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.
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.
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.
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.
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.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
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.
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.
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.
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.
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.
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.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
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.
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.
Combination of Immune Genetic Particle Swarm Optimization algorithm with BP a...paperpublications3
Abstract:In this paper, merging Immune Genetic Particle Swarm Optimization algorithm (IGPSO) with BP algorithm to optimize BP Neural Network parameter i.e., BPIGPSO amalgamation to solve optimal reactive power dispatch algorithm. The basic perception is that first training BP neural network with IGPSO to find out a comparatively optimal solution, then take the network parameter at this time as the preliminary parameter of BP algorithm to carry out the training, finally searching the optimal solution. The proposed BPIGPSO has been tested on standard IEEE 57 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Keywords:BP neural network, Immune Genetic Particle Swarm Optimization algorithm, Optimal Reactive Power, Transmission loss.
Dwindling of real power loss by using Improved Bees Algorithmpaperpublications3
Abstract: In this paper, a new Improved Bees Algorithm (IBA) is proposed for solving reactive power dispatch problem. The aim of this paper is to utilize an optimization algorithm called the improved Bees Algorithm, inspired from the natural foraging behaviour of honey bees, to solve the reactive power dispatch problem. The IBA algorithm executes both an exploitative neighbourhood search combined with arbitrary explorative search. The proposed Improved Imperialist Competitive Algorithm (IBA) algorithm has been tested on standard IEEE 57 bus test system and simulation results show clearly the high-quality performance of the projected algorithm in reducing the real power loss.
Keywords: Optimal Reactive Power, Transmission loss, honey bee, foraging behaviour, waggle dance, bee’s algorithm, swarm intelligence, swarm-based optimization, adaptive neighbourhood search, site abandonment, random search.
APPROXIMATING NASH EQUILIBRIUM UNIQUENESS OF POWER CONTROL IN PRACTICAL WSNSIJCNCJournal
Transmission power has a major impact on link and communication reliability and network lifetime in Wireless Sensor Networks. We study power control in a multi-hop Wireless Sensor Network where nodes' communication interfere with each other. Our objective is to determine each node's transmission power level that will reduce the communication interference and keep energy consumption to a minimum. We propose a potential game approach to obtain the unique equilibrium of the network transmission power allocation. The unique equilibrium is located in a continuous domain. However, radio transceivers accept only discrete values for transmission power level setting. We study the viability and performance of mapping the continuous solution from the potential game to the discrete domain required by the radio. We demonstrate the success of our approach through TOSSIM simulation when nodes use the Collection Tree Protocol for routing the data. Also, we show results of our method from the Indriya testbed. We compare it with the case where the motes use Collection Tree Protocol with the maximum transmission power.
This paper analyses the optimal power system planning with DGs used as real and reactive power compensator. Recently planning of DG placement reactive power compensation are the major problems in distribution system. As the requirement in the power is more the DG placement becomes important. When planned to make the DG placement, cost analysis becomes as a major concern. And if the DGs operate as reactive power compensator it is most helpful in power quality maintenance. So, this paper deals with the optimal power system planning with renewable DGs which can be used as a reactive power compensators. The problem is formulated and solved using popular meta-heuristic techniques called cuckoo search algorithm (CSA) and particle swarm optimization (PSO). the comparative results are presented.
This document presents a hybrid Gravitational Search Algorithm and Sequential Quadratic Programming (GSA-SQP) approach to solve economic emission load dispatch (EELD) problems in power systems. The approach aims to minimize both fuel costs and emission levels simultaneously while satisfying operational constraints. It formulates EELD as a multi-objective optimization problem involving non-linear, non-convex objectives and constraints. Numerical results on three test power systems show the proposed GSA-SQP hybrid approach provides better performing solutions compared to other evolutionary algorithms like NSGA-II and SPEA2.
Memory Polynomial Based Adaptive Digital PredistorterIJERA Editor
Digital predistortion (DPD) is a baseband signal processing technique that corrects for impairments in RF
power amplifiers (PAs). These impairments cause out-of-band emissions or spectral regrowth and in-band
distortion, which correlate with an increased bit error rate (BER). Wideband signals with a high peak-to-average
ratio, are more susceptible to these unwanted effects. So to reduce these impairments, this paper proposes the
modeling of the digital predistortion for the power amplifier using GSA algorithm.
α Nearness ant colony system with adaptive strategies for the traveling sales...ijfcstjournal
On account of ant colony algorithm easy to fall into local optimum, this paper presents an improved ant
colony optimization called α-AACS and reports its performance. At first, we provide an concise description
of the original ant colony system(ACS) and introduce α-nearness based on the minimum 1-tree for ACS’s
disadvantage, which better reflects the chances of a given link being a member of an optimal tour. Then, we
improve α-nearness by computing a lower bound and propose other adaptations for ACS. Finally, we
conduct a fair competition between our algorithm and others. The results clearly show that α-AACS has a
better global searching ability in finding the best solutions, which indicates that α-AACS is an effective
approach for solving the traveling salesman problem.
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.
This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
Hybrid method for achieving Pareto front on economic emission dispatch IJECEIAES
In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multiobjective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II.
This document presents a method for optimizing the placement and sizing of multiple distributed generation (DG) units in a transmission system to minimize power losses and improve voltage. Fuzzy logic is used to determine the optimal locations for DG units based on power loss index and voltage. Particle swarm optimization is then used to determine the optimal size of DG units at the identified locations. The method is tested on the IEEE 14-bus system, showing that placing DG units at buses 3, 4 and 5 can reduce power losses by up to 94.47% and improve voltages compared to using a single DG unit.
Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization TechniquejournalBEEI
This document presents a study that uses Particle Swarm Optimization (PSO) technique to solve the Dynamic Economic Dispatch (DED) problem for a 9-bus power system with 3 generators over a 24-hour period. The objective is to determine the optimal generator outputs at each hour to minimize total generation costs while satisfying system constraints. PSO is applied to find the optimal solution by updating generator output positions based on personal and global best cost values. Results found the minimum cost schedule for each generator over the 24 hours while ensuring system limits were not violated.
Dynamic economic load dispatch a review of solution methodologies48jiten2k13
This document discusses various solution techniques for the economic load dispatch (ELD) problem in power systems. It first defines ELD and explains why it is important for minimizing generation costs while meeting load demands. The document then outlines different ELD formulation and solution methods like invasive weed optimization, particle swarm optimization, genetic algorithms, and simulated annealing. It provides flowcharts to illustrate the processes. The document also discusses the limitations of classical optimization methods for dynamic ELD problems and concludes with references used.
International Journal of Engineering Research and DevelopmentIJERD Editor
• Electrical, Electronics and Computer Engineering,
• Information Engineering and Technology,
• Mechanical, Industrial and Manufacturing Engineering,
• Automation and Mechatronics Engineering,
• Material and Chemical Engineering,
• Civil and Architecture Engineering,
• Biotechnology and Bio Engineering,
• Environmental Engineering,
• Petroleum and Mining Engineering,
• Marine and Agriculture engineering,
• Aerospace Engineering
Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dis...ijeei-iaes
In this paper, a novel approach Modified Monkey optimization (MMO) algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases. The proposed (MMO) algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.
Dwindling of real power loss by using Improved Bees Algorithmpaperpublications3
Abstract: In this paper, a new Improved Bees Algorithm (IBA) is proposed for solving reactive power dispatch problem. The aim of this paper is to utilize an optimization algorithm called the improved Bees Algorithm, inspired from the natural foraging behaviour of honey bees, to solve the reactive power dispatch problem. The IBA algorithm executes both an exploitative neighbourhood search combined with arbitrary explorative search. The proposed Improved Imperialist Competitive Algorithm (IBA) algorithm has been tested on standard IEEE 57 bus test system and simulation results show clearly the high-quality performance of the projected algorithm in reducing the real power loss.
This document describes research on optimizing distribution systems using the Moth Flame Optimization algorithm. The research aims to minimize power losses and improve voltage stability by optimally placing distributed generators and capacitors on the network. It formulates the optimization problem and describes the Moth Flame Optimization technique. The research is expected to contribute by demonstrating the viability of using the Moth Flame Optimization algorithm to solve the distribution system optimization problem.
A chaotic particle swarm optimization (cpso) algorithm for solving optimal re...Alexander Decker
This document presents a chaotic particle swarm optimization (CPSO) algorithm for solving the multi-objective reactive power dispatch problem. The CPSO algorithm aims to avoid premature convergence by fusing ergodic and stochastic chaos. It formulates reactive power dispatch as an optimization problem with two objectives: minimizing real power losses and maximizing static voltage stability margin. The CPSO is tested on the IEEE 30 bus system and is shown to reduce power losses and maximize voltage stability more than other algorithms.
A chaotic particle swarm optimization (cpso) algorithm for solving optimal re...Alexander Decker
This document presents a chaotic particle swarm optimization (CPSO) algorithm for solving the multi-objective reactive power dispatch problem. The CPSO algorithm aims to avoid premature convergence by fusing ergodic and stochastic chaos. It formulates reactive power dispatch as an optimization problem with two objectives: minimizing real power losses and maximizing static voltage stability margin. The CPSO is tested on the IEEE 30 bus system and is shown to reduce power losses and maximize voltage stability more than other algorithms.
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.
Combination of Immune Genetic Particle Swarm Optimization algorithm with BP a...paperpublications3
Abstract:In this paper, merging Immune Genetic Particle Swarm Optimization algorithm (IGPSO) with BP algorithm to optimize BP Neural Network parameter i.e., BPIGPSO amalgamation to solve optimal reactive power dispatch algorithm. The basic perception is that first training BP neural network with IGPSO to find out a comparatively optimal solution, then take the network parameter at this time as the preliminary parameter of BP algorithm to carry out the training, finally searching the optimal solution. The proposed BPIGPSO has been tested on standard IEEE 57 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Keywords:BP neural network, Immune Genetic Particle Swarm Optimization algorithm, Optimal Reactive Power, Transmission loss.
Dwindling of real power loss by using Improved Bees Algorithmpaperpublications3
Abstract: In this paper, a new Improved Bees Algorithm (IBA) is proposed for solving reactive power dispatch problem. The aim of this paper is to utilize an optimization algorithm called the improved Bees Algorithm, inspired from the natural foraging behaviour of honey bees, to solve the reactive power dispatch problem. The IBA algorithm executes both an exploitative neighbourhood search combined with arbitrary explorative search. The proposed Improved Imperialist Competitive Algorithm (IBA) algorithm has been tested on standard IEEE 57 bus test system and simulation results show clearly the high-quality performance of the projected algorithm in reducing the real power loss.
Keywords: Optimal Reactive Power, Transmission loss, honey bee, foraging behaviour, waggle dance, bee’s algorithm, swarm intelligence, swarm-based optimization, adaptive neighbourhood search, site abandonment, random search.
APPROXIMATING NASH EQUILIBRIUM UNIQUENESS OF POWER CONTROL IN PRACTICAL WSNSIJCNCJournal
Transmission power has a major impact on link and communication reliability and network lifetime in Wireless Sensor Networks. We study power control in a multi-hop Wireless Sensor Network where nodes' communication interfere with each other. Our objective is to determine each node's transmission power level that will reduce the communication interference and keep energy consumption to a minimum. We propose a potential game approach to obtain the unique equilibrium of the network transmission power allocation. The unique equilibrium is located in a continuous domain. However, radio transceivers accept only discrete values for transmission power level setting. We study the viability and performance of mapping the continuous solution from the potential game to the discrete domain required by the radio. We demonstrate the success of our approach through TOSSIM simulation when nodes use the Collection Tree Protocol for routing the data. Also, we show results of our method from the Indriya testbed. We compare it with the case where the motes use Collection Tree Protocol with the maximum transmission power.
This paper analyses the optimal power system planning with DGs used as real and reactive power compensator. Recently planning of DG placement reactive power compensation are the major problems in distribution system. As the requirement in the power is more the DG placement becomes important. When planned to make the DG placement, cost analysis becomes as a major concern. And if the DGs operate as reactive power compensator it is most helpful in power quality maintenance. So, this paper deals with the optimal power system planning with renewable DGs which can be used as a reactive power compensators. The problem is formulated and solved using popular meta-heuristic techniques called cuckoo search algorithm (CSA) and particle swarm optimization (PSO). the comparative results are presented.
This document presents a hybrid Gravitational Search Algorithm and Sequential Quadratic Programming (GSA-SQP) approach to solve economic emission load dispatch (EELD) problems in power systems. The approach aims to minimize both fuel costs and emission levels simultaneously while satisfying operational constraints. It formulates EELD as a multi-objective optimization problem involving non-linear, non-convex objectives and constraints. Numerical results on three test power systems show the proposed GSA-SQP hybrid approach provides better performing solutions compared to other evolutionary algorithms like NSGA-II and SPEA2.
Memory Polynomial Based Adaptive Digital PredistorterIJERA Editor
Digital predistortion (DPD) is a baseband signal processing technique that corrects for impairments in RF
power amplifiers (PAs). These impairments cause out-of-band emissions or spectral regrowth and in-band
distortion, which correlate with an increased bit error rate (BER). Wideband signals with a high peak-to-average
ratio, are more susceptible to these unwanted effects. So to reduce these impairments, this paper proposes the
modeling of the digital predistortion for the power amplifier using GSA algorithm.
α Nearness ant colony system with adaptive strategies for the traveling sales...ijfcstjournal
On account of ant colony algorithm easy to fall into local optimum, this paper presents an improved ant
colony optimization called α-AACS and reports its performance. At first, we provide an concise description
of the original ant colony system(ACS) and introduce α-nearness based on the minimum 1-tree for ACS’s
disadvantage, which better reflects the chances of a given link being a member of an optimal tour. Then, we
improve α-nearness by computing a lower bound and propose other adaptations for ACS. Finally, we
conduct a fair competition between our algorithm and others. The results clearly show that α-AACS has a
better global searching ability in finding the best solutions, which indicates that α-AACS is an effective
approach for solving the traveling salesman problem.
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.
This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
Hybrid method for achieving Pareto front on economic emission dispatch IJECEIAES
In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multiobjective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II.
This document presents a method for optimizing the placement and sizing of multiple distributed generation (DG) units in a transmission system to minimize power losses and improve voltage. Fuzzy logic is used to determine the optimal locations for DG units based on power loss index and voltage. Particle swarm optimization is then used to determine the optimal size of DG units at the identified locations. The method is tested on the IEEE 14-bus system, showing that placing DG units at buses 3, 4 and 5 can reduce power losses by up to 94.47% and improve voltages compared to using a single DG unit.
Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization TechniquejournalBEEI
This document presents a study that uses Particle Swarm Optimization (PSO) technique to solve the Dynamic Economic Dispatch (DED) problem for a 9-bus power system with 3 generators over a 24-hour period. The objective is to determine the optimal generator outputs at each hour to minimize total generation costs while satisfying system constraints. PSO is applied to find the optimal solution by updating generator output positions based on personal and global best cost values. Results found the minimum cost schedule for each generator over the 24 hours while ensuring system limits were not violated.
Dynamic economic load dispatch a review of solution methodologies48jiten2k13
This document discusses various solution techniques for the economic load dispatch (ELD) problem in power systems. It first defines ELD and explains why it is important for minimizing generation costs while meeting load demands. The document then outlines different ELD formulation and solution methods like invasive weed optimization, particle swarm optimization, genetic algorithms, and simulated annealing. It provides flowcharts to illustrate the processes. The document also discusses the limitations of classical optimization methods for dynamic ELD problems and concludes with references used.
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Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dis...ijeei-iaes
In this paper, a novel approach Modified Monkey optimization (MMO) algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases. The proposed (MMO) algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.
Dwindling of real power loss by using Improved Bees Algorithmpaperpublications3
Abstract: In this paper, a new Improved Bees Algorithm (IBA) is proposed for solving reactive power dispatch problem. The aim of this paper is to utilize an optimization algorithm called the improved Bees Algorithm, inspired from the natural foraging behaviour of honey bees, to solve the reactive power dispatch problem. The IBA algorithm executes both an exploitative neighbourhood search combined with arbitrary explorative search. The proposed Improved Imperialist Competitive Algorithm (IBA) algorithm has been tested on standard IEEE 57 bus test system and simulation results show clearly the high-quality performance of the projected algorithm in reducing the real power loss.
This document describes research on optimizing distribution systems using the Moth Flame Optimization algorithm. The research aims to minimize power losses and improve voltage stability by optimally placing distributed generators and capacitors on the network. It formulates the optimization problem and describes the Moth Flame Optimization technique. The research is expected to contribute by demonstrating the viability of using the Moth Flame Optimization algorithm to solve the distribution system optimization problem.
A chaotic particle swarm optimization (cpso) algorithm for solving optimal re...Alexander Decker
This document presents a chaotic particle swarm optimization (CPSO) algorithm for solving the multi-objective reactive power dispatch problem. The CPSO algorithm aims to avoid premature convergence by fusing ergodic and stochastic chaos. It formulates reactive power dispatch as an optimization problem with two objectives: minimizing real power losses and maximizing static voltage stability margin. The CPSO is tested on the IEEE 30 bus system and is shown to reduce power losses and maximize voltage stability more than other algorithms.
A chaotic particle swarm optimization (cpso) algorithm for solving optimal re...Alexander Decker
This document presents a chaotic particle swarm optimization (CPSO) algorithm for solving the multi-objective reactive power dispatch problem. The CPSO algorithm aims to avoid premature convergence by fusing ergodic and stochastic chaos. It formulates reactive power dispatch as an optimization problem with two objectives: minimizing real power losses and maximizing static voltage stability margin. The CPSO is tested on the IEEE 30 bus system and is shown to reduce power losses and maximize voltage stability more than other algorithms.
The document discusses voltage stability enhancement in radial distribution systems through optimal placement of distributed generators (DGs) and capacitors. It proposes using the Moth Flame Optimization algorithm to determine the optimal location and sizing of DGs and capacitors to minimize power losses and maximize net savings. The methodology considers constraints like voltage limits and power flow limits. Test systems like IEEE 12 and 33 node systems are used to demonstrate the effectiveness of the proposed approach.
Optimal placement of distributed power flow controller for loss reduction usi...eSAT Journals
Abstract
The aim of this paper is to reduce power loss and improve the voltage profiles in an electrical system in optimal manner. The flexible AC transmission system (FACTS) device such as Distributed power flow controller (DPFC) can strongly improve the different parameters in a power system. DPFC can be used to reduce line losses and increase voltage profiles. The optimized allocation of FACTS devices is an important issue, so the Voltage stability index (L-index) has been used in order to place UPFC in power system. The advantage of the L-index is to accelerate the optimization process. After placing the DPFC, Firefly optimization method is used for finding the rating of DPFC. The results obtained using Firefly optimization method is compared with Genetic Algorithm. To show the validity of the proposed techniques and for comparison purposes, simulation carried out on an IEEE- 14 Bus and IEEE- 30 Bus test system for different loading conditions.
Keywords: Distributed power flow controllers (DPFC), Optimized Placement, Voltage stability index (L-index), Firefly optimization method, Genetic algorithm.
Combination of Immune Genetic Particle Swarm Optimization algorithm with BP a...paperpublications3
Abstract:In this paper, merging Immune Genetic Particle Swarm Optimization algorithm (IGPSO) with BP algorithm to optimize BP Neural Network parameter i.e., BPIGPSO amalgamation to solve optimal reactive power dispatch algorithm. The basic perception is that first training BP neural network with IGPSO to find out a comparatively optimal solution, then take the network parameter at this time as the preliminary parameter of BP algorithm to carry out the training, finally searching the optimal solution. The proposed BPIGPSO has been tested on standard IEEE 57 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Passerine swarm optimization algorithm for solving optimal reactive power dis...IJAAS Team
This paper presents Passerine Swarm Optimization Algorithm (PSOA) for solving optimal reactive power dispatch problem. This algorithm is based on behaviour of social communications of Passerine bird. Basically, Passerine bird has three common behaviours: search behaviour, adherence behaviour and expedition behaviour. Through the shared communications Passerine bird will search for the food and also run away from hunters. By using the Passerine bird communications and behaviour, five basic rules have been created in the PSOA approach to solve the optimal reactive power dispatch problem. Key aspect is to reduce the real power loss and also to keep the variables within the limits. Proposed Passerine Swarm Optimization Algorithm (PSOA) has been tested in standard IEEE 30 bus test system and simulations results reveal about the better performance of the proposed algorithm in reducing the real power loss and enhancing the static voltage stability margin.
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.
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
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.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problemijeei-iaes
This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA) for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
This document summarizes a research paper that proposes using the firefly algorithm to solve the economic load dispatch problem in power systems. The economic load dispatch problem involves scheduling power generation to meet demand at minimum cost while satisfying constraints. The firefly algorithm is a nature-inspired metaheuristic optimization algorithm based on fireflies' flashing behavior. Test results on 3-unit and 6-unit systems show the firefly algorithm finds efficient optimal solutions for economic load dispatch and performs better than traditional optimization methods.
This document presents a two-stage approach for optimal capacitor placement in distribution systems to minimize losses using fuzzy logic and bat algorithm. In the first stage, fuzzy logic is used to determine optimal capacitor locations based on power loss index and voltage levels. In the second stage, the bat algorithm is used to determine the optimal capacitor sizes at the identified locations to minimize losses. The methodology is tested on 15-bus and 34-bus test systems and results are presented. Capacitor placement helps improve power factor, voltage profile, reduces power losses and increases feeder capacity of distribution systems.
Optimal power flow solution with current injection model of generalized inte...IJECEIAES
1. The document presents a novel ant lion optimization algorithm with Lévy flight operator called ameliorated ant lion optimization (AALO) to solve optimal power flow problems incorporating a current injection model of generalized interline power flow controller (GIPFC).
2. GIPFC can control multiple transmission lines simultaneously and control sending end voltage to improve bus voltages and minimize objectives like fuel cost, emissions, and losses while satisfying constraints.
3. AALO enhances the exploration of the standard ant lion optimization algorithm. It is tested on benchmark functions and the IEEE 30-bus system with GIPFC to optimize power flow.
Voltage Profile Enhancement and Reduction of Real Power loss by Hybrid Biogeo...ijeei-iaes
This paper presents Hybrid Biogeography algorithm for solving the multi-objective reactive power dispatch problem in a power system. Real Power Loss minimization and maximization of voltage stability margin are taken as the objectives. Artificial bee colony optimization (ABC) is quick and forceful algorithm for global optimization. Biogeography-Based Optimization (BBO) is a new-fangled biogeography inspired algorithm. It mainly utilizes the biogeography-based relocation operator to share the information among solutions. In this work, a hybrid algorithm with BBO and ABC is projected, and named as HBBABC (Hybrid Biogeography based Artificial Bee Colony Optimization), for the universal numerical optimization problem. HBBABC merge the searching behavior of ABC with that of BBO. Both the algorithms have different solution probing tendency like ABC have good exploration probing tendency while BBO have good exploitation probing tendency. HBBABC used to solve the reactive power dispatch problem and the proposed technique has been tested in standard IEEE30 bus test system.
Research on Chaotic Firefly Algorithm and the Application in Optimal Reactive...TELKOMNIKA JOURNAL
The document proposes a chaotic firefly algorithm (CFA) to overcome the shortcomings of the original firefly algorithm getting stuck in local optima. CFA introduces chaos initialization, chaos population regeneration, and linear decreasing inertia weight to increase global search ability. CFA is tested on six benchmark functions and applied to optimize reactive power dispatch in an IEEE 30-bus system. Results show CFA performs better than the original firefly algorithm and particle swarm optimization in finding optimal solutions faster.
Hybrid Particle Swarm Optimization for Solving Multi-Area Economic Dispatch P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) and RCGA.
Comparative study of methods for optimal reactive power dispatchelelijjournal
Reactive power dispatch plays a main role in order to provide good facility secure and economic operation
in the power system. In a power system optimal reactive power dispatch is supported to improve the voltage
profile, to reduce losses, to improve voltage stability, to reduce cost etc. This paper presents a brief literature survey of reactive power dispatch and also discusses a comparative study of conventional and evolutionary computation techniques applied for reactive power dispatch. The paper is useful for researchers for further research and study so that it can apply in the various areas of power system
An Heterogeneous Population-Based Genetic Algorithm for Data Clusteringijeei-iaes
As a primary data mining method for knowledge discovery, clustering is a technique of classifying a dataset into groups of similar objects. The most popular method for data clustering K-means suffers from the drawbacks of requiring the number of clusters and their initial centers, which should be provided by the user. In the literature, several methods have proposed in a form of k-means variants, genetic algorithms, or combinations between them for calculating the number of clusters and finding proper clusters centers. However, none of these solutions has provided satisfactory results and determining the number of clusters and the initial centers are still the main challenge in clustering processes. In this paper we present an approach to automatically generate such parameters to achieve optimal clusters using a modified genetic algorithm operating on varied individual structures and using a new crossover operator. Experimental results show that our modified genetic algorithm is a better efficient alternative to the existing approaches.
Development of a Wireless Sensors Network for Greenhouse Monitoring and Controlijeei-iaes
Wireless sensor networks (WSN) could be used to monitor and control many parameters of environment such as temperature, humidity, and radiation leakage. In greenhouse the weather and soil should be independent of the natural agents. To achieve this condition a wireless sensor nodes could be deployed and communicate with a central base station to measure and transmit the sensed required environment factors. In this paper a WSN was implemented by deployed wireless sensor nodes in a greenhouse with temperature, humidity, moisture light, and CO2 sensors. The proposed model was built and tested, and the result shows an excellent improvement in the sensed parameters. To control the environmental factors, the used microcontroller programmed to control the parameters according to preset values, or manually through a user interface panel.
Analysis of Genetic Algorithm for Effective power Delivery and with Best Upsurgeijeei-iaes
Wireless network is ready for hundreds or thousands of nodes, where each node is connected to one or sometimes more sensors. WSN sensor integrated circuits, embedded systems, networks, modems, wireless communication and dissemination of information. The sensor may be an obligation to technology and science. Recent developments underway to miniaturization and low power consumption. They act as a gateway, and prospective clients, I usually have the data on the server WSN. Other components separate routing network routers, called calculating and distributing routing tables. Discussed the routing of wireless energy balance. Optimization solutions, we have created a genetic algorithm. Before selecting an algorithm proposed for the construction of the center console. In this study, the algorithms proposed model simulated results based on "parameters depending dead nodes, the number of bits transmitted to a base station, where the number of units sent to the heads of fuel consumption compared to replay and show that the proposed algorithm has a network of a relative.
Design for Postplacement Mousing based on GSM in Long-Distanceijeei-iaes
This document describes the design of a remote post-type mouse trap that uses infrared sensors, a power grid, and GSM communication. The trap consists of alternating conducting bars connected to a power source. An infrared sensor module with a Fresnel lens detects mice and activates the power grid only in the detection area. A GSM module sends a message when a mouse is caught. The design was tested over a week and successfully caught two mice. It aims to provide a low-power, reliable way to catch mice remotely without using bait.
Investigation of TTMC-SVPWM Strategies for Diode Clamped and Cascaded H-bridg...ijeei-iaes
This paper presents a concept of two types multilevel inverters such as diode clamped and cascaded H-bridge for harmonic reduction on high power applications. Normally, multilevel inverters can be used to reduce the harmonic problems in electrical distribution systems. This paer focused on the performance and analysis of a three phase seven level inverter including diode clamped and cascaded H-bridge based on new tripizodal triangular space vector PWM technique approaches. TTMC based modified Space vector Pulse width modulation technique so called tripizodal triangular Space vector Pulse width modulation (TTMC-SVPWM) technique. In this paper the reference sine wave generated as in case of conventional off set injected SVPWM technique. It is observed that the TTMC-Space vector pulse width modulation ensures excellent, close to optimized pulse distribution results and THD is compared to seven level, diode clamped and cascaded multi level inverters. Theoretical investigations were confirmed by the digital simulations using MATLAB/SIMULINK software.
Mitigation of Power Quality Problems Using Custom Power Devices: A Reviewijeei-iaes
Electrical power quality (EPQ) in distribution systems is a critical issue for commercial, industrial and residential applications. The new concept of advanced power electronic based Custom Power Devices (CPDs) mainly distributed static synchronous compensator (D-STATCOM), dynamic voltage restorer (DVR) and unified power quality conditioner (UPQC) have been developed due to lacking the performance of traditional compensating devices to minimize power quality disturbances. This paper presents a comprehensive review on D-STATCOM, DVR and UPQC to solve the electrical power quality problems of the distribution networks. This is intended to present a broad overview of the various possible DSTATCOM, DVR and UPQC configurations for single-phase (two wire) and three-phase (three-wire and four-wire) networks and control strategies for the compensation of various power quality disturbances. Apart from this, comprehensive explanation, comparison, and discussion on D-STATCOM, DVR, and UPQC are presented. This paper is aimed to explore a broad prospective on the status of D-STATCOMs, DVRs, and UPQCs to researchers, engineers and the community dealing with the power quality enhancement. A classified list of some latest research publications on the topic is also appended for a quick reference.
Comparison of Dynamic Stability Response of A SMIB with PI and Fuzzy Controll...ijeei-iaes
Consumer utilities are non –linear in nature. This injects increased flow of current and reduced voltage with distortions which cause adverse effect on the stability of consumer utilities. To overcome this problem we are using a modern Flexible Alternating Current Transmission System controller i.e. distributed power flow controller (DPFC). This controller is similar to UPFC, which can be installed in a transmission line between the two electrical areas. In DPFC, instead of the common Dc link capacitor three single phase converters are used. In this paper we are concentrating on system stability (oscillation damping). For analyzing the stability of a single machine infinite bus system (SMIB) we have used PI controlled Distributed Power Flow Controller (DPFC) and Fuzzy controlled DPFC. All these models are simulated using MATLAB/SIMULINK. Simulation results shows Fuzzy controlled DPFC are better than PI controlled DPFC. The significance of the results are better stability and constant power supply.
Embellished Particle Swarm Optimization Algorithm for Solving Reactive Power ...ijeei-iaes
This document summarizes a research paper that proposes an Embellished Particle Swarm Optimization (EPSO) algorithm to solve the reactive power problem in power systems. EPSO extends the standard PSO algorithm by dividing particles into multiple interacting swarms to maintain diversity. It is tested on standard IEEE 57-bus and 118-bus test systems and shown to reduce real power losses more effectively than other algorithms. The EPSO approach cooperatively updates particles between swarms to converge faster to near-optimal solutions while avoiding premature convergence.
Intelligent Management on the Home Consumers with Zero Energy Consumptionijeei-iaes
The energy and environment crisis has forced modern humans to think about new and clean energy sources and in particular, renewable energy sources. With the development of home network, the residents have the opportunity to plan the home electricity usage with the goal of reducing the cost of electricity. In this regard, to improve the energy consumption efficiency in residential buildings, smart buildings with zero energy consumption were considered as a proper option. Zero-energy building is a building that has smart equipment whose integral of generated and consumed power within a year is zero. In this article, smart devices submit their power consumption with regard to the requested activity associated with the user’s time setting for run times and end times of the work to the energy management unit and ultimately the time to start work will be determined. The problem’s target function is reducing the energy cost for the consumer with taking into account the applicable limitations.
Analysing Transportation Data with Open Source Big Data Analytic Toolsijeei-iaes
This document discusses analyzing transportation data using open source big data analytic tools. It provides an overview of H2O and SparkR, two popular tools. It then demonstrates applying these tools to a transportation dataset, using a generalized linear model. Specifically, it shows importing and splitting the data, building a GLM model with H2O and SparkR, making predictions on test data, and comparing predicted versus actual values. The document provides examples of the coding and outputs at each step of the analysis process.
A Pattern Classification Based approach for Blur Classificationijeei-iaes
Blur type identification is one of the most crucial step of image restoration. In case of blind restoration of such images, it is generally assumed that the blur type is known prior to restoration of such images. However, it is not practical in real applications. So, blur type identification is extremely desirable before application of blind restoration technique to restore a blurred image. An approach to categorize blur in three classes namely motion, defocus, and combined blur is presented in this paper. Curvelet transform based energy features are utilized as features of blur patterns and a neural network is designed for classification. The simulation results show preciseness of proposed approach.
Computing Some Degree-Based Topological Indices of Grapheneijeei-iaes
This document computes three topological indices - the Arithmetic-Geometric (AG2) index, SK3 index, and Sanskruti index - for the molecular graph of graphene. It begins by introducing topological indices and defining the three indices. It then presents the main results, explicitly calculating the formula for each index in graphene. For the AG2 index, it considers three cases based on the number of benzene rings in the graphene structure. The key findings are concise formulae for each of the three topological indices of graphene.
A Lyapunov Based Approach to Enchance Wind Turbine Stabilityijeei-iaes
This paper introduces a nonlinear control of a wind turbine based on a Double Feed Induction Generator. The Rotor Side converter is controlled by using field oriented control and Backstepping strategy to enhance the dynamic stability response. The Grid Side converter is controlled by a sliding mode. These methods aim to increase dynamic system stability for variable wind speed. Hence, The Doubly Fed Induction Generator (DFIG) is studied in order to illustrate its behavior in case of severe disturbance, and its dynamic response in grid connected mode for variable speed wind operation. The model is presented and simulated under Matlab/ Simulink.
Fuzzy Control of a Large Crane Structureijeei-iaes
The usage of tower cranes, one type of rotary cranes, is common in many industrial structures, e.g., shipyards, factories, etc. With the size of these cranes becoming larger and the motion expected to be faster and has no prescribed path, their manual operation becomes difficult and hence, automatic closed-loop control schemes are very important in the operation of rotary crane. In this paper, the plant of concern is a tower crane consists of a rotatable jib that carries a trolley which is capable of traveling over the length of the jib. There is a pendulum-like end line attached to the trolley through a cable of variable length. A fuzzy logic controller with various types of membership functions is implemented for controlling the position of the trolley and damping the load oscillations. It consists of two main types of controllers radial and rotational each of two fuzzy inference engines (FIEs). The radial controller is used to control the trolley position and the rotational is used for damping the load oscillations. Computer simulations are used to verify the performance of the controller. The results from the simulations show the effectiveness of the method in the control of tower crane keeping load swings small at the end of motion.
Site Diversity Technique Application on Rain Attenuation for Lagosijeei-iaes
This paper studied the impact of site diversity (SD) as a fade mitigation technique on rain attenuation at 12 GHz for Lagos. SD is one of the most effective methods to overcome such large fades due to rain attenuation that takes advantage of the usually localized nature of intense rainfall by receiving the satellite downlink signal at two or more earth stations to minimize the prospect of potential diversity stations being simultaneously subjected to significant rain attenuation. One year (January to December 2011) hourly rain gauge data was sourced from the Nigerian Meteorological Agency (NIMET) for three sites (Ikeja, Ikorodu and Marina) in Lagos, Nigeria. Significant improvement in both performance and availability was observed with the application of SD technique; again, separation distance was seen to be responsible for this observed performance improvements.
Impact of Next Generation Cognitive Radio Network on the Wireless Green Eco s...ijeei-iaes
Land mobile communication is burdened with typical propagation constraints due to the channel characteristics in radio systems.Also,the propagation characteristics vary form place to place and also as the mobile unit moves,from time to time.Hence,the tramsmission path between transmitter and receiver varies from simple direct LOS to the one which is severely obstructed by buildings, foliage and terrain. Multipath propagation and shadow fading effects affect the signal strength of an arbitrary Transmitter-Receiver due to the rapid fluctuations in the phase and amplitude of signal which also determines the average power over an area of tens or hundreds of meters. Shadowing introduces additional fluctuations, so the received local mean power varies around the area –mean. The present paper deals with the performance analysis of impact of next generation wireless cognitive radio network on wireless green eco system through signal and interference level based k coverage probability under the shadow fading effects.
Music Recommendation System with User-based and Item-based Collaborative Filt...ijeei-iaes
Internet and E-commerce are the generators of abundant of data, causing information Overloading. The problem of information overloading is addressed by Recommendation Systems (RS). RS can provide suggestions about a new product, movie or music etc. This paper is about Music Recommendation System, which will recommend songs to users based on their past history i.e. taste. In this paper we proposed a collaborative filtering technique based on users and items. First user-item rating matrix is used to form user clusters and item clusters. Next these clusters are used to find the most similar user cluster or most similar item cluster to a target user. Finally songs are recommended from the most similar user and item clusters. The proposed algorithm is implemented on the benchmark dataset Last.fm. Results show that the performance of proposed method is better than the most popular baseline method.
A Real-Time Implementation of Moving Object Action Recognition System Based o...ijeei-iaes
This paper proposes a PixelStreams-based FPGA implementation of a real-time system that can detect and recognize human activity using Handel-C. In the first part of our work, we propose a GUI programmed using Visual C++ to facilitate the implementation for novice users. Using this GUI, the user can program/erase the FPGA or change the parameters of different algorithms and filters. The second part of this work details the hardware implementation of a real-time video surveillance system on an FPGA, including all the stages, i.e., capture, processing, and display, using DK IDE. The targeted circuit is an XC2V1000 FPGA embedded on Agility’s RC200E board. The PixelStreams-based implementation was successfully realized and validated for real-time motion detection and recognition.
Wireless Sensor Network for Radiation Detectionijeei-iaes
n this paper a wireless sensor network (WSN) is designed from a group of radiation detector stations with different types of sensors. These stations are located in different areas and each sensor transmits its data through GSM network to the main monitoring and control station. The design includes GPS module to determine the location of mobile and fixed station. The data is transmitted with GSM/GPRS modem. Instead of using traditional SMS data string or word messages a digital data frame is constructed and transmitted as SMS data. In the main monitoring station graphical user interface (GUI) software is designed to shows information and statues of the all stations in the network. It reports any radiation leaks, in addition to the data; the GUI contains a geographical map to display the location of the leakage station and can control the stations power consumption by sending a special command to it.
Charge Sharing Suppression in Single Photon Processing Pixel Arrayijeei-iaes
This paper proposes a mechanism for suppression of charge sharing in single photon processing pixel array by introducing additional circuit. The idea of the proposed mechanism is that in each pixel only analog part will introduced, the digital part is shared between each four pixels, this leads to reduce the number of transistors (area). By having communication pixels, a decision that which one of the neighboring pixels shall collect the distributed charges is taken. The functionality, which involves analog and digital behaviors, is modeled in VHDL.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
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Enriched Firefly Algorithm for Solving Reactive Power Problem
1. Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol. 3, No. 4, December 2015, pp. 209~215
DOI: 10.11591/ijeei.v3i4.175 209
Received July 23, 2015; Revised October 5, 2015; Accepted October 27, 2015
Enriched Firefly Algorithm for Solving Reactive
Power Problem
K. Lenin1
, B. Ravindhranath Reddy2
, M. Surya Kalavathi3
1
Research Scholar, JNTU, Hyderabad 500 085 India
2
Deputy Executive Engineer, JNTU, Hyderabad 500 085 India
3
Department of Electrical and Electronics Engineering, JNTU, Hyderabad 500 085, India
email: gklenin@gmail.com
Abstract
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.
Keyword: firefly algorithm, optimal reactive power, transmission loss
1. Introduction
Various algorithms utilized to solve the reactive power problem. Various numerical
methods like the gradient method [1]-[2], Newton method [3] and linear programming [4]-[7]
have been utilized to solve the optimal reactive power dispatch problem. The problem of voltage
stability and collapse play a key role in power system planning and operation [8].Evolutionary
algorithms such as genetic algorithm have been already utilized to solve the reactive power flow
problem [9]-[11]. In [12], Hybrid differential evolution algorithm is utilized to improve the voltage
stability index. In [13] Biogeography Based algorithm have been used to solve the reactive
power dispatch problem. In [14], a fuzzy based methodology is used to solve the optimal
reactive power scheduling method. In [15], an improved evolutionary programming is used to
solve the optimal reactive power dispatch problem. In [16], the optimal reactive power flow
problem is solved by integrating a genetic algorithm with a nonlinear interior point method. In
[17], a pattern algorithm is used to solve ac-dc optimal reactive power flow model with the
generator capability limits. In [18], F. Capitanescu proposes a two-step approach to evaluate
Reactive power reserves with respect to operating constraints and voltage stability. In [19], a
programming based approach is used to solve the optimal reactive power dispatch problem. In
[20], A. Kargarian et al present a probabilistic algorithm for optimal reactive power provision in
hybrid electricity markets with uncertain loads.This paper proposes Enriched Firefly Algorithm
(EFA) to solve reactive power dispatch problem. Our proposed EFA approach is good in
exploration and exploitation for searching the global near optimal solution, when compared to
other literature surveyed algorithms. A firefly algorithm (FA) is a population-based algorithm
enthused by the social behaviour of fireflies [21],[22]. Fireflies converse by flashing their light.
Dimmer fireflies are attracted to brighter ones and move towards them to mate [23]. FA is
extensively used to solve reliability and redundancy problems. A class of firefly called Lampyride
also used pheromone to attract their mate [24]. The proposed Enriched Firefly Algorithm (EFA)
extends the single population FA to the interacting multi-swarms by cooperative Models [25].
The proposed EFA algorithm has been evaluated on standard IEEE 30 bus test system. The
simulation results show that our proposed approach outperforms all the entitled reported
algorithms in minimization of real power loss.
2. Objective function
The Optimal Power Flow problem is considered as a common minimization problem
with constraints, and can be written in the following form:
2. ISSN: 2089-3272
IJEEI Vol. 3, No. 4, December 2015 : 209 – 215
210
Minimize f(x, u) (1)
Subject to g(x,u)=0 (2)
And
h x, u 0 (3)
Where f(x,u) is the objective function. g(x.u) and h(x,u) are respectively the set of equality and
inequality constraints. x is the vector of state variables, and u is the vector of control variables.
The state variables are the load buses (PQ buses) voltages, angles, the generator
reactive powers and the slack active generator power:
x P , θ , . . , θ , V , . , V , Q , . . , Q (4)
The control variables are the generator bus voltages, the shunt capacitors and the transformers
tap-settings:
u V , T, Q (5)
or
u V , … , V , T , . . , T , Q , . . , Q (6)
Where Ng, Nt and Nc are the number of generators, number of tap transformers and the number
of shunt compensators respectively.
2.1. Active power loss
The objective of the reactive power dispatch is to minimize the active power loss in the
transmission network, which can be mathematically described as follows:
∑ ∈ 2 (7)
Or
∑ ∑∈ (8)
Where gk: is the conductance of branch between nodes i and j, Nbr: is the total number of
transmission lines in power systems. Pd: is the total active power demand, Pgi: is the generator
active power of unit i, and Pgsalck: is the generator active power of slack bus.
2.2. Voltage profile improvement
For minimizing the voltage deviation in PQ buses, the objective function becomes:
(9)
Where ωv: is a weighting factor of voltage deviation.
VD is the voltage deviation given by:
∑ | 1| (10)
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Enriched Firefly Algorithm for Solving Reactive Power Problem (K. Lenin)
211
2.3. Equality Constraint
The equality constraint g(x,u) of the ORPD problem is represented by the power
balance equation, where the total power generation must cover the total power demand and the
power losses:
(11)
2.4. Inequality Constraints
The inequality constraints h(x,u) imitate the limits on components in the power system
as well as the limits created to ensure system security. Upper and lower bounds on the active
power of slack bus, and reactive power of generators:
(12)
, ∈ (13)
Upper and lower bounds on the bus voltage magnitudes:
, ∈ (14)
Upper and lower bounds on the transformers tap ratios:
, ∈ (15)
Upper and lower bounds on the compensators reactive powers:
, ∈ (16)
Where N is the total number of buses, NT is the total number of Transformers; Nc is the total
number of shunt reactive compensators.
3. Proposed Enriched Firefly Algorithm
There are three ideal rules amalgamated into the unique Firefly algorithm (FA), i) all
fireflies are unisex so that a firefly is attracted to all other fireflies ii) a firefly’s attractiveness is
proportionate to its brightness seen by other fireflies. For any two fireflies, the dimmer firefly is
attracted by the brighter one and moves towards it, but if there are no brighter fireflies nearby
means then firefly moves arbitrarily iii) the brightness of a firefly is proportional to the value of
its objective function. According to the above three rules, the degree of attractiveness of a firefly
is planned by the following equation:
(17)
where β is the degree of attractiveness of a firefly at a distance r, β0 is the degree of
attractiveness of the firefly at r= 0, r is the distance between any two fireflies, and γ is a light
absorption coefficient.
The distance r between firefly i and firefly j located at xi and xj respectively is calculated
as a Euclidean distance:
∑ (18)
The movement of the dimmer firefly i towards the brighter firefly j in terms of the dimmer
one’s updated location is determined by the following equation:
4. ISSN: 2089-3272
IJEEI Vol. 3, No. 4, December 2015 : 209 – 215
212
(19)
The third term in (19) is included for the case where there is no brighter firefly than the
one being considered and rand is a random number in the range of [0, 1].
3.1. Basic Firefly Algorithm
[Step 1] fireflies are arbitrarily placed within the exploration range, supreme
attractiveness is , the light absorption is γ, randomization parameter is , maximum number of
iterations is T; the position of fireflies is arbitrary distributed.
[Step 2] Compute the fluorescence brightness of fireflies. Compute the objective
function values of Firefly Algorithm that use the enriched Firefly Algorithm as the largest
individual fluorescence brightness value .
[Step 3] Modernize the position of firefly. When the firefly is no only attracted by a
brighter firefly but also prejudiced by the historical best position of group, the position formula
is updating as function (20).The brightest fireflies will modernize their position as the following
function:
1 1 2⁄ (20)
Where 1 is the global optimal position at generation t.
[Step 4] Recalculate the fluorescence brightness value by using the distance measure
function after updating the location and penetrating the local area for the toughest
fluorescence brightness individual, modernizing the optimal solution when the target value is
enriched, or else unchanged.
[Step 5] When reach the maximum iteration number T , record the optimal solution,
otherwise repeat step (3), (4), (5) and start the next search. The optimal solution is also the
global optimum value and the global optimum image threshold is the corresponding
threshold value , at the position .
3.2. Enriched Firefly Algorithm
In order to overcome the early convergence of classical FA, Cooperative optimization
model is amalgamated into FA to construct an Enriched FA in this paper. In order to progress
the balance between the exploration and exploitation in EFA we suggest a modification of Eq.
(21) used in traditional FA. The goal of the modification is to reinstate balance between
exploration and exploitation affording increased possibility of escaping basin of attraction of
local optima. In the suggested EFA ,the firefly find a brighter firefly when iterative search use
Firefly Algorithm ,then move towards with a certain step, but the direction of movement will
bounce under the influence of the historical best position of group. The direction that towards
blend with the direction that towards the historical best position of group is the deflect
direction, in this way each search is affected by better solutions thereby improving the
convergence rate. The principle of Firefly Algorithm with the influence of the historical best
position of group .Suppose any firefly in the probing range is attracted by a brighter firefly and
influenced by the historical best position of group, then the original direction of movement will
change and move towards the optimal direction, thus speeding up the convergence rate.
1 1 2⁄ (21)
In the proposed EFA, Eq. (20) of old-style FA based on constants values of and is
modified by Eq. (21) Using new variables, and . In this case, the fireflies are adjusted by:
Schematic procedure of Firefly Algorithm with the influence of the historical best position of
group. The movement of a firefly is attracted to another more brighter firefly with the influence of
the historical best position of group is determined by where is the updating position of
firefly, is the initial position of firefly which play an important role in balancing the global
5. IJEEI ISSN: 2089-3272
Enriched Firefly Algorithm for Solving Reactive Power Problem (K. Lenin)
213
searching and the local searching, represents the position of fireflies
update under the attraction between fireflies, represent the
updating position of fireflies under the influence of the historical best position of group,
1 2⁄ is the arbitrary parameter that can avoid the result falling into local optimum.
Input:
Generate preliminary population of fireflies n within
d-dimensional search space , i = 1, 2, . . . , n and
k = 1, 2, . . . , d
Calculate the fitness of the population f ( ) which
is right proportional to light intensity
Algorithm’s parameter— ,
Output:
Acquired least location: min
start
reiteration
for = 1 to n
for = 1 to n
if
Transport firefly toward in
d-dimension using Eq. (20)
end if
Attraction varies with distance r
Calculate new solutions and modernize light
intensity using Eq. (21)
end for
end for
Rank the fireflies and find the existing best
until stop condition true
end
4. Results and Discussion
EFA algorithm has been verified in IEEE 30-bus, 41 branch system. It has 6 generator-
bus voltage magnitudes, 4 transformer-tap settings, and 2 bus shunt reactive compensators.
Bus 1 is slack bus and 2, 5, 8, 11 and 13 are taken as PV generator buses and the rest are PQ
load buses. Control variables limits are listed in Table 1.
Table 1. Preliminary Variable Limits (PU)
Variables Min. Value Max. Value Type
Generator Bus 0.92 1.12 Continuous
Load Bus 0.94 1.04 Continuous
Transformer-Tap 0.94 1.04 Discrete
Shunt Reactive Compensator -0.11 0.30 Discrete
The power limits generators buses are represented in Table 2. Generators buses (PV)
2,5,8,11,13 and slack bus is 1.
Table 2. Generators Power Limits
Bus Pg Pgmin Pgmax Qgmin
1 98.00 51 202 -21
2 81.00 22 81 -21
5 53.00 16 53 -16
8 21.00 11 34 -16
11 21.00 11 29 -11
13 21.00 13 41 -16
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IJEEI Vol. 3, No. 4, December 2015 : 209 – 215
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Table 3. Values of Control Variables After Optimization
Control Variables EFA
V1 1.0621
V2 1.0522
V5 1.0317
V8 1.0422
V11 1.0821
V13 1.0641
T4,12 0.00
T6,9 0.02
T6,10 0.90
T28,27 0.91
Q10 0.11
Q24 0.11
Real power loss 4.3001
Voltage deviation 0.9070
Table 3 shows the proposed approach succeeds in keeping the control variables within
limits. Table 4 summarizes the results of the optimal solution obtained by various methods.
Table 4. Comparison Results
Methods Real power loss (MW)
SGA (26) 4.98
PSO (27) 4.9262
LP (28) 5.988
EP (28) 4.963
CGA (28) 4.980
AGA (28) 4.926
CLPSO (28) 4.7208
HSA (29) 4.7624
BB-BC (30) 4.690
EFA 4.3001
5. Conclusion
In this paper, the EFA has been effectively implemented to solve Optimal Reactive
Power Dispatch problem. The proposed algorithm has been tested on the standard IEEE 30 bus
system. Simulation results show the robustness of proposed EFA method for providing better
optimal solution in decreasing the real power loss. The control variables obtained after the
optimization by EFA is within the limits.
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