International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Firefly Algorithm to Opmimal Distribution of Reactive Power Compensation Units IJECEIAES
The issue of electric power grid mode of optimization is one of the basic directions in power engineering research. Currently, methods other than classical optimization methods based on various bio-heuristic algorithms are applied. The problems of reactive power optimization in a power grid using bio-heuristic algorithms are considered. These algorithms allow obtaining more efficient solutions as well as taking into account several criteria. The Firefly algorithm is adapted to optimize the placement of reactive power sources as well as to select their values. A key feature of the proposed modification of the Firefly algorithm is the solution for the multi-objective optimization problem. Algorithms based on a bio-heuristic process can find a neighborhood of global extreme, so a local gradient descent in the neighborhood is applied for a more accurate solution of the problem. Comparison of gradient descent, Firefly algorithm and Firefly algorithm with gradient descent is carried out.
Design of Full Order Optimal Controller for Interconnected Deregulated Power ...ijceronline
International 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.
Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimizationijeei-iaes
This paper presents, an Adaptive Cat Swarm Optimization (ACSO) for solving reactive power dispatch problem. Cat Swarm Optimization (CSO) is one of the new-fangled swarm intelligence algorithms for finding the most excellent global solution. Because of complication, sometimes conventional CSO takes a lengthy time to converge and cannot attain the precise solution. For solving reactive power dispatch problem and to improve the convergence accuracy level, we propose a new adaptive CSO namely ‘Adaptive Cat Swarm Optimization’ (ACSO). First, we take account of a new-fangled adaptive inertia weight to velocity equation and then employ an adaptive acceleration coefficient. Second, by utilizing the information of two previous or next dimensions and applying a new-fangled factor, we attain to a new position update equation composing the average of position and velocity information. The projected ACSO has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the high-quality performance of the planned algorithm in tumbling the real power loss.
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
Economic/Emission Load Dispatch Using Artificial Bee Colony AlgorithmIDES Editor
This paper presents an application of the
artificial bee colony (ABC) algorithm to multi-objective
optimization problems in power system. A new multiobjective
artificial bee colony (MOABC) algorithm to
solve the economic/ emission dispatch (EED) problem is
proposed in this paper. Non-dominated sorting is
employed to obtain a Pareto optimal set. Moreover, fuzzy
decision theory is employed to extract the best
compromise solution. A numerical result for IEEE 30-bus
test system is presented to demonstrate the capability of
the proposed approach to generate well-distributed
Pareto-optimal solutions of EED problem in one single
run. In addition, the EED problem is also solved using the
weighted sum method using ABC. Results obtained with
the proposed approach are compared with other
techniques available in the literature. Results obtained
show that the proposed MOABC has a great potential in
handling multi-objective optimization problem.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Firefly Algorithm to Opmimal Distribution of Reactive Power Compensation Units IJECEIAES
The issue of electric power grid mode of optimization is one of the basic directions in power engineering research. Currently, methods other than classical optimization methods based on various bio-heuristic algorithms are applied. The problems of reactive power optimization in a power grid using bio-heuristic algorithms are considered. These algorithms allow obtaining more efficient solutions as well as taking into account several criteria. The Firefly algorithm is adapted to optimize the placement of reactive power sources as well as to select their values. A key feature of the proposed modification of the Firefly algorithm is the solution for the multi-objective optimization problem. Algorithms based on a bio-heuristic process can find a neighborhood of global extreme, so a local gradient descent in the neighborhood is applied for a more accurate solution of the problem. Comparison of gradient descent, Firefly algorithm and Firefly algorithm with gradient descent is carried out.
Design of Full Order Optimal Controller for Interconnected Deregulated Power ...ijceronline
International 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.
Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimizationijeei-iaes
This paper presents, an Adaptive Cat Swarm Optimization (ACSO) for solving reactive power dispatch problem. Cat Swarm Optimization (CSO) is one of the new-fangled swarm intelligence algorithms for finding the most excellent global solution. Because of complication, sometimes conventional CSO takes a lengthy time to converge and cannot attain the precise solution. For solving reactive power dispatch problem and to improve the convergence accuracy level, we propose a new adaptive CSO namely ‘Adaptive Cat Swarm Optimization’ (ACSO). First, we take account of a new-fangled adaptive inertia weight to velocity equation and then employ an adaptive acceleration coefficient. Second, by utilizing the information of two previous or next dimensions and applying a new-fangled factor, we attain to a new position update equation composing the average of position and velocity information. The projected ACSO has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the high-quality performance of the planned algorithm in tumbling the real power loss.
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
Economic/Emission Load Dispatch Using Artificial Bee Colony AlgorithmIDES Editor
This paper presents an application of the
artificial bee colony (ABC) algorithm to multi-objective
optimization problems in power system. A new multiobjective
artificial bee colony (MOABC) algorithm to
solve the economic/ emission dispatch (EED) problem is
proposed in this paper. Non-dominated sorting is
employed to obtain a Pareto optimal set. Moreover, fuzzy
decision theory is employed to extract the best
compromise solution. A numerical result for IEEE 30-bus
test system is presented to demonstrate the capability of
the proposed approach to generate well-distributed
Pareto-optimal solutions of EED problem in one single
run. In addition, the EED problem is also solved using the
weighted sum method using ABC. Results obtained with
the proposed approach are compared with other
techniques available in the literature. Results obtained
show that the proposed MOABC has a great potential in
handling multi-objective optimization problem.
Optimum Network Reconfiguration using Grey Wolf OptimizerTELKOMNIKA JOURNAL
Distribution system Reconfiguration is the process of changing the topology of the distribution
network by opening and closing switches to satisfy a specific objective. It is a complex, combinatorial
optimization problem involving a nonlinear objective function and constraints. Grey Wolf Optimizer (GWO)
is a recently developed metaheuristic search algorithm inspired by the leadership hierarchy and hunting
strategy of grey wolves in nature. The objective of this paper is to determine an optimal network
reconfiguration that presents the minimum power losses, considering network constraints, and using GWO
algorithm. The proposed algorithm was tested using some standard networks (33 bus, 69 bus, 84 bus and
118 bus), and the obtained results reveal the efficiency and effectiveness of the proposed approach.
Enriched Firefly Algorithm for Solving Reactive Power Problemijeei-iaes
In this paper, Enriched Firefly Algorithm (EFA) is planned to solve optimal reactive power dispatch problem. This algorithm is a kind of swarm intelligence algorithm based on the response of a firefly to the light of other fireflies. In this paper, we plan an augmentation on the original firefly algorithm. The proposed algorithm extends the single population FA to the interacting multi-swarms by cooperative Models. The proposed EFA has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Energy Audit And Management Of Induction Motor Using Field Test And Genetic A...IDES Editor
This paper proposes an economical method that
can be used by industries/plants to make a right decision in
replacing the inefficient induction motors with efficient
ones. proposed method focuses on the field efficiency of
motors without the needs for removing motors and
measuring the output power. The use of a few sets of
measured data from field test coupled with the genetic
algorithms using one operating point for evaluating motor
equivalent circuit parameters instead of using the no load
and blocked-rotor tests is proposed. Test results indicate
that this method has a high accuracy, then it is suitable for
conducting onsite energy audit of motors in order to project
cost savings and payback and to support a confidence
decision regarding the investment in higher efficiency
motors.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
In the deregulated market environment as generation, transmission and distribution are separate entities; reactive power flow in transmission lines is a question of great importance. Due to inductive load characteristic, reactive power is inherently flowing in transmission line. Hence under restructured market this reactive power allocation is necessary. In this work authors presents a power flow tracing based allocation method for reactive power to loads. MVAr-mile method is used for allocation of reactive power cost. A sample 6 bus and IEEE 14 bus system is used for showing the feasibility of developed method.
This paper compares the reduction of harmonics in various level cascaded H-bridge inverters. The switching angles for the cascaded H-bridge inverter were calculated by evolutionary optimization technique. Fourier analysis is used to determine the switching angles for the desired electrical parameters.
Lower order harmonics such as third, fifth, seventh, ninth and eleventh order harmonics were taken into consideration to reduce the total harmonic distortion. Simulation was done for thirteen, fifteen and seventeen level cascaded H-bridge inverters using Matlab. Total harmonic distortion of voltage and current for R, RL and Motor load were analyzed.
Design of High Speed Low Power 15-4 Compressor Using Complementary Energy Pat...CSCJournals
This paper presents the implementation of a novel high speed low power 15-4 Compressor for high speed multiplication applications using single phase clocked quasi static adiabatic logic namely CEPAL (Complementary Energy Path Adiabatic Logic). The main advantage of this static adiabatic logic is the minimization of the 1/2CVth2 energy dissipation occurring every cycle in the multi-phase power-clocked adiabatic circuits. The proposed Compressor uses bit sliced architecture to exploit the parallelism in the computation of sum of 15 input bits by five full adders. The newly proposed Compressor is also centered around the design of a novel 5-3 Compressor that attempts to minimize the stage delays of a conventional 5-3 Compressor that is designed using single bit full adder and half adder architectures. Firstly, the performance characteristics of CEPAL 15-3 Compressor with 14 transistor and 10 transistor adder designs are compared against the conventional static CMOS logic counterpart to identify its adiabatic power advantage. The analyses are carried out using the industry standard Tanner EDA design environment using 250 nm technology libraries. The results prove that CEPAL 14T 15-4 Compressor is 68.11% power efficient, 75.31% faster over its static CMOS counterpart.
Performance assessment of an optimization strategy proposed for power systemsTELKOMNIKA JOURNAL
In the present article, the selection process of the topology of an artificial neural network (ANN) as well as its configuration are exposed. The ANN was adapted to work with the Newton Raphson (NR) method for the calculation of power flow and voltage optimization in the PQ nodes of a 10-node power system represented by the IEEE 1250 standard system. The purpose is to assess and compare its results with the ones obtained by implementing ant colony and genetic algorithms in the optimization of the same system. As a result, it is stated that the voltages in all system nodes surpass 0,99 p.u., thus representing a 20% increase in the optimal scenario, where the algorithm took 30 seconds, of which 9 seconds were used in the training and validation processes of the ANN.
A Threshold Enhancement Technique for Chaotic On-Off Keying SchemeCSCJournals
In this paper, an improvement for Chaotic ON-OFF (COOK) Keying scheme is proposed. The scheme enhances Bit Error Rate (BER) performance of standard COOK by keeping the signal elements at fixed distance from the threshold irrespective of noise power. Each transmitted chaotic segment is added to its flipped version before transmission. This reduces the effect of noise contribution at correlator of the receiver. The proposed system is tested in Additive White Gaussian Noise (AWGN) channel and compared with the standard COOK under different Eb/No levels. A theoretical estimate of BER is derived and compared with the simulation results. Effect of spreading factor increment in the proposed system is studied. Results show that the proposed scheme has a considerable advantage over the standard COOK at similar average bit energy and with higher values of spreading factors.
5. 9375 11036-1-sm-1 20 apr 18 mar 16oct2017 ed iqbal qcIAESIJEECS
In this paper, Tailored Flower Pollination (TFP) algorithm is proposed to solve the optimal reactive power problem. Comprising of the elements of chaos theory, Shuffled frog leaping search and Levy Flight, the performance of the flower pollination algorithm has been improved. Proposed TFP algorithm has been tested in standard IEEE 118 & practical 191 bus test systems and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Atmosphere Clouds Model Algorithm for Solving Optimal Reactive Power Dispatch...ijeei-iaes
In this paper, a new method, called Atmosphere Clouds Model (ACM) algorithm, used for solving optimal reactive power dispatch problem. ACM stochastic optimization algorithm stimulated from the behavior of cloud in the natural earth. ACM replicate the generation behavior, shift behavior and extend behavior of cloud. The projected (ACM) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the superior performance of the proposed algorithm in plummeting the real power loss.
Optimal Allocation of Capacitor Bank in Radial Distribution System using Anal...IJECEIAES
In this paper, a novel analytical technique is proposed for optimal allocation of shunt capacitor bank in radial distribution system. An objective function is formulated to determine the optimal size, number and location of capacitor bank for real & reactive power loss reduction, voltage profile enhancement and annual cost saving. A new constant, Power Voltage Sensitivity Constant (PVSC), has been proposed here. The value of PVSC constant decides the candidate bus location and size. The achievability of the proposed method has been demonstrated on IEEE-69 bus and real distribution system of Jamawaramgarh, Jaipur city. The obtained results are compared with latest optimization techniques to show the effectiveness and robustness of the proposed technique.
Firefly Algorithm based Optimal Reactive Power Flowijceronline
The optimal reactive power flow (ORPF) helps to effectively utilize the existing reactive power sources for minimizing the network loss. Firefly Algorithm (FA), inspired by social flashing behavior of fireflies, is one of the evolutionary computing models for solving multimodal optimization problems. This paper attempts to obtain global best solution of ORPF using FA. The results of IEEE 57 bus system are presented to demonstrate its performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Novel Approach to GSA, GA and Wavelet Transform to Design Fuzzy Logic Contr...IAES-IJPEDS
This paper proposes a novel approach for obtaining a closed loop control
scheme based on Fuzzy Logic Controller to regulate the output voltage
waveform of multilevel inverter. Fuzzy Logic Controller is used to guide and
control the inverter to synthesize a stepped output voltage waveform with
reduced harmonics. In this paper, three different intelligent soft-computing
methods are used to design a fuzzy system to be used as a closed loop control
system for regulating the inverter output. Gravitational Search Algorithm
and Genetic Algorithm are used as optimization methods to evaluate
switching angles for different combination of input voltages applied to MLI.
Wavelet Transform is used as synthesizing technique to shape stepped output
waveform of inverter using orthogonal wavelet sets. The proposed FLC
controlled method is carried out for a wider range of input dc voltages by
considering ±10% variations in nominal voltage value. A 7-level inverter is
used to validate the results of proposed control methods. The three proposed
methods are then compared in terms of various parameters like
computational time, switching angles and THD to justify the performance
and system flexibility. Finally, hardware based results are also obtained to
verify the viability of the proposed method.
Artificial Neural Network Based Fault Classifier for Transmission Line Protec...IJERD Editor
This paper presents a method for classification of transmission line faults based on Artificial Neural Network (ANN).Samples of prefault and postfault three phase currents taken at one end of transmission line are used as ANN inputs. Simulation studies have been carried out extensively on two power system models: one in which the transmission line is fed from one end and another, in which the transmission line is fed from two ends. Different types of faults at different operating conditions have been considered for carrying out simulation studies. The simulation results confirm the feasibility of the proposed approach.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Determining optimal location and size of capacitors in radial distribution ne...IJECEIAES
In this study, the problem of optimal capacitor location and size determination (OCLSD) in radial distribution networks for reducing losses is unraveled by moth swarm algorithm (MSA). MSA is one of the most powerful meta-heuristic algorithm that is taken from the inspiration of the food source finding behavior of moths. Four study cases of installing different numbers of capacitors in the 15-bus radial distribution test system including two, three, four and five capacitors areemployed to run the applied MSA for an investigation of behavior and assessment of performances. Power loss and the improvement of voltage profile obtained by MSA are compared with those fromother methods. As a result, it can be concluded that MSA can give a good truthful and effective solution method for OCLSD problem.
Optimum Network Reconfiguration using Grey Wolf OptimizerTELKOMNIKA JOURNAL
Distribution system Reconfiguration is the process of changing the topology of the distribution
network by opening and closing switches to satisfy a specific objective. It is a complex, combinatorial
optimization problem involving a nonlinear objective function and constraints. Grey Wolf Optimizer (GWO)
is a recently developed metaheuristic search algorithm inspired by the leadership hierarchy and hunting
strategy of grey wolves in nature. The objective of this paper is to determine an optimal network
reconfiguration that presents the minimum power losses, considering network constraints, and using GWO
algorithm. The proposed algorithm was tested using some standard networks (33 bus, 69 bus, 84 bus and
118 bus), and the obtained results reveal the efficiency and effectiveness of the proposed approach.
Enriched Firefly Algorithm for Solving Reactive Power Problemijeei-iaes
In this paper, Enriched Firefly Algorithm (EFA) is planned to solve optimal reactive power dispatch problem. This algorithm is a kind of swarm intelligence algorithm based on the response of a firefly to the light of other fireflies. In this paper, we plan an augmentation on the original firefly algorithm. The proposed algorithm extends the single population FA to the interacting multi-swarms by cooperative Models. The proposed EFA has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Energy Audit And Management Of Induction Motor Using Field Test And Genetic A...IDES Editor
This paper proposes an economical method that
can be used by industries/plants to make a right decision in
replacing the inefficient induction motors with efficient
ones. proposed method focuses on the field efficiency of
motors without the needs for removing motors and
measuring the output power. The use of a few sets of
measured data from field test coupled with the genetic
algorithms using one operating point for evaluating motor
equivalent circuit parameters instead of using the no load
and blocked-rotor tests is proposed. Test results indicate
that this method has a high accuracy, then it is suitable for
conducting onsite energy audit of motors in order to project
cost savings and payback and to support a confidence
decision regarding the investment in higher efficiency
motors.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
In the deregulated market environment as generation, transmission and distribution are separate entities; reactive power flow in transmission lines is a question of great importance. Due to inductive load characteristic, reactive power is inherently flowing in transmission line. Hence under restructured market this reactive power allocation is necessary. In this work authors presents a power flow tracing based allocation method for reactive power to loads. MVAr-mile method is used for allocation of reactive power cost. A sample 6 bus and IEEE 14 bus system is used for showing the feasibility of developed method.
This paper compares the reduction of harmonics in various level cascaded H-bridge inverters. The switching angles for the cascaded H-bridge inverter were calculated by evolutionary optimization technique. Fourier analysis is used to determine the switching angles for the desired electrical parameters.
Lower order harmonics such as third, fifth, seventh, ninth and eleventh order harmonics were taken into consideration to reduce the total harmonic distortion. Simulation was done for thirteen, fifteen and seventeen level cascaded H-bridge inverters using Matlab. Total harmonic distortion of voltage and current for R, RL and Motor load were analyzed.
Design of High Speed Low Power 15-4 Compressor Using Complementary Energy Pat...CSCJournals
This paper presents the implementation of a novel high speed low power 15-4 Compressor for high speed multiplication applications using single phase clocked quasi static adiabatic logic namely CEPAL (Complementary Energy Path Adiabatic Logic). The main advantage of this static adiabatic logic is the minimization of the 1/2CVth2 energy dissipation occurring every cycle in the multi-phase power-clocked adiabatic circuits. The proposed Compressor uses bit sliced architecture to exploit the parallelism in the computation of sum of 15 input bits by five full adders. The newly proposed Compressor is also centered around the design of a novel 5-3 Compressor that attempts to minimize the stage delays of a conventional 5-3 Compressor that is designed using single bit full adder and half adder architectures. Firstly, the performance characteristics of CEPAL 15-3 Compressor with 14 transistor and 10 transistor adder designs are compared against the conventional static CMOS logic counterpart to identify its adiabatic power advantage. The analyses are carried out using the industry standard Tanner EDA design environment using 250 nm technology libraries. The results prove that CEPAL 14T 15-4 Compressor is 68.11% power efficient, 75.31% faster over its static CMOS counterpart.
Performance assessment of an optimization strategy proposed for power systemsTELKOMNIKA JOURNAL
In the present article, the selection process of the topology of an artificial neural network (ANN) as well as its configuration are exposed. The ANN was adapted to work with the Newton Raphson (NR) method for the calculation of power flow and voltage optimization in the PQ nodes of a 10-node power system represented by the IEEE 1250 standard system. The purpose is to assess and compare its results with the ones obtained by implementing ant colony and genetic algorithms in the optimization of the same system. As a result, it is stated that the voltages in all system nodes surpass 0,99 p.u., thus representing a 20% increase in the optimal scenario, where the algorithm took 30 seconds, of which 9 seconds were used in the training and validation processes of the ANN.
A Threshold Enhancement Technique for Chaotic On-Off Keying SchemeCSCJournals
In this paper, an improvement for Chaotic ON-OFF (COOK) Keying scheme is proposed. The scheme enhances Bit Error Rate (BER) performance of standard COOK by keeping the signal elements at fixed distance from the threshold irrespective of noise power. Each transmitted chaotic segment is added to its flipped version before transmission. This reduces the effect of noise contribution at correlator of the receiver. The proposed system is tested in Additive White Gaussian Noise (AWGN) channel and compared with the standard COOK under different Eb/No levels. A theoretical estimate of BER is derived and compared with the simulation results. Effect of spreading factor increment in the proposed system is studied. Results show that the proposed scheme has a considerable advantage over the standard COOK at similar average bit energy and with higher values of spreading factors.
5. 9375 11036-1-sm-1 20 apr 18 mar 16oct2017 ed iqbal qcIAESIJEECS
In this paper, Tailored Flower Pollination (TFP) algorithm is proposed to solve the optimal reactive power problem. Comprising of the elements of chaos theory, Shuffled frog leaping search and Levy Flight, the performance of the flower pollination algorithm has been improved. Proposed TFP algorithm has been tested in standard IEEE 118 & practical 191 bus test systems and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Atmosphere Clouds Model Algorithm for Solving Optimal Reactive Power Dispatch...ijeei-iaes
In this paper, a new method, called Atmosphere Clouds Model (ACM) algorithm, used for solving optimal reactive power dispatch problem. ACM stochastic optimization algorithm stimulated from the behavior of cloud in the natural earth. ACM replicate the generation behavior, shift behavior and extend behavior of cloud. The projected (ACM) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the superior performance of the proposed algorithm in plummeting the real power loss.
Optimal Allocation of Capacitor Bank in Radial Distribution System using Anal...IJECEIAES
In this paper, a novel analytical technique is proposed for optimal allocation of shunt capacitor bank in radial distribution system. An objective function is formulated to determine the optimal size, number and location of capacitor bank for real & reactive power loss reduction, voltage profile enhancement and annual cost saving. A new constant, Power Voltage Sensitivity Constant (PVSC), has been proposed here. The value of PVSC constant decides the candidate bus location and size. The achievability of the proposed method has been demonstrated on IEEE-69 bus and real distribution system of Jamawaramgarh, Jaipur city. The obtained results are compared with latest optimization techniques to show the effectiveness and robustness of the proposed technique.
Firefly Algorithm based Optimal Reactive Power Flowijceronline
The optimal reactive power flow (ORPF) helps to effectively utilize the existing reactive power sources for minimizing the network loss. Firefly Algorithm (FA), inspired by social flashing behavior of fireflies, is one of the evolutionary computing models for solving multimodal optimization problems. This paper attempts to obtain global best solution of ORPF using FA. The results of IEEE 57 bus system are presented to demonstrate its performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Novel Approach to GSA, GA and Wavelet Transform to Design Fuzzy Logic Contr...IAES-IJPEDS
This paper proposes a novel approach for obtaining a closed loop control
scheme based on Fuzzy Logic Controller to regulate the output voltage
waveform of multilevel inverter. Fuzzy Logic Controller is used to guide and
control the inverter to synthesize a stepped output voltage waveform with
reduced harmonics. In this paper, three different intelligent soft-computing
methods are used to design a fuzzy system to be used as a closed loop control
system for regulating the inverter output. Gravitational Search Algorithm
and Genetic Algorithm are used as optimization methods to evaluate
switching angles for different combination of input voltages applied to MLI.
Wavelet Transform is used as synthesizing technique to shape stepped output
waveform of inverter using orthogonal wavelet sets. The proposed FLC
controlled method is carried out for a wider range of input dc voltages by
considering ±10% variations in nominal voltage value. A 7-level inverter is
used to validate the results of proposed control methods. The three proposed
methods are then compared in terms of various parameters like
computational time, switching angles and THD to justify the performance
and system flexibility. Finally, hardware based results are also obtained to
verify the viability of the proposed method.
Artificial Neural Network Based Fault Classifier for Transmission Line Protec...IJERD Editor
This paper presents a method for classification of transmission line faults based on Artificial Neural Network (ANN).Samples of prefault and postfault three phase currents taken at one end of transmission line are used as ANN inputs. Simulation studies have been carried out extensively on two power system models: one in which the transmission line is fed from one end and another, in which the transmission line is fed from two ends. Different types of faults at different operating conditions have been considered for carrying out simulation studies. The simulation results confirm the feasibility of the proposed approach.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Determining optimal location and size of capacitors in radial distribution ne...IJECEIAES
In this study, the problem of optimal capacitor location and size determination (OCLSD) in radial distribution networks for reducing losses is unraveled by moth swarm algorithm (MSA). MSA is one of the most powerful meta-heuristic algorithm that is taken from the inspiration of the food source finding behavior of moths. Four study cases of installing different numbers of capacitors in the 15-bus radial distribution test system including two, three, four and five capacitors areemployed to run the applied MSA for an investigation of behavior and assessment of performances. Power loss and the improvement of voltage profile obtained by MSA are compared with those fromother methods. As a result, it can be concluded that MSA can give a good truthful and effective solution method for OCLSD problem.
A Hybrid Formulation between Differential Evolution and Simulated Annealing A...TELKOMNIKA JOURNAL
The aim of this paper is to solve the optimal reactive power dispatch (ORPD) problem.
Metaheuristic algorithms have been extensively used to solve optimization problems in a reasonable time
without requiring in-depth knowledge of the treated problem. The perform ance of a metaheuristic requires
a compromise between exploitation and exploration of the search space. However, it is rarely to have the
two characteristics in the same search method, where the current emergence of hybrid methods. This
paper presents a hybrid formulation between two different metaheuristics: differential evolution (based on a
population of solution) and simulated annealing (based on a unique solution) to solve ORPD. The first one
is characterized with the high capacity of exploration, while the second has a good exploitation of the
search space. For the control variables, a mixed representation (continuous/discrete), is proposed. The
robustness of the method is tested on the IEEE 30 bus test system.
Capacitor Placement Using Bat Algorithm for Maximum Annual Savings in Radial ...IJERA Editor
This paper presents a two stage approach that determines the optimal location and size of capacitors on radial distribution systems to improve voltage profile and to reduce the active power loss. In first stage, the capacitor locations can be found by using loss sensitivity method. Bat algorithm is used for finding the optimal capacitor sizes in radial distribution systems. The sizes of the capacitors corresponding to maximum annual savings are determined by considering the cost of the capacitors. The proposed method is tested on 15-bus, 33 bus, 34-bus, 69-bus and 85-bus test systems and the results are presented.
Particle Swarm Optimization based Network Reconfiguration in Distribution Sys...theijes
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SIMULTANEOUS OPTIMIZATION OF STANDBY AND ACTIVE ENERGY FOR SUB-THRESHOLD CIRC...VLSICS Design
Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of
dramatically increasing in leakage current. So, leakage power reduction is an important design issue for
active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active
and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the
first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A
slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical
paths gates to ensure low active energy per cycle with the maximum allowable frequency at the
optimal supply voltage. The second phase, determine the optimal reverse body bias that can be applied to
all gates for standby power optimization at the optimal supply voltage determined from the first phase.
Therefore, there exist two sets of gates and two reverse body bias values for each set. The reverse body bias
is switched between these two values in response to the mode of operation. Experimental results are
obtained for some ISCAS-85 benchmark circuits such as 74L85, 74283, ALU74181, and 16 bit RCA. The
optimized circuits show significant energy saving ranged (from 14.5% to 42.28%) and standby power
saving ranged (from 62.8% to 67%).
SIMULTANEOUS OPTIMIZATION OF STANDBY AND ACTIVE ENERGY FOR SUB-THRESHOLD CIRC...VLSICS Design
Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power eduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standbyrgy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In thefirst phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply voltage. The second phase, determine the optimal reverse body bias that can be applied to
all gates for standby power optimization at the optimal supply voltage determined from the first phase. Therefore, there exist two sets of gates and two reverse body bias values for each set. The reverse body bias is switched between these two values in response to the mode of operation. Experimental results are obtained for some ISCAS-85 benchmark circuits such as 74L85, 74283, ALU74181, and 16 bit RCA. The optimized circuits show significant energy saving ranged (from 14.5% to 42.28%) and standby power saving ranged (from 62.8% to 67%).
SIMULTANEOUS OPTIMIZATION OF STANDBY AND ACTIVE ENERGY FOR SUB-THRESHOLD CIRC...VLSICS Design
Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A
slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical
paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply voltage. The second phase, determine the optimal reverse body bias that can be applied to all gates for standby power optimization at the optimal supply voltage determined from the first phase.
Therefore, there exist two sets of gates and two reverse body bias values for each set. The reverse body bias is switched between these two values in response to the mode of operation. Experimental results are obtained for some ISCAS-85 benchmark circuits such as 74L85, 74283, ALU74181, and 16 bit RCA. The optimized circuits show significant energy saving ranged (from 14.5% to 42.28%) and standby power
saving ranged (from 62.8% to 67%)
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.
SIMULTANEOUS OPTIMIZATION OF STANDBY AND ACTIVE ENERGY FOR SUB-THRESHOLD CIRC...VLSICS Design
Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of
dramatically increasing in leakage current. So, leakage power reduction is an important design issue for
active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active
and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the
first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A
slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the
optimal supply voltage. The second phase, determine the optimal reverse body bias that can be applied to
all gates for standby power optimization at the optimal supply voltage determined from the first phase.
Therefore, there exist two sets of gates and two reverse body bias values for each set. The reverse body bias
is switched between these two values in response to the mode of operation. Experimental results are
obtained for some ISCAS-85 benchmark circuits such as 74L85, 74283, ALU74181, and 16 bit RCA. The
optimized circuits show significant energy saving ranged (from 14.5% to 42.28%) and standby power
saving ranged (from 62.8% to 67%).
THRESHOLD SENSITIVE HETEROGENOUS ROUTING PROTOCOL FOR BETTER ENERGY UTILIZATI...ijassn
Advancements in WSN have led to the wide applicability of sensor network in various fields. WSNs basic classification is Reactive and Proactive network. Reactive networks responds to the very immediate changes in its environment in required parameters of interest, as opposed to the Proactive network, due to continuous sensing nature of WSN. To make it more efficient and improved in terms of Energy in network’s
lifetime, we need to reduce the energy expense in the network model, which is one of the most significant issues in wireless sensor networks (WSNs) [1, 2]. In this paper, we proposed an efficient version of TSEP Protocol, which prolongs the networks lifetime by efficient utilization of sensor energy, as we have simulated. We evaluated the performance of our protocol and compared the results with the TSEP. And from the results of simulation, it can be concluded easily that our proposed efficient routing protocol performs better in terms of network lifetime and stability period
THRESHOLD SENSITIVE HETEROGENOUS ROUTING PROTOCOL FOR BETTER ENERGY UTILIZATI...ijassn
Advancements in WSN have led to the wide applicability of sensor network in various fields. WSNs basic classification is Reactive and Proactive network. Reactive networks responds to the very immediate changes in its environment in required parameters of interest, as opposed to the Proactive network, due to continuous sensing nature of WSN. To make it more efficient and improved in terms of Energy in network’s lifetime, we need to reduce the energy expense in the network model, which is one of the most significant issues in wireless sensor networks (WSNs) [1, 2]. In this paper, we proposed an efficient version of TSEP Protocol, which prolongs the networks lifetime by efficient utilization of sensor energy, as we have simulated. We evaluated the performance of our protocol and compared the results with the TSEP. And
from the results of simulation, it can be concluded easily that our proposed efficient routing protocol performs better in terms of network lifetime and stability period.
Modified Headfirst Sliding Routing: A Time-Based Routing Scheme for Bus-Nochy...IJERA Editor
Several interesting topologies emerge by incorporating the third dimension in networks-on-chip (NoC). The Network-on-Chip (NoC) is Network-version of System on-Chip (SoC) means that on-chip communication is done through packet based networks. In NOC topology, routing algorithm and switching are main terminology .The routing algorithm is one of the key factor in NOC architecture. The routing algorithm, which defines as the path taken by a packet between the source and the destination. A good routing algorithm is necessary to improve the network performance. . Here we are proposing a new architecture to improve the throughput and latency of the network. In the proposed approach we are using a fixed path for the packet to transmit from source to destination
Modified Headfirst Sliding Routing: A Time-Based Routing Scheme for Bus-Nochy...
E021052327
1. IOSR Journal of Engineering (IOSRJEN)
e-ISSN: 2250-3021, p-ISSN: 2278-8719, www.iosrjen.org
Volume 2, Issue 10 (October 2012), PP 23-27
www.iosrjen.org 23 | P a g e
Optimal Capacitor Placement for Loss Reduction in Distribution
Systems Using Bat Algorithm
Mrs. V. Usha Reddy1
, A. Manoj2
1
Assistant Professor, Department of EEE, SVU College of Engineering, Tirupati, Andhra Pradesh, India.
2
Department of EEE, SVU College of Engineering, Tirupati, Andhra Pradesh, India
Abstract–– Electricity, today, has not only become a necessity but also a tool for determining the economic
standing and growth of a nation. The exponential growth in demand over the past two decades and the widening
gap between demand and supply is a growing concern. So as to reduce this gap, in addition to adding new
generating units, automation technology is being employed for reducing the T&D losses and therefore the
increasing necessity of fast and efficient algorithms. This paper presents a two stage approach: first, Fuzzy
Logic is used to find optimal capacitor locations and then Bat Algorithm is used to find optimal capacitor sizes
in order to minimize losses. The proposed method is tested on 15-bus and 34-bus test systems and the results are
presented.
Keywords ––Bat Algorithm, Capacitor placement, Distribution system, Fuzzy logic, Metaheuristic
I. INTRODUCTION
New and efficient algorithms for minimising the losses in distribution systems have assumed greater
significance recently since distribution automation requires the most efficient operating scenario for economic
viability variations. In India, with estimated T&D losses of 24% in 2011 and the target of reducing it to 17.1%
by 2017; 14.1% by 2022, the need for fast and efficient methods to reduce losses is imminent. Studies have
indicated that as much as 18% of total power generated is wasted in the form of losses at the distribution level
only. Capacitors are the most commonly used devices for minimizing the losses in distribution system. The
usage of capacitors results in the improvement of power factor, voltage profile, power loss reduction and
available capacity of feeders. With these various objectives in mind, Optimal Capacitor Placement (OCP) aims
to determine capacitor location and its size.
Even though various techniques, like nonlinear optimization techniques [1-5], heuristics [6, 7] and
combinational optimization techniques [8], used to solve OCP problem have various merits, their efficacy relies
entirely on the goodness of data. Advanced techniques like neural networks, fuzzy logic, genetic algorithms
(GA) and particle swarm optimization (PSO) [9-12] overcame this problem. Two stage approach using Fuzzy
and other algorithms [13-16] further improved the results.
In this paper, with a little attention given to load flow analysis of distribution network; a two stage
approach to solve OCP problem is presented. First, fuzzy logic is used to determine the locations of optimal
capacitors and then Bat Algorithm (BA) is used to determine size of optimal capacitors for loss reduction.
With distribution automation, many applications & functions are coming up requiring a robust and efficient
power flow solution method. The Newton-Raphson and fast decoupled load flow solution technique and a host
of their derivatives have efficiently solved the Well Behaved Power Systems for a long time. Distribution
networks, because of the some of the following special features, fail in the category of Ill-conditioned Power
Systems:
Radial or near radial structure
High R/X ratios
Multi-phase, unbalanced operation
Unbalanced distributed load and
Dispersed generation
Hence, special techniques for solving distribution networks which exploit their radial nature have long been
identified.
A modified load-flow technique [17] is considered for solving radial distribution networks. This
method involves only the evaluation of a simple algebraic expression of receiving-end voltages; takes zero
initial loss for computation of voltage of each node and considers flat voltage start to incorporate voltage
convergence. This method is very efficient, has good and fast convergence characteristics.
2. Optimal Capacitor Placement for Loss Reduction in Distribution Systems Using Bat Algorithm
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II. OPTIMAL CAPACITOR LOCATIONS
The efficiency of methods prior to Fuzzy logic, even though good, depends mainly on the goodness of data.
Fuzzy logic provides a remedy for any lack of uncertainty in the data. Fuzzy logic has the advantage of
including heuristics and representing engineering judgments into the optimal capacitor location problem.
Furthermore, the solutions obtained from a fuzzy algorithm can be quickly assessed to determine their feasibility
in being implemented in the distribution system. While designing a fuzzy logic for identifying optimal capacitor
locations, two objectives are considered mainly. They are:
i. To minimise the real power loss and
ii. To maintain voltage within permissible limits
The two inputs for Fuzzy Inference System (FIS) are per unit nodal voltages and power loss indices (PLI). The
output is Capacitor Suitability Index (CSI). The FIS contains a set of rules that determine the capacitor
placement suitability of each node in the distribution system.
The power loss index at each node of the distribution system can be determined by following the steps given
below:
i. Perform the load flow for the original system to obtain the real and reactive power losses.
ii. After compensating the total reactive load at every node of the distribution system, perform the load flow to
calculate the power loss reduction.
iii. The loss reductions are linearly normalised into a range of [0, 1] with largest loss reduction having a value
of „1‟ and the smallest loss reduction having a value of „0‟.
iv. PLI at nth
node is now determined by using the formula given below:
𝑃𝐿𝐼(𝑛) =
lossreduction (n)−𝑙𝑜𝑠𝑠𝑟𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 (𝑚𝑖𝑛 )
lossreduction max −lossreduction (min )
(1)
The inputs and outputs of FIS are modeled by fuzzy membership functions. PLI value varies from 0 to
1. The membership functions for PLI are triangular and are denoted by L, LM, M, HM and H. The value of per
unit nodal voltage ranges from 0.9 to 1.1. The membership functions for per unit nodal voltages are trapezoidal
and triangular and are denoted by L, LN, N, HN and H. CSI value varies from 0 to 1. The membership functions
for CSI are triangular and are denoted by L, LM, M, HM and H. The membership functions of the variables are
shown in figures given below:
Figure 1. Membership function plot for PLI
Figure 2. Membership function plot for per unit nodal voltage
3. Optimal Capacitor Placement for Loss Reduction in Distribution Systems Using Bat Algorithm
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Figure 3. Membership function plot for CSI
Rules framed in the form “IF premise (or antecedent) THEN conclusion (or consequent)” are used to determine
the suitability of a particular node or location for capacitor placement. The rules are framed and summarized in
the fuzzy decision matrix as given in Table 1.
Table 1. Decision Matrix for determining the optimal capacitor locations
AND
Per Unit Voltage
L LN N HN HH
P
L
I
L LM LM L L L
LM M LM LM L L
M HM M LM L L
HM HM HM M LM L
H H HM M LM LM
After receiving the inputs PLI and per unit voltage, the FIS, based on the rules framed in the decision matrix,
calculates the suitability membership function of each node. This is then defuzzified in order to determine the
node suitability ranking. The node having the highest value of CSI is most suitable for capacitor placement.
Therefore the algorithm for finding the optimal capacitor location can be given as:
Step 1: Read the line and load data of the distribution system.
Step 2: Conduct load flow to determine the total active and reactive power losses.
Step 3: Conduct load flow to determine the total power losses after compensating reactive power at every node.
Step 4: Calculate the power loss reduction and PLI.
Step 5: PLI and per unit voltages are given as inputs to FIS
Step 6: Determine CSI by defuzzifying the outputs of FIS.
Step 7: the nodes having the highest value of CSI are most suitable for capacitor placement
III. BAT ALGORITHM
3.1. Introduction
Bat Algorithm (BA) is a nature inspired metaheuristic algorithm developed by Xin-She Yang in 2010.
This paper presents the application of BA for finding the optimum sizes of capacitors after the optimum
locations are determined using fuzzy logic.
Metaheuristic algorithms use certain trade-off of randomization and local search. Randomization provides a
good way to move away from local search to the search on the global scale. Therefore, almost all the
metaheuristic algorithms intend to be suitable for global optimization [18]. This algorithm is based on the
echolocation behavior of micro bats [19]. Micro bats use a type of sonar, called, echolocation, to detect prey,
avoid obstacles and locate their roosting crevices in the dark. These bats emit a very loud sound pulse and
listen for the echo that bounces back from surrounding objects.
Bat algorithm is developed by idealizing some of the characteristics of micro bats. The approximated or
idealized rules are:
a) All bats use echolocation to sense distance and they also know the difference between prey and barriers.
b) Bats fly randomly with velocity vi at position xi with a fixed frequency fmin, varying wavelength λ and
loudness A0 to search for prey. They can automatically adjust the wavelength (or frequency) of their emitted
pulses and the rate of pulse emission r ϵ [0,1] depending on the proximity of the target
c) Loudness varies from a large positive A0 to a minimum constant value Amin.
3.2. Population
The initial population i.e., number of virtual bats for BA (n) is generated randomly. The number of bats
can be anywhere between 10 and 40. After finding the initial fitness of the population for given objective
function, the values are updated based on movement, loudness and pulse rate.
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3.3. Movement of Virtual Bats
The rules for updating the positions xi and velocities vi of the virtual bats are given as
fi = fmin + (fmax-fmin)β (2)
𝑣𝑖
𝑡 = 𝑣𝑖
𝑡−1 + (𝑥𝑖
𝑡 - x* )fi (3)
𝑥𝑖
𝑡
= 𝑥𝑖
𝑡−1
+ 𝑣𝑖
𝑡
(4)
where β ϵ [0,1] is a random vector and
x* is current global best solution.
Once a solution is selected among current best solutions, a new solution for each bat is generated locally using
random walk
xnew = xold + εAt
(5)
where ε ϵ [-1,1] is a random number.
3.4. Loudness and Pulse Emission
The loudness Ai and the rate of pulse emission ri are updated accordingly as the iterations proceed. The
loudness decreases and rate of pulse emission increases as the bat closes on its prey i.e., the equations for
convergence can be taken as
𝐴𝑖
𝑡+1
=α𝐴𝑖
𝑡
(6)
𝑟𝑖
𝑡+1
= 𝑟𝑖
0
[1-exp(-γt)] (7)
where α and γ are constants.
For any 0<α<1 and γ>0, we have
𝐴𝑖
𝑡
0, 𝑟𝑖
𝑡
𝑟𝑖
0
as t∞ (8)
The initial loudness A0 can typically be [1, 2], while the initial emission rate 𝑟𝑖
0
can be [0, 1].
3.5. Implementation of BA
From the equations above, we can implement BA in following steps:
Step 1: Initialize number of bats, number of iterations, loudness A0, and pulse rate ri.
Step 2: Generate the population randomly.
Step 3: Perform load flow to determine active power loss for generated population.
Step 4: Select minimum value as current best solution.
Step 5: Update frequency, velocity and position of bats using equations (2) to (5).
Step 6: Perform load flow for updated values and determine the losses.
Step 7: If the obtained losses are less than the current best solution, then replace the current best solution with
the present obtained value and update loudness and pulse rate using equations (6) and (7).
Step 8: Repeat steps 5 to 7 until the given number of iterations are completed.
IV. RESULTS
The optimal capacitor placement using Fuzzy and BA was applied on IEEE-15 and IEEE-34 bus
systems and the results obtained are very encouraging. The method places capacitors at less number of locations
with optimum sizes and offers much saving in investment and maintenance.
The proposed method has been programmed using MATLAB 7.12 and run on an Intel core i5 personal
computer. The various parameters used in the algorithm are n=40, A0=1, r0=0.1, α=0.9 and γ=0.1. The losses (in
kW) before and after compensation are tabulated below:
Table 2. Test results of 15 and 34 bus systems
Before
Compensation
After
Compensation
15 bus 61.7993 29.0686
34 bus 221.72 158.5951
The results show that 53.05% reduction in power losses for 15 bus system and 28.47% reduction in
power losses for 34 bus system are obtained when compared to uncompensated line.
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V. CONCLUSIONS
This paper has presented a novel method to determine the optimum capacitor locations using fuzzy
approach and capacitor sizing problem for loss minimisation using BA method. The proposed method has been
tested with several bus systems and the results are encouraging. Compared to the conventional methods, the FIS
considers loss reduction and voltage profile simultaneously to decide the most suitable nodes for capacitor
placement. By installing capacitors at all potential locations, the real power loss has been reduced significantly.
BA iteratively searches the optimal capacitor sizes effectively for maximum loss reduction. The parameters A0,
r0, α, γ play an important role in the performance of BA. The convergence depends highly on the parameters
mentioned above.
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