectively able to control the power. The algorithm was tested on IEEE-30 Bus Reliability Test System (RTS). Comparative studies were conducted based on the performance of SVC in terms of their location and sizing for installations in power system.
Network reconfiguration to improve reliability indices and efficiency in dist...INFOGAIN PUBLICATION
Failure statistics show that distribution networks engage the most contribution the customer unavailability services. Because optimal reconfiguration of distribution systems has many advantages. Sothis paper presents an efficient hybrid Big Bang-Big Crunch optimization (HBB-BC) algorithm to solve the single-objective reconfiguration of improve the objective functions of the problem such as system average interruption frequency index, system average interruption duration index, average energy not supplied, in distribution systems. So that each objective is calculated in this optimization process. The HBB-BC is a powerful algorithm and has fast convergence. This algorithm using the Particle congestion Optimization (PSO) capacities improves the susceptibility of the Big Bang- Big Crunch (BB-BC) algorithm for better discovery. In addition, the HBB-BC uses a mutation operator after position updating to avoid local optimum and to explore new search areas. The effectiveness of the proposed algorithm is show on balanced test distribution systems. The simulation results are compared with the other solution obtained by other approach.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
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1. Innovative Systems Design and Engineering www.iiste.org
ISSN 2222-1727 (Paper) ISSN 2222-2871 (Online)
Vol 2, No 5, 2011
A Heuristic Based Multi-Objective Approach for
Network Reconfiguration of Distribution Systems
V. Raj Kumar (Corresponding author)
Department of Electrical & Electronics Engineering, GITAM Institute of Technology,
GITAM University, Visakhapatnam, Andhra Pradesh, India.
E-mail : coolvrajkumar@gmail.com
B.Viswanath
Department of Electrical & Electronics Engineering,
GVP College of Engineering (Autonomous), Visakhapatnam, India.
E- mail: bviswanath_108@yahoo.com
D. Vijaya Kumar
Department of Electrical & Electronics Engineering, GITAM Institute of Technology,
GITAM University, Visakhapatnam, Andhra Pradesh., India.
E- mail : divjaykumar74@gmail.com
B. Venkata Ramana
Department of Electrical & Electronics Engineering,
LENDI Institute of Engineering & Technology, Vizianagaram, India.
E-mail :venkat.boyi@gmail.com
Abstract
This paper presents an algorithm for network reconfiguration based on the heuristic rules and fuzzy multi-
objective approach with an improved Fast Decoupled load flow algorithm. Multiple objectives are
considered to minimize the real power loss, deviation in bus voltages, branch current violation and for load
balancing among feeders, while subjected to a radial network structure in which all loads kept energized.
These four objectives are modeled with fuzzy sets to evaluate their imprecise nature. Heuristic rules are
also incorporated in the algorithm for drastically minimizing the number of tie-switch operations. An
improved Fast Decoupled load flow algorithm with Single Matrix Model (FDC-SMM) has been proposed
for distribution networks. The proposed algorithm is very effective in dealing with reconfiguration
problems of single and multi-feeder networks
Keywords: Multi-objective approach, Reconfiguration, Fuzzy set theory, Fast decoupled load flow
1. Introduction
Network reconfiguration is one of the main functions of the distribution automation. Their configurations
may be varied with switching operations so that all of the loads are supplied and reduce the power loss. The
change in network configuration is performed by opening sectionalizing (normally closed) and closing tie
(normally open) switches of the network. These switchings are performed in such a way that the radiality of
the network. A heuristic algorithm has been presented by Shirmohammadi and Hong (1989). Here the
solution procedure starts by closing all of the network switches which are then opened one after another so
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as to establish the optimum flow pattern in the network is maintained and all of the loads are energized.
Debapriya Das (2006) presented an algorithm for network reconfiguration based on fuzzy multi-objective
approach. Four multiple objectives were considered for minimization of (i) real power loss (ii) nodes
voltage deviation (iii) branch current constraint violation and (iv) feeder load imbalance and were modeled
by fuzzy sets. Distribution system reconfiguration for loss reduction was first proposed by Merlin and Back
(1975). They have used a branch-and-bound-type optimization technique to determine the minimum loss
configuration. In this method, all network switches are first closed to form a meshed network. The switches
are then opened successively to restore radial configuration. Taylor and Lubkeman (1990) implemented
heuristic search strategies for feeder reconfiguration. A best-first tree searching strategy, based on
heuristics, was used to evaluate various alternatives. A rule based system was created to avoid exhaustive
search. Civanlar et al. (1988) made use solely of heuristics to determine a distribution system configuration
which would reduce line losses. Civanlar et al. made use of what is known as a “branch exchange”
operation for switching operations: the opening of any switch was required to correspond to the closure of
another switch, ensuring that the radial nature of the distribution system would be preserved. Baran and Wu
(1989) have made an attempt to improve the method of Civanlar et al. (1988) by introducing two
approximation formulas for power flow in the transfer of system loads. The power-flow equations used by
Baran and Wu were defined by recursive approximation of P, Q, and V at each node. Zhou et al. (1997)
have proposed two feeder reconfiguration algorithms for the purpose of service restoration and load
balancing. Their methodologies combined the optimization techniques with heuristic rules and fuzzy logic
for efficiency and robust performance. Taleski and Rajicic (1997) have proposed a method to determine the
configuration with minimum energy losses for a given period. Borozan and Rajakovic (1997) have
considered the application aspects of optimal distribution network reconfiguration. Chichani and Hackam
(1991) proposed a linear programming method using transportation techniques and a heuristic search
method. A comparison was presented with the previously existing optimal load flow based heuristic
techniques.
In this paper a method is presented considering multiple objectives for network reconfiguration in which all
loads are kept energized. Heuristic rules are also incorporated in the proposed algorithm and considers only
few switches to get the optimal solution. The proposed algorithm reduces the required number of load flow
runs, thereby relieving from large computational burden.
2. Membership Functions of Different Objectives
In the fuzzy domain, each objective is associated with a membership function. The membership function
indicates the degree of satisfaction of the objective. In the crisp domain, either the objective is satisfied or it
is violated, implying membership values of unity and zero, respectively. On the contrary, fuzzy sets
entertain varying degrees of membership function values from zero to unity. The membership function
consists of a lower and upper bound value together with a strictly monotonically decreasing and continuous
function for different objectives which are described below.
2.1 Membership Function For Real Power Loss Reduction (µ i)
L
The basic purpose for this membership function is to reduce the real power loss of the system.
PLOSS (i)
Let xi be defined as xi , for i = 1,2,…Nk. (1)
PLOSS 0
Where Nk is the total number of branches in the newly formed loop including tie- branch when kth tie-
switch is closed, PLOSS(i) is the total real power loss of the radial configuration of the system when ith
branch in the loop is opened, and PLOSS° is the total real power loss before network reconfiguration.
Equation (1) indicates that if xi is high, power loss reduction is low and, hence, a lower membership value
is assigned and if xi is low, the power loss reduction is high and a higher membership value is assigned.
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ISSN 2222-1727 (Paper) ISSN 2222-2871 (Online)
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Fig. 1. Membership function for power-loss reduction.
The membership function for real power loss reduction is given in Fig.1. and µLi can be written as
xmax xi
Li , for xmin < xi < xmax
xmax xmin
µLi = 1, for xi ≤ xmin
µLi = 0, for xi ≥ xmax (2)
In this paper, it has been assumed that maximum reduction in losses is 50% and minimum reduction is 0%.
Thus, xmin=0.5 and xmax=1.0. This means if the active power loss is 50% or less of the base case PLOSS 0,
the unity membership value is assigned and if the loss is equals (100%) or more than base case PLOSS 0,
the zero membership value is assigned. This implies that any branch opening in newly formed loop which
causes higher losses need to be ignored.
2.2 Membership Function for Maximum Node Voltage Deviation (µ i)
V
The basic purpose of this membership function is that the deviation of nodes voltage should be less.
Let ΔVi be defined as ΔVi = max|Vi,j - Vs|, for i =1,2,…Nk , j = 1,2,…NB (3)
where, Nk is total number of branches including the tie branch in the newly formed loop when the kth tie
switch is closed;
NB is the total number of nodes in the system;
Vs is the Voltage of the substation (in per unit);
Vi,j is the Voltage of node j corresponding to the opening of the ith branch in the newly formed loop (in
per unit).
If the maximum value of nodes voltage deviation is less, then a higher membership value is assigned and if
deviation is more, then a lower membership value is assigned.
Fig. 2. Membership function for maximum node voltage deviation.
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From Fig.2 it can written
µVi=(ΔVmax-ΔVi)/( ΔVmax-ΔVmin) for ΔVmin<ΔVi<ΔVmax
µVi=1, for ΔVi ≤ ΔVmin.
µVi=0, for ΔVi ≥ΔVmax. (4)
In this paper, ΔVmin = 0.05 and ΔVmax = 0.10 have been considered. ΔVmin = 0.05 means if the substation
voltage is 1.0 p.u., then the minimum system voltage will be 0.95 p.u. and if system voltage is greater than
or equal to 0.95 p.u., the unity membership value is assigned. Similarly if ΔV max is 0.10, the permissible
minimum system voltage will be 0.90 p.u. and if the minimum system voltage is less than or equals to 0.90
p.u., then zero membership value is assigned.
2.3 Membership Function for Maximum Branch Current Loading Index (µ i)
A
The basic purpose for this membership function is to minimize the branch current constraint violation.
Let Branch current loading index be defined as,
I (i, m)
Branch current loading index , m = 1,2,…NB-1 for i = 1,2,…Nk (5)
I c ( m)
where,
Nk :total number of branches in the loop including the tie branch when the kth tie switch is closed;
I(i, m) :magnitude of current of branch-m when the ith branch in the loop is opened;
Ic(m) :line capacity of branch-m;
NB :total number of the nodes of the system.
I (i, m)
Let zi be defined as zi max , for m=1,2....NB-1. for i = 1,2,…Nk (6)
I c ( m)
When the maximum value of branch current loading index exceeds unity, a lower membership value is
assigned and as long as it is less than or equal to unity, the maximum membership value is assigned (i.e.,
unity).
Fig.3: Membership Function For Maximum Branch Current Loading Index.
The membership function for the maximum branch current loading index is shown in Fig.3 and it can
written,
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Vol 2, No 5, 2011
zmax zi
Ai , for zmin < z < zmax
zmax zmin
µAi =1, for zi ≤ zmin.
µAi =0, for zi ≥ zmax. (7)
In this case, zmin = 1.0 and zmax = 1.15 have been considered. zmin = 1.0 indicates that as long as the branch
currents of the system are less than or equal to their respective line capacity, unity membership value is
assigned and zmax = 1.15 indicates that 15% overloading is allowed for each branch and if in any branch, the
current is greater than or equal to 1.15 times the line capacity, a zero membership value is assigned
2.4 Membership Function for Feeder Load Balancing (µ i)
B
Load balancing is one of the major objectives of feeder reconfiguration. An effective strategy to increase
the loading margin of heavily loaded feeders is to transfer part of their loads to lightly loaded feeders.
Feeder load balancing index may be given as
( IFFi max IFi , j )
FLBi , j , j = 1,2,…NF for i = 1,2,…Nk (8)
IFFi max
where
Nk : total number of branches in the loop including the tie branch when the kth tie switch is closed;
NF : total number of feeders;
IFi,j : current of feeder j corresponding to the opening of the ith branch in the loop;
IFFimax: maximum value of the feeder currents of various feeders corresponding to the opening of the ith
branch in the loop = max(IFij), forj = 1,2,… NF.
Let fi be defined as fi = max(FLBi,j), for j = 1,2,…NF for i = 1,2,…Nk (9)
Equation (9) indicates that a better load balancing can be achieved if the value of f i is low. Therefore, for
lower fi, a higher membership grade is assigned and for higher fi, a lower membership grade is assigned.
Fig.4: Membership Function For The Load Balancing Index.
From Fig. 4, we can write
µBi = (fmax - fi)/(fmax - fmin) for fmin < f < fmax
µBi = 1.0, for fi ≤ fmin
µBi = 0, for fi ≥ fmax. (10)
In this case, fmin = 0.10 and fmax = 0.50 have been considered. fmin = 0.10 indicates that the maximum
deviation of feeder currents will be 10% with respect to the maximum value of feeder current and if this
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deviation is less than or equal to 10%, the unity membership value is assigned and f max = 0.50 indicates that
if this deviation is greater than 50%, a zero membership value is assigned.
3. Optimization In Fuzzy Environment
When there are multiple objectives to be satisfied simultaneously, a compromise has to be made to get the
best solution. One solution methodology for the multiobjective optimization in fuzzy framework is based
on the max-min principle which is described as below.
Step 1)
Let Ntie be the number of tie switches in a given distribution network. Assume that kth tie switch is closed.
Then Nk branches are observed in the newly formed loop. For each kth tie switch closed and ith branch
opened, the membership values of all the different objectives are evaluated. After opening the ith branch in
this loop (radial structure is retained), the load-flow run was carried out to compute µLi, µVi, µAi, and µBi,
for i = 1,2,…Nk using equations (2), (4), (7) and (10) respectively. This aspect needs very large CPU time
as it needs to cover Nk branches for each k-tie switch case and the same is to be repeated for Ntie switches.
Step 2)
The degree of overall satisfaction (Dk,i) for this option is the minimum of all the above membership values.
Now, a fuzzy decision for overall satisfaction may be defined as the choice that satisfies all of the
objectives and if we interpret this as a logical “and”, it can be modelled with the intersection of the fuzzy
sets. In this thesis work, classical fuzzy set intersection is used and the fuzzy decision for overall
satisfaction is then given by Dk,i = min{µLi, µVi, µAi, and µBi}, for i = 1,2,…Nk.
Step 3)
The optimal solution (OSk) is the maximum of all such overall degrees of satisfaction. Now, a fuzzy
decision for an optimal solution may be defined as the choice that maximizes all such overall degrees of
satisfaction and if we interpret this as a logical “or” we can model it with the union of fuzzy sets. In this
thesis work, the classical fuzzy set union is used and the fuzzy decision for an optimal solution is then
given by OSk = max{Dk,i}, for i = 1,2,…Nk.
At the end of step 3, it will be indicating the optimal branch i to be opened with the k th tie switch closed.
The above process (steps 1 to 3) is to be repeated for remaining tie-switch cases identifying the tie-switch
which has maximum voltage deviation across its nodes.
4. Heuristic Rules For Minimizing The Number Of Tie-Switch Operations And Algorithm
In the present work, heuristic rules are considered which minimize the number of tie-switch operations.
These heuristic rules are explained below.
In the first iteration, compute the voltage difference across all of the open tie switches and detect the open
tie switch across which the voltage difference is maximum. If this maximum voltage difference is greater
than some specified value ( ) , then this tie switch is considered first. It is expected that because of the
largest voltage difference, this switching will cause maximum loss reduction, improve minimum system
voltage, and will provide better load balancing. In the next iteration, the same procedure is repeated for the
remaining tie-switches and so forth.
If, in any iteration, this maximum voltage difference is less than the specified value ( ) , then this tie-
switch operation is discarded and automatically other tie-switch operations are discarded because the
voltage difference across all other open tie switches is less than .
4.1 Algorithm for the Proposed Heuristic Based Fuzzy Method
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ISSN 2222-1727 (Paper) ISSN 2222-2871 (Online)
Vol 2, No 5, 2011
A complete algorithm for the proposed heuristic based fuzzy method of the network reconfiguration
process is given below:
Step 1) Read system data;
Step2) Run the SMM YY model load-flow program for radial distribution networks;
Step 3) Compute the voltage difference across the open tie switches (i.e., ∆V tie(i) for i 1,2,…ntie);
Step 4) Identify the open tie switch across which the voltage difference is maximum and its code k
(i.e., ΔVtie,max = ΔVtie(k));
Step 5) If ∆Vtie,max > ε, go to Step 6); otherwise, go to Step 10);
Step 6) Select the tie switch “k” and identify the total number of loop branches (Nk) including the tie
branch when the tie-switch “k” is closed;
Step 7) Open one branch at a time in the loop and evaluate the membership value for each objective and
also evaluate the overall degree of satisfaction (i.e., for I = 1 to Nk, compute µLi, µVi, µAi, and µBi
using (2), (4), (7)and (10), respectively, and evaluate: D k,i=min{µLi, µVi, µAi, and µBi}
Step 8) Obtain the optimal solution for that operation of tie-switch “k,” (i.e., OS k=max{Dk,i},
for i = 1,2,…,Nk);
Step 9) ntie = ntie – 1. If ntie>0 go to step 2;
Step 10) Print output results;
Step 11) Stop
5. Test Cases
The proposed algorithm has been tested on 33, 69 and 70 bus Distribution systems. 33 bus system is
having single substation with 5 – tie switches. 69 bus system also has single substation with 5-tie switches.
The 70 bus system is with two substations, four feeders and 11- tie switches.
5.1 33-Bus Single Feeder Circuit (Single Substation)
----------------- Tie-switches
__________ sectionalizing switches
Fig. 5. Bus System Before Reconfiguration
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Fig.6. Bus System After Reconfiguration
5.2 69-Bus Single Feeder Circuit (Single Substation)
Fig.7. Bus System Before Reconfiguration
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Fig.8. Bus System After Reconfiguration
5.3 Bus Four Feeder Circuit (Two Substations)
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Fig.9. 70 Bus System Before Reconfiguration
Fig.10. 70 Bus System After Reconfiguration
6. RESULTS
For a 33-Bus Single Feeder Circuit (Single Substation)
Before network reconfiguration,
The total real power loss is 373.63 KW.
The minimum voltage is Vmin = V33 = 0.877172 p.u.
After reconfiguration,
The total real power loss is 243.99 kW.
The minimum voltage is Vmin =V32 = 0.899635 p.u.
After network reconfiguration, the real power loss reduction is 34.7% and minimum voltage of the system
has improved from 0.877172 to 0.899635 p.u.
Table1. Optimal Solution for Tie Switch Operation of 33 Bus System
Tie-Switch Operation Optimal Solution
(Tie-k) (Osk)
tie-1 0.156802
tie-4 0.181545
tie-3 0.189632
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tie-7 0.20084
tie-11 0.207366
Table 2. Feeder Currents of 33 Bus System
Feeders Current ( Amp.)
Before After
Reconfiguration Reconfiguration
IF1 = 99.11 IF1 = 115.87
IF2 = 106.73 IF2 =129.42
IF3 =159.38 IF3 = 131.71
IF4 =147.34 IF4 = 133.24
From Table 2, it is seen that the feeders current are more balanced after reconfiguration.
Fig.11 Line Losses of 33, 69&70 Bus Systems Before & After Reconfiguration
7. Conclusion
In this paper, a heuristic-based fuzzy multi-objective algorithm has been presented to solve the network
reconfiguration problem in a radial distribution system.
The objectives considered attempt to maximize the fuzzy satisfaction of Minimization of real power
loss, minimization of the deviations of nodes voltage, minimization of the branch current constraint
violation and feeder load balancing among various feeders subject to the radial network structure in which
all loads must be energized.
The algorithm also minimizes the number of tie-switch operations, the obtained results are quite good
and they encourage the implementation of the strategy on a large-size distribution network.
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