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.
Enriched Firefly Algorithm for Solving Reactive Power Problemijeei-iaes
In this paper, Enriched Firefly Algorithm (EFA) is planned to solve optimal reactive power dispatch problem. This algorithm is a kind of swarm intelligence algorithm based on the response of a firefly to the light of other fireflies. In this paper, we plan an augmentation on the original firefly algorithm. The proposed algorithm extends the single population FA to the interacting multi-swarms by cooperative Models. The proposed EFA has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
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.
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.
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.
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.
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.
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.
Enriched Firefly Algorithm for Solving Reactive Power Problemijeei-iaes
In this paper, Enriched Firefly Algorithm (EFA) is planned to solve optimal reactive power dispatch problem. This algorithm is a kind of swarm intelligence algorithm based on the response of a firefly to the light of other fireflies. In this paper, we plan an augmentation on the original firefly algorithm. The proposed algorithm extends the single population FA to the interacting multi-swarms by cooperative Models. The proposed EFA has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
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.
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.
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.
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.
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.
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.
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.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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.
Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization TechniquejournalBEEI
This paper presents the application of particle swarm optimization (PSO) technique for solving the dynamic economic dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines.
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.
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.
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.
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.
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
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...paperpublications3
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Keywords: quantum particle swarm optimization, genetic particle swarm optimization, hybrid algorithm Optimization, Swarm Intelligence, optimal reactive power, Transmission loss.
Multi-Objective Aspects of Distribution Network Volt-VAr OptimizationPower System Operation
Recent research has enabled the integration of traditional Volt-VAr Control (VVC) resources, such as capacitors banks and transformer tap changers, with Distributed Energy Resources (DERs), such as photovoltaic farms and batteries, in order to achieve various Volt-VAr Optimization (VVO) targets, such as Conservation Voltage Reduction (CVR), minimizing VAr flow at the transformer, minimizing grid losses, minimizing asset operations and more. In this case, where more than one target function is involved, the question of multi-objective optimization is raised. In this work, we demonstrate various methods in which such optimization can be performed in practice and we discuss the various operational considerations that are involved with each method. We demonstrate the methods using simulation on a test feeder
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.
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 .
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Journals
Abstract This paper presents Hybrid Particle Swarm Optimization (HPSO) technique to solve the Optimal Load Dispatch (OLD) problems with line flow constrain, bus voltage limits and generator operating constraints. In the proposed HPSO method both features of EP and PSO are incorporated, so the combined HPSO algorithm may become more effective to find the optimal solutions. In this paper, the proposed Hybrid PSO, PSO and EP techniques have been tested on IEEE14, 30 bus systems. Numerical simulation results show that the Hybrid PSO algorithm outperformed standard PSO algorithm and Evolution Programming method on the same problem and can save considerable cost of Optimal Load Dispatch.
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.
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
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.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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.
Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization TechniquejournalBEEI
This paper presents the application of particle swarm optimization (PSO) technique for solving the dynamic economic dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines.
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.
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.
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.
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.
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
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...paperpublications3
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Keywords: quantum particle swarm optimization, genetic particle swarm optimization, hybrid algorithm Optimization, Swarm Intelligence, optimal reactive power, Transmission loss.
Multi-Objective Aspects of Distribution Network Volt-VAr OptimizationPower System Operation
Recent research has enabled the integration of traditional Volt-VAr Control (VVC) resources, such as capacitors banks and transformer tap changers, with Distributed Energy Resources (DERs), such as photovoltaic farms and batteries, in order to achieve various Volt-VAr Optimization (VVO) targets, such as Conservation Voltage Reduction (CVR), minimizing VAr flow at the transformer, minimizing grid losses, minimizing asset operations and more. In this case, where more than one target function is involved, the question of multi-objective optimization is raised. In this work, we demonstrate various methods in which such optimization can be performed in practice and we discuss the various operational considerations that are involved with each method. We demonstrate the methods using simulation on a test feeder
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.
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 .
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Journals
Abstract This paper presents Hybrid Particle Swarm Optimization (HPSO) technique to solve the Optimal Load Dispatch (OLD) problems with line flow constrain, bus voltage limits and generator operating constraints. In the proposed HPSO method both features of EP and PSO are incorporated, so the combined HPSO algorithm may become more effective to find the optimal solutions. In this paper, the proposed Hybrid PSO, PSO and EP techniques have been tested on IEEE14, 30 bus systems. Numerical simulation results show that the Hybrid PSO algorithm outperformed standard PSO algorithm and Evolution Programming method on the same problem and can save considerable cost of Optimal Load Dispatch.
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.
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
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
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.
PRACTICAL IMPLEMENTION OF GAOPF ON INDIAN 220KV TRANSMISSION SYSTEMecij
This paper presents the practical implementation of developed genetic algorithm based optimal power flow algorithms. These algorithms are tested on IEEE30 bus system and the results were presented in the paper [8]. The same algorithms now tested on 220KV Washi zone Indian power transmission system . The GAOPF with fixed penalty and Fuzzy based variable penalty tested on 220KV transmission system consists of 52 bus and 88lines. The fuel costs ,computational time and the system condition were studied and the results are presented in this paper .Also the available load transfer capability of the 220KV system for congestion management is also presented
A Study of Load Flow Analysis Using Particle Swarm OptimizationIJERA Editor
Load flow study is done to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state working condition of a power system. It is important and most frequently car-ried out study performed by power utilities for power system planning, optimization, operation and control. In this project a Particle Swarm Optimization (PSO) is proposed to solve load flow problem under different load-ing/ contingency conditions for computing bus voltage magnitudes and angles of the power system. With the increasing size of power system, this is very necessary to finding the solution to maximize the utilization of ex-isting system and to provide adequate voltage support. For this the good voltage profile is must. STATCOM, if placed optimally can be effective in providing good voltage profile and in turn resulting into stable power sys-tem. The study presents a hybrid particle swarm based methodology for solving load flow in electrical power systems. Load flow is an electrical engineering well-known problem which provides the system status in the steady-state and is required by several functions performed in power system control centers.
Power system transient stability margin estimation using artificial neural ne...elelijjournal
This paper presents a methodology for estimating the normalized transient stability margin by using the multilayered perceptron (MLP) neural network. The complex relationship between the input variables and output variables is established by using the neural networks. The nonlinear mapping relation between the normalized transient stability margin and the operating conditions of the power system is established by using the MLP neural network. To obtain the training set of the neural network the potential energy boundary surface (PEBS) method along with time domain simulation method is used. The proposed method is applied on IEEE 9 bus system and the results shows that the proposed method provides fast and accurate tool to assess online transient stability.
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...paperpublications3
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Evaluation of IEEE 57 Bus System for Optimal Power Flow AnalysisIJERA Editor
The analysis of load flow in a network under steady state operation is challenging task especially subjected to
inequality constraints in which the system operates. No doubt, that the load flow system analysis is an important
aspect for power system analysis and design. The basic analysis technique for power flow is to find different
parameters including magnitude and phase angle of voltage at each bus with active and reactive power flows in
each transmission lines. Thus, load flow analysis is important numerical analysis for any power system. In this
regard, this experiment is studied to evaluate IEEE 57 bus system for optimal flow analysis.
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.
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.
Decline of Real Power Loss and Preservation of Voltage Stability by using Chi...ijeei-iaes
In this paper, a new Chirping Algorithm (CA) is developed based on the chirping behaviour of crickets for solving the reactive power optimization problem. It is based on the chirping behaviour of crickets (insect) found almost everywhere around the world. The proposed Chirping Algorithm (CA) has been tested in standard IEEE 30, 57,118 bus test systems and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss and control variables are well within the limits.
Optimal power flow solution with current injection model of generalized inte...IJECEIAES
Optimal power flow (OPF) solutions with generalized interline power flow controller (GIPFC) devices play an imperative role in enhancing the power system’s performance. This paper used a novel ant lion optimization (ALO) algorithm which is amalgamated with Lévy flight operator, and an effectual algorithm is proposed named as, ameliorated ant lion optimization (AALO) algorithm. It is being implemented to solve single objective OPF problem with the latest flexible alternating current transmission system (FACTS) controller named as GIPFC. GIPFC can control a couple of transmission lines concurrently and it also helps to control the sending end voltage. In this paper, current injection modeling of GIPFC is being incorporated in conventional Newton-Raphson (NR) load flow to improve voltage of the buses and focuses on minimizing the considered objectives such as generation fuel cost, emissions, and total power losses by fulfilling equality, in-equality. For optimal allocation of GIPFC, a novel Lehmann-SymanzikZimmermann (LSZ) approach is considered. The proposed algorithm is validated on single benchmark test functions such as Sphere, Rastrigin function then the proposed algorithm with GIPFC has been testified on standard IEEE-30 bus system.
Soft Computing Technique Based Enhancement of Transmission System Lodability ...IJERA Editor
Due to the growth of electricity demands and transactions in power markets, existing power networks need to be enhanced in order to increase their loadability. The problem of determining the best locations for network reinforcement can be formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). The complexity of the problem makes extensive simulations necessary and the computational requirement is high. This paper compares the effectiveness of Evolutionary Programming (EP) and an ordinal optimization (OO) technique is proposed in this paper to solve the MDCP involving two types of flexible ac transmission systems (FACTS) devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), for system loadability enhancement. In this approach, crude models are proposed to cope with the complexity of the problem and speed up the simulations with high alignment confidence. The test and Validation of the proposed algorithm are conducted on IEEE 14–bus system and 22-bus Indian system.Simulation results shows that the proposed models permit the use of OO-based approach for finding good enough solutions with less computational efforts.
Similar to Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimization (20)
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 design for mousing is made up of power control module, infrared sensor module, signal processing module, distance information transportation based on GSM and device of power grid. The design consists of two sets of conductors, separately linked by fire wire and null line and distributing alternatively. The major innovation is infrared sensor module with Fresnel lens, and that the infrared detecting area should be spread in one direction at least. When the mouse get into the infrared detecting area, the sensor signal of infrared detecting device is sent to power control module through signal element and then starts the device of power grid to power up to make the mouse be shocked or die. GSM module is adopted to tell that the mouse is caught successfully. This design can be placed in any position that the mouse is always out and no need of baits.
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 paper proposes Embellished Particle Swarm Optimization (EPSO) algorithm for solving reactive power problem .The main concept of Embellished Particle Swarm Optimization is to extend the single population PSO to the interacting multi-swarm model. Through this multi-swarm cooperative approach, diversity in the whole swarm community can be upheld. Concurrently, the swarm-to-swarm mechanism drastically speeds up the swarm community to converge to the global near optimum. In order to evaluate the performance of the proposed algorithm, it has been tested in standard IEEE 57,118 bus systems and results show that Embellished Particle Swarm Optimization (EPSO) is more efficient in reducing the Real power losses when compared to other standard reported algorithms.
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
Big data analytics allows a vast amount of structured and unstructured data to be effectively processed so that correlations, hidden patterns, and other useful information can be mined from the data. Several open source big data analytic tools that can perform tasks such as dimensionality reduction, feature extraction, transformation, optimization, are now available. One interesting area where such tools can provide effective solutions is transportation. Big data analytics can be used to efficiently manage transport infrastructure assets such as roads, airports, bus stations or ports. In this paper an overview of two open source big data analytic tools is first provided followed by a simple demonstration of application of these tools on transport dataset.
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
Graphene is one of the most promising nanomaterial because of its unique combination of superb properties, which opens a way for its exploitation in a wide spectrum of applications ranging from electronics to optics, sensors, and bio devices. Inspired by recent work on Graphene of computing topological indices, here we compute new topological indices viz. Arithmetic-Geometric index (AG2 index), SK3 index and Sanskruti index of a molecular graph G and obtain the explicit formulae of these indices for 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.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
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Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimization
1. Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol. 2, No. 3, September 2014, pp. 111~118
ISSN: 2089-3272 111
Received May 13, 2014; Revised July 23, 2014; Accepted August 4, 2014
Reduction of Active Power Loss byUsing Adaptive Cat
Swarm Optimization
K Lenin, B Ravindhranath Reddy
Jawaharlal Nehru Technological University Kukatpally,
Hyderabad 500 085, India
email: gklenin@gmail.com
Abstract
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. TheprojectedACSO
has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the high-
quality performance of the plannedalgorithm in tumbling the real power loss.
Keywords: Optimal Reactive Power, Transmission loss, Adaptive cat swarmoptimization
1. Introduction
Optimal reactive power dispatch (ORPD) problem is multi-objective optimization
problems that reduce the real power loss. Various mathematical techniqueslike the gradient
method [1-2], Newton method [3] and linear programming [4-7] have been adopted to solve the
optimal reactive power dispatch problem. Both the gradient and Newton methods has the
difficulty in managing inequality constraints. If linear programming is applied then the input-
output function has to be articulated as a set of linear functions which mostly lead to loss of
accurateness. The problem of voltage stability and collapse play a major role in power system
planning and operation [8]. Global optimization has received widespread research awareness,
and a great number of methods have been applied to solve this problem. Evolutionary
algorithms such as genetic algorithm have been already proposed to solve the reactive power
flow problem [9,10]. Evolutionary algorithm is a heuristic approach used for minimization
problems by utilizing nonlinear and non-differentiable continuous space functions. In [11],
Genetic algorithm has been used to solve optimal reactive power flow problem. In [12], Hybrid
differential evolution algorithm is proposed to improve the voltage stability index. In [13]
Biogeography Based algorithm is projected to solve the reactive power dispatch problem. In
[14], afuzzy based method is used to solve the optimal reactive power scheduling method .In
[15], an improved evolutionary programming is used to solvethe optimal reactive power dispatch
problem. In [16], the optimal reactive power flow problem is solved by integrating a genetic
algorithm with a nonlinearinterior point method. In [17], apattern algorithm is used to solve ac-dc
optimal reactive powerflow model with the generator capability limits. In [18], proposes a two-
step approach to evaluate Reactive power reserves with respect to operating constraints and
voltage stability. In [19], a programming based proposed approach used to solve the optimal
reactive power dispatch problem. In [20], presents aprobabilistic algorithm for optimal reactive
power provisionin hybrid electricity markets with uncertain loads. Cat Swarm Optimization
(CSO) which mimics the behaviour of cats [21]. By imitate the behaviour of cats and modelling
into two modes, CSO can decipher the optimization problems. So in this paper, we plan an
Adaptive CSO in order to attain the elevated convergence accuracy in a lesser amount of
iteration. First we employ an adaptive inertia weight and adaptive acceleration coefficient. So,
the new velocity update equation will be calculated in an adaptive formula. Then, our aim is to
consider the effect of previous or next steps in order to compute the current position. So by
2. ISSN: 2089-3272
IJEEI Vol. 2, No. 3, September 2014 : 111 – 118
112
utilizing a factor namely ‘Forgetting Factor’, information values of steps will be dissimilar. Finally,
we use an average form of position update equation composing new velocity and position
information. The proposed algorithm ACSO been evaluated in standard IEEE 57 bus test
system & the simulation results shows that our proposed approach outperforms all reported
algorithms in minimization of real power loss.
2. Problem Formulation
The OPF problem is measured as a general minimization problem with constraints, and
can be mathematically written in the following form:
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/reactors 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.
3. Objective Function
Active power loss
The objective of the reactive power dispatch is to minimize the active power loss in the
transmission network, which can be described as follows:
F PL ∑ g∈ V V 2V V cosθ (7)
or
F PL ∑ P P P ∑ P P∈ (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.
3. IJEEI ISSN: 2089-3272
Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimization (K Lenin)
113
Voltage profile improvement
For minimizing the voltage deviation in PQ buses, the objective function becomes:
F PL ω VD (9)
Where ωv: is a weighting factor of voltage deviation.
VD is the voltage deviation given by:
VD ∑ |V 1| (10)
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:
P P P (11)
This equation is solved by running Newton Raphson load flow method, by calculating
the active power of slack bus to determine active power loss.
Inequality Constraints
The inequality constraints h(x,u) reflect 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:
P P P (12)
Q Q Q , i ∈ N (13)
Upper and lower bounds on the bus voltage magnitudes:
V V V , i ∈ N (14)
Upper and lower bounds on the transformers tap ratios:
T T T , i ∈ N (15)
Upper and lower bounds on the compensators reactive powers:
Q Q Q , i ∈ N (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.
4. Cat Swarm Optimization
Cat Swarm Optimization is a new-fangled optimization algorithm in the field of swarm
intelligence. The CSO algorithm replica the behaviour of cats into two modes: ‘Search mode’
and ‘Trace mode’. Swarm is made of primary population composed of particles to explore in the
solution space. Here in CSO, we employ cats as particles for solving the problem. In CSO,
each cat has its own location composed of D dimensions, velocities for every dimension, a
fitness value, which represents the accommodation of the cat to the fitness function, and a flag
to identify whether the cat is in search mode or trace mode. The final solution would be the most
excellent position of one of the cats. The CSO keeps the best solution until it reaches the end of
the iterations [22].
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114
Search mode
For modelling the behaviour of cats in resting time and being-alert, we use the search
mode. In this mode is a time for opinion and deciding about next move. This mode has four
main parameters which are mentioned as follow: search memory pools (SMP), search range of
the selected dimension (SRD), calculate of dimension to change (CDC) and self-position
consideration (SPC).
The process of search mode is describes as follow:
Step 1: create j copies of the present location of catk, where j = SMP. If the value of SPC is true,
let j = (SMP-1), then preserve the present location as one of the candidates.
Step 2: For every copy, according to CDC, arbitrarily Add or Subtract SRD percent the present
values and reinstate the old ones.
Step 3: compute the fitness values (FS) of all candidate points.
Step 4: If all FS are not exactly equal, compute the selecting probability of every candidate point
by (1), or else set all the selecting probability of every candidate point is 1.
Step 5: arbitrarily choose the point to move to from the candidate points, and replace the
location of catk.
P
| |
(17)
If the objective of the fitness function is to discover the minimum solution, FSb = FSmax,
otherwise FSb = FSmin
Trace Mode
Trace mode is the second mode of algorithm. In this mode, cats craving to trace targets
and foods. The procedure of trace mode can be described as follow:
Step 1: renew the velocities for each dimension according to (18).
Step 2: verify if the velocities are in the range of maximum velocity. In case the new velocity is
over-range, it is set equal to the limit.
V , V , r c X , X , (18)
Step 3: renew the location of catk according to equation (19)
X , X , V , (19)
Xbest,d is the position of the cat, who has the best fitness value, Xk,d is the position of
catk, c1 is an acceleration coefficient for extending the velocity of the cat to move in the solution
space and usually is equal to 2.03 and r1 is a random value uniformly generated in the range of
[0,1].
Key explanation of CSO
In order to merge the two modes into the algorithm, we define a mixture ratio (MR)
which specifies the rate of mixing of search mode and trace mode. This parameter makes a
decision how many cats will be moved into search mode procedure.First of all, we generate N
cats and initialize the positions, velocities and the flags for cats. (*) According to the fitness
function, calculate the fitness value of the each cat and keep the best cat into memory (Xbest). In
next step, according to cat’s flag, apply cat to the search mode or trace mode procedure. After
finishing the associated progression, re-pick the number of cats and set them into search mode
or trace mode according to MR parameter. At the end, check the termination condition, if
satisfied, stop the program, and otherwise go to (*) [23].
5. Adaptive Cat Swarm Optimization
The trace mode of CSO has two equations: velocity update equation and position
update equation. For attainment an adaptive CSO, we modify some of the parameters in
velocity equation. Also to calculate the current location of cats, we deem the information of
previous and next dimensions by using an extraordinary factor and then we attain a fresh
5. IJEEI ISSN: 2089-3272
Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimization (K Lenin)
115
dynamic position update equation. We explain the proposed algorithm in two parts.
By means of Adaptive Parameters
In the proposed algorithm, we insert an adaptive inertia weight to the velocity equation
which is updated in every dimension. By utilizing this parameter, we create equilibrium between
global and local search ability. A large inertia weight make easy of a global search while a small
inertia weigh make easy of a local search. First we employ a large value and it will be reduced
gradually to the least value by using (20).
W i W (20)
Equation (20) specifies that the inertia weight will be renewed adaptively, where Ws is
the starting weight, imax is the maximum dimension of benchmark and i is the existing dimension.
So the maximum inertia weight happens in the primary dimension of the each iteration and it will
be updated decreasingly in each dimension. In the projected algorithm Ws is equal to 0.5. Also,
c1 is an acceleration coefficient for extending the velocity of the cat to shift in the solution space.
This parameter is a constant value and is usually equal to 2.03, but we use an adaptive formula
to update it by (21).
C i C (21)
Equation (21) reveals that the adaptive acceleration coefficient will be steadily
increased in each dimension and the greatest value happens in the last dimension. Here Cs is
equal to 2.03.
By using these two adaptive parameters, we modify the velocity update equation for
each cat to a new form describing in (22).
V , W d V , r C d X , X , (22)
Fresh Dynamic location Update Equation
In this part, we modify the location update equation to a new form. In the conventional
CSO, the position of cat is including of current information of velocity and position. Occasionally
in many cases, using of previous information in order to guess the current position is useful.
Also, taking the advantages of next information can be suitable information for renewing the
cat’s position. So we use the two previous or next dimensions information of velocity and
position by applying a fresh factor which is called ‘Forgetting factor’. By this factor, the values of
previous and next steps will be different. So the information value for first previous or next step
is senior than second previous or next step. It means that the pressure of previous or next step
is more significant than previous or next second step. New-fangled position update equation is
described by (23). In the projected algorithm, γ is the forgetting factor and is equal to 0.8 (It is
necessary to use γ > 0.5). This fresh position update equation is composing two new vibrant
terms, average location information and average velocity information. Here, we employ the
current and the average information of first and second previous or next dimensions for both
velocity and position by applying a forgetting factor (γ).
X ,
1
2
location inofrmation velocity information
location information X ,
γ X , 1 γ X ,
2
γ X , 1 γ X ,
2
velocity information V ,
, ,
, ,
(23)
6. Simulation Results
The proposed ACSO algorithm for solving ORPD problem is tested for standard IEEE-
57 bus power system. The IEEE 57-bus system data consists of 80 branches, seven generator-
buses and 17 branches under load tap setting transformer branches. The possible reactive
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116
power compensation buses are 18, 25 and 53. Bus 2, 3, 6, 8, 9 and 12 are PV buses and bus 1
is selected as slack-bus. In this case, the search space has 27 dimensions, i.e., the seven
generator voltages, 17 transformer taps, and three capacitor banks. The system variable limits
are given in Table 1. The initial conditions for the IEEE-57 bus power system are given as
follows:
Pload = 12.221 p.u. Qload = 3.251 p.u.
The total initial generations and power losses are obtained as follows:
∑ P = 12.6259 p.u. ∑ Q = 3.3369 p.u.
Ploss = 0.26493 p.u. Qloss = -1.2209 p.u.
Table 2 shows the various system control variables i.e. generator bus voltages, shunt
capacitances and transformer tap settings obtained after ACSO based optimization which are
within their acceptable limits. In Table 3, a comparison of optimum results obtained from
proposed ACSO with other optimization techniques for ORPD mentioned in literature for IEEE-
57 bus power system is given. These results indicate the robustness of proposed ACSO
approach for providing better optimal solution in case of IEEE-57 bus system.
Table 1. Variables limits for ieee-57 bus power system (p.u.)
reactive power generation limits
bus no 1 2 3 6 8 9 12
Qgmin -1.2 -.013 -.03 -0.06 -1.2 -0.02 -0.3
qgmax 2 0.6 0.5 0.23 2 0.03 1.43
voltage and tap setting limits
vgmin vgmax vpqmin vpqmax tkmin tkmax
0.8 1.0 0.93 1.06 0.6 1.2
shunt capacitor limits
bus no 18 25 53
qcmin 0 0 0
qcmax 10 5.3 6.2
Table 2. Control variables obtained after optimization by ACSO method for
ieee-57 bus system (p.u.)
Control
Variables
ACSO
V1 1.1
V2 1.078
V3 1.064
V6 1.057
V8 1.078
V9 1.044
V12 1.058
Qc18 0.0835
Qc25 0.326
Qc53 0.0615
T4-18 1.017
T21-20 1.068
T24-25 0.968
T24-26 0.936
T7-29 1.095
T34-32 0.948
T11-41 1.016
T15-45 1.068
T14-46 0.936
T10-51 1.044
T13-49 1.065
T11-43 0.913
T40-56 0.906
T39-57 0.968
T9-55 0.988
7. IJEEI ISSN: 2089-3272
Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimization (K Lenin)
117
Table 3. comparative optimization results for ieee-57 bus power system (p.u.)
S.No. Optimization
Algorithm
Best
Solution
Worst Solution Average
Solution
1 NLP [24] 0.25902 0.30854 0.27858
2 CGA [24] 0.25244 0.27507 0.26293
3 AGA [24] 0.24564 0.26671 0.25127
4 PSO-w [24] 0.24270 0.26152 0.24725
5 PSO-cf [24] 0.24280 0.26032 0.24698
6 CLPSO [24] 0.24515 0.24780 0.24673
7 SPSO-07 [24] 0.24430 0.25457 0.24752
8 L-DE [24] 0.27812 0.41909 0.33177
9 L-SACP-DE [24] 0.27915 0.36978 0.31032
10 L-SaDE [24] 0.24267 0.24391 0.24311
11 SOA [24] 0.24265 0.24280 0.24270
12 LM [25] 0.2484 0.2922 0.2641
13 MBEP1 [25] 0.2474 0.2848 0.2643
14 MBEP2 [25] 0.2482 0.283 0.2592
15 BES100 [25] 0.2438 0.263 0.2541
16 BES200 [25] 0.3417 0.2486 0.2443
17 Proposed ACSO 0.22321 0.23984 0.23199
7. Conclusion
In this paper, the ACSO has been productively implemented to solve ORPD problem.
The main advantages of the ACSO to the ORPD problem are optimization of different type of
objective function, real coded of both continuous and discrete control variables, and easily
handling nonlinear constraints. The proposed algorithm has been tested on the IEEE 57-bus
system.The active power loss has been minimized andthe voltage profile indexes are within the
limits.
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