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.
Fuzzy expert system based optimal capacitor allocation in distribution system-2IAEME Publication
One of the most popular image denoising methods based on self-similarity is called nonlocal
means (NLM). Though it can achieve remarkable performance, this method has a few shortcomings,
e.g., the computationally expensive calculation of the similarity measure, and the lack of reliable
candidates for some non repetitive patches. In this paper, we propose to improve NLM by integrating
Gaussian blur, clustering, and row image weighted averaging into the NLM framework.
Experimental results show that the proposed technique can perform denoising better than the original
NLM both quantitatively and visually, especially when the noise level is high.
Optimal Reactive Power Scheduling Using Cuckoo Search AlgorithmIJECEIAES
The article describes multidisciplinary design process of high-performance electric generator for advanced aircrafts by analytical methods and computer modeling techniques (electromagnetic, thermal and mechanical calculations). New technical solutions used in its development are described. The main ideas are revealed of the method of EG voltage stabilization we used. To improve the heat dissipation efficiency, we have developed a new cooling system, and provide its study and description in this paper. The advantages of this cooling system include the fact that EG is made with dry, uncooled rotor. This allowed eliminating additional pumps, and significantly reducing tThis paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.he size of CSD. According to the results of our study, we created an experimental full capacity layout, and its studies are also provided in this paper.
Voltage sensitivity analysis to determine the optimal integration of distribu...IJECEIAES
This paper presents a voltage sensitivity analysis with respect to the real power injected with renewable energies to determine the optimal integration of distributed generation (DG) in distribution systems (DS). The best nodes where the power injections improve voltages magnitudes complying with the constraints are determined. As it is a combinatorial problem, particle swarm optimization (PSO) and simulated annealing (SA) were used to change injections from 10% to 60% of the total power load using solar and wind generators and find the candidate nodes for installing power sources. The method was tested using the 33-node, 69-node and 118-node radial distribution networks. The results showed that the best nodes for injecting real power with renewable energies were selected for the distribution network by using the voltage sensitivity analysis. Algorithms found the best nodes for the three radial distribution networks with similar values in the maximum injection of real power, suggesting that this value maintains for all the power system cases. The injections applied to the different nodes showed that voltage magnitudes increase significantly, especially when exceeding the maximum penetration of DG. The test showed that some nodes support injections up to the limits, but the voltages increase considerably on all nodes.
Engineering Research Publication
Best International Journals, High Impact Journals,
International Journal of Engineering & Technical Research
ISSN : 2321-0869 (O) 2454-4698 (P)
www.erpublication.org
This paper presents a solution to solve the network reconfiguration, DG coordination (location and size) and capacitor coordination (location and size), simultaneously. The proposed solution will be determined by using Artificial Bee Colony (ABC). Various case studies are presented to see the impact on the test system, in term of power loss reduction and also voltage profiles. The proposed approach is applied to a 33-bus test system and simulate by using MATLAB programming. The simulation results show that combination of DG, capacitor and network reconfiguration gives a positive impact on total power losses minimization as well as voltage profile improvement compared to other case studies.
Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.
A review of techniques in optimal sizing of hybrid renewable energy systemseSAT Journals
Abstract This paper presents a review of techniques usedin recent published works on optimal sizing of hybrid renewable energy sources. Hybridization of renewable energy sources is an emergent promising trend born out of the need to fully utilize and solve problems associated with the reliability of renewable energy resources such as wind and solar. Exploitation of these resources has been instrumental in tackling or mitigating present day energy problems such as price instability for fossil based fuels, global warming and climate change in addition to being seen as way of meeting future demand for power. This paper targets researchers in the renewable energy space and the general public seeking to inform them on trends in methods applied in optimal sizing of hybrid renewable energy sources as well as to provide a scope into what has been done in this field. In reviewing previous works, a two prong approach has been used focusing attention on the sizing methods used in the reviewed works as well as the performance indices used to check quality by these works. In summary there is a clear indication of increased interest in recent years in optimal sizing of hybrid renewable energy resources with metaheuristic approaches such as Genetic Algorithms and Particle Swarm Optimization coming out as very interesting to researchers. It has also been observed that resources being hybridized are those with complementary regimes on specific sites.
Index Terms - Energy storage, hybrid power systems, optimization methods, renewable energy sources, reviews, solar energy, wind energy.
Fuzzy expert system based optimal capacitor allocation in distribution system-2IAEME Publication
One of the most popular image denoising methods based on self-similarity is called nonlocal
means (NLM). Though it can achieve remarkable performance, this method has a few shortcomings,
e.g., the computationally expensive calculation of the similarity measure, and the lack of reliable
candidates for some non repetitive patches. In this paper, we propose to improve NLM by integrating
Gaussian blur, clustering, and row image weighted averaging into the NLM framework.
Experimental results show that the proposed technique can perform denoising better than the original
NLM both quantitatively and visually, especially when the noise level is high.
Optimal Reactive Power Scheduling Using Cuckoo Search AlgorithmIJECEIAES
The article describes multidisciplinary design process of high-performance electric generator for advanced aircrafts by analytical methods and computer modeling techniques (electromagnetic, thermal and mechanical calculations). New technical solutions used in its development are described. The main ideas are revealed of the method of EG voltage stabilization we used. To improve the heat dissipation efficiency, we have developed a new cooling system, and provide its study and description in this paper. The advantages of this cooling system include the fact that EG is made with dry, uncooled rotor. This allowed eliminating additional pumps, and significantly reducing tThis paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.he size of CSD. According to the results of our study, we created an experimental full capacity layout, and its studies are also provided in this paper.
Voltage sensitivity analysis to determine the optimal integration of distribu...IJECEIAES
This paper presents a voltage sensitivity analysis with respect to the real power injected with renewable energies to determine the optimal integration of distributed generation (DG) in distribution systems (DS). The best nodes where the power injections improve voltages magnitudes complying with the constraints are determined. As it is a combinatorial problem, particle swarm optimization (PSO) and simulated annealing (SA) were used to change injections from 10% to 60% of the total power load using solar and wind generators and find the candidate nodes for installing power sources. The method was tested using the 33-node, 69-node and 118-node radial distribution networks. The results showed that the best nodes for injecting real power with renewable energies were selected for the distribution network by using the voltage sensitivity analysis. Algorithms found the best nodes for the three radial distribution networks with similar values in the maximum injection of real power, suggesting that this value maintains for all the power system cases. The injections applied to the different nodes showed that voltage magnitudes increase significantly, especially when exceeding the maximum penetration of DG. The test showed that some nodes support injections up to the limits, but the voltages increase considerably on all nodes.
Engineering Research Publication
Best International Journals, High Impact Journals,
International Journal of Engineering & Technical Research
ISSN : 2321-0869 (O) 2454-4698 (P)
www.erpublication.org
This paper presents a solution to solve the network reconfiguration, DG coordination (location and size) and capacitor coordination (location and size), simultaneously. The proposed solution will be determined by using Artificial Bee Colony (ABC). Various case studies are presented to see the impact on the test system, in term of power loss reduction and also voltage profiles. The proposed approach is applied to a 33-bus test system and simulate by using MATLAB programming. The simulation results show that combination of DG, capacitor and network reconfiguration gives a positive impact on total power losses minimization as well as voltage profile improvement compared to other case studies.
Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.
A review of techniques in optimal sizing of hybrid renewable energy systemseSAT Journals
Abstract This paper presents a review of techniques usedin recent published works on optimal sizing of hybrid renewable energy sources. Hybridization of renewable energy sources is an emergent promising trend born out of the need to fully utilize and solve problems associated with the reliability of renewable energy resources such as wind and solar. Exploitation of these resources has been instrumental in tackling or mitigating present day energy problems such as price instability for fossil based fuels, global warming and climate change in addition to being seen as way of meeting future demand for power. This paper targets researchers in the renewable energy space and the general public seeking to inform them on trends in methods applied in optimal sizing of hybrid renewable energy sources as well as to provide a scope into what has been done in this field. In reviewing previous works, a two prong approach has been used focusing attention on the sizing methods used in the reviewed works as well as the performance indices used to check quality by these works. In summary there is a clear indication of increased interest in recent years in optimal sizing of hybrid renewable energy resources with metaheuristic approaches such as Genetic Algorithms and Particle Swarm Optimization coming out as very interesting to researchers. It has also been observed that resources being hybridized are those with complementary regimes on specific sites.
Index Terms - Energy storage, hybrid power systems, optimization methods, renewable energy sources, reviews, solar energy, wind energy.
A Mixed Discrete-Continuous Attribute List Representation for Large Scale Cla...jaumebp
This work assesses the performance of the BioHEL data mining method to handle large-scale datasets, and proposes a representation to deal efficiently with domains with mixed discrete-continuous attributes
Reliability Prediction of Port Harcourt Electricity Distribution Network Usin...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
Impact of Dispersed Generation on Optimization of Power ExportsIJERA Editor
Dispersed generation (DG) is defined as any source of electrical energy of limited size that is connected directly to the distribution system of a power network. It is also called decentralized generation, embedded generation or distributed generation. Dispersed generation is any modular generation located at or near the load center. It can be applied in the form of rechargeable, such as, mini-hydro, solar, wind and photovoltaic system or in the form of fuel-based systems, such as, fuel cells and micro-turbines. This paper presents the impact of dispersed generation on the optimization of power exports. Computer simulation was carried out using the hourly loads of the selected distribution feeders on Kaduna distribution system as input parameters for the computation of the line loss reduction ratio index (LLRI). The result showed that the line loss reduced from 163.56MW to 144.61 MW when DG was introduced which is an indication of a reduction in line losses with the installation of DG at the various feeders of the distribution system. In all the feeders where DG is integrated, the average magnitude of the line loss reduction index is 0.8754 MW which is less than 1 indicating a reduction in the electrical line losses with the introduction of DG. The line loss reduction index confirmed that by integrating DG into the distribution system, the distribution losses are reduced and optimization of power exports is achieved The results of this research paper will form a basis to establish that proper location of distributed generation units have significant impact on their effective capacity.
Improvement of voltage profile for large scale power system using soft comput...TELKOMNIKA JOURNAL
In modern power system operation, control, and planning, reactive power as part of power system component is very important in order to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to improve the voltage profile and decrease the total power loss of transmission line system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. The effectiveness of the proposed technique is examined by utilizing Java-Madura-Bali (JAMALI) 500 kV power system grid as the test system. From the simulation results, the PSO and ABC algorithms are providing satisfactory results in obtaining the capacitor size and can reduce the total power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
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.
Multi-Population Methods with Adaptive Mutation for Multi-Modal Optimization ...ijscai
This paper presents an efficient scheme to locate multiple peaks on multi-modal optimization problems by
using genetic algorithms (GAs). The premature convergence problem shows due to the loss of diversity,
the multi-population technique can be applied to maintain the diversity in the population and the
convergence capacity of GAs. The proposed scheme is the combination of multi-population with adaptive
mutation operator, which determines two different mutation probabilities for different sites of the
solutions. The probabilities are updated by the fitness and distribution of solutions in the search space
during the evolution process. The experimental results demonstrate the performance of the proposed
algorithm based on a set of benchmark problems in comparison with relevant algorithms.
For years, the Machine Learning community has focused on developing efficient
algorithms that can produce very accurate classifiers. However, it is often much easier
to find several good classifiers based on dataset combination, instead of single classifier
applied on deferent datasets. The advantages of using classifier dataset combinations
instead of a single one are twofold: it helps lowering the computational complexity by
using simpler models, and it can improve the classification accuracy and performance.
Most Data mining applications are based on pattern matching algorithms, thus improving
the performance of the classification has a positive impact on the quality of the overall
data mining task. Since combination strategies proved very useful in improving the
performance, these techniques have become very important in applications such as
Cancer detection, Speech Technology and Natural Language Processing .The aim of this
paper is basically to propose proprietary metric, Normalized Geometric Index (NGI)
based on the latent properties of datasets for improving the accuracy of data mining tasks.
AN IMPROVED METHOD FOR IDENTIFYING WELL-TEST INTERPRETATION MODEL BASED ON AG...IAEME Publication
This paper presents an approach based on applying an aggregated predictor formed by multiple versions of a multilayer neural network with a back-propagation optimization algorithm for helping the engineer to get a list of the most appropriate well-test interpretation models for a given set of pressure/ production data. The proposed method consists of three stages: (1) data decorrelation through principal component analysis to reduce the covariance between the variables and the dimension of the input layer in the artificial neural network, (2) bootstrap replicates of the learning set where the data is repeatedly sampled with a random split of the data into train sets and using these as new learning sets, and (3) automatic reservoir model identification through aggregated predictor formed by a plurality vote when predicting a new class. This method is described in detail to ensure successful replication of results. The required training and test dataset were generated by using analytical solution models. In our case, there were used 600 samples: 300 for training, 100 for cross-validation, and 200 for testing. Different network structures were tested during this study to arrive at optimum network design. We notice that the single net methodology always brings about confusion in selecting the correct model even though the training results for the constructed networks are close to 1. We notice also that the principal component analysis is an effective strategy in reducing the number of input features, simplifying the network structure, and lowering the training time of the ANN. The results obtained show that the proposed model provides better performance when predicting new data with a coefficient of correlation approximately equal to 95% Compared to a previous approach 80%, the combination of the PCA and ANN is more stable and determine the more accurate results with lesser computational complexity than was feasible previously. Clearly, the aggregated predictor is more stable and shows less bad classes compared to the previous approach.
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.
Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensem...IJECEIAES
Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process to hypothesize useful knowledge from the extensive data. Based upon the classical statistical prototypes the data can be exploited beyond the storage and management of the data. Cluster analysis a primary investigation with little or no prior knowledge, consists of research and development across a wide variety of communities. Cluster ensembles are melange of individual solutions obtained from different clusterings to produce final quality clustering which is required in wider applications. The method arises in the perspective of increasing robustness, scalability and accuracy. This paper gives a brief overview of the generation methods and consensus functions included in cluster ensemble. The survey is to analyze the various techniques and cluster ensemble methods.
VOLTAGE PROFILE IMPROVEMENT AND LINE LOSSES REDUCTION USING DG USING GSA AND ...Journal For Research
In recent years, the power industry has experienced significant changes on the power distribution systems primarily due to the implementation of smart-grid technology and the incremental implementation of distributed generation. Distributed Generation (DG) is simply defined as the decentralization of power plants by placing smaller generating units closer to the point of consumption, traditionally ten mega-watts or smaller. The distribution power system is generally designed for radial power flow, but with the introduction of DG, power flow becomes bidirectional. Therefore this thesis focuses on testing various indices and using effective techniques for the optimal placement and sizing of the DG unit by minimizing power losses and voltage deviation. A 14-bus radial distribution system has been taken as the test system. The feasibility of the work lies on the fast execution of the programs as it would be equipped with the real time operation of the distribution system and it is seen that execution of the DG placement is quite fast and feasible with the optimization techniques used in this work.
ATTRIBUTE REDUCTION-BASED ENSEMBLE RULE CLASSIFIERS METHOD FOR DATASET CLASSI...csandit
Attribute reduction and classification task are an essential process in dealing with large data
sets that comprise numerous number of input attributes. There are many search methods and
classifiers that have been used to find the optimal number of attributes. The aim of this paper is
to find the optimal set of attributes and improve the classification accuracy by adopting
ensemble rule classifiers method. Research process involves 2 phases; finding the optimal set of
attributes and ensemble classifiers method for classification task. Results are in terms of
percentage of accuracy and number of selected attributes and rules generated. 6 datasets were
used for the experiment. The final output is an optimal set of attributes with ensemble rule
classifiers method. The experimental results conducted on public real dataset demonstrate that
the ensemble rule classifiers methods consistently show improve classification accuracy on the
selected dataset. Significant improvement in accuracy and optimal set of attribute selected is
achieved by adopting ensemble rule classifiers method.
A progressive domain expansion method for solving optimal control problemTELKOMNIKA JOURNAL
Electricity generation at the hydropower stations in Nigeria has been below the expected value. While the hydro stations have a capacity to generate up to 2,380 MW, the daily average energy generated in 2017 was estimated at around 846 MW. A factor responsible for this is the lack of a proper control system to manage the transfer of resources between the cascaded Kainji-Jebba Hydropower stations operating in tandem. This paper addressed the optimal regulation of the operating head of the Jebba hydropower reservoir in the presence of system constraints, flow requirement and environmental factors that are weather-related. The resulting two-point boundary value problem was solved using the progressive expansion of domain technique as against the shooting or multiple shooting techniques. The results provide the optimal inflow required to keep the operating head of the Jebba reservoir at a nominal level, hence ensuring that the maximum number of turbo-alternator units are operated.
Power System Reliability Assessment in a Complex Restructured Power SystemIJECEIAES
The basic purpose of an electric power system is to supply its consumers with electric energy as parsimoniously as possible and with a sensible degree of continuity and quality. It is expected that the solicitation of power system reliability assessment in bulk power systems will continue to increase in the future especially in the newly deregulated power diligence. This paper presents the research conducted on the three areas of incorporating multi-state generating unit models, evaluating system performance indices and identifying transmission paucities in complex system adequacy assessment. The incentives for electricity market participants to endow in new generation and transmission facilities are highly influenced by the market risk in a complex restructured environment. This paper also presents a procedure to identify transmission deficiencies and remedial modification in the composite generation and transmission system and focused on the application of probabilistic techniques in composite system adequacy assessment
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.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Mixed Discrete-Continuous Attribute List Representation for Large Scale Cla...jaumebp
This work assesses the performance of the BioHEL data mining method to handle large-scale datasets, and proposes a representation to deal efficiently with domains with mixed discrete-continuous attributes
Reliability Prediction of Port Harcourt Electricity Distribution Network Usin...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
Impact of Dispersed Generation on Optimization of Power ExportsIJERA Editor
Dispersed generation (DG) is defined as any source of electrical energy of limited size that is connected directly to the distribution system of a power network. It is also called decentralized generation, embedded generation or distributed generation. Dispersed generation is any modular generation located at or near the load center. It can be applied in the form of rechargeable, such as, mini-hydro, solar, wind and photovoltaic system or in the form of fuel-based systems, such as, fuel cells and micro-turbines. This paper presents the impact of dispersed generation on the optimization of power exports. Computer simulation was carried out using the hourly loads of the selected distribution feeders on Kaduna distribution system as input parameters for the computation of the line loss reduction ratio index (LLRI). The result showed that the line loss reduced from 163.56MW to 144.61 MW when DG was introduced which is an indication of a reduction in line losses with the installation of DG at the various feeders of the distribution system. In all the feeders where DG is integrated, the average magnitude of the line loss reduction index is 0.8754 MW which is less than 1 indicating a reduction in the electrical line losses with the introduction of DG. The line loss reduction index confirmed that by integrating DG into the distribution system, the distribution losses are reduced and optimization of power exports is achieved The results of this research paper will form a basis to establish that proper location of distributed generation units have significant impact on their effective capacity.
Improvement of voltage profile for large scale power system using soft comput...TELKOMNIKA JOURNAL
In modern power system operation, control, and planning, reactive power as part of power system component is very important in order to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to improve the voltage profile and decrease the total power loss of transmission line system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. The effectiveness of the proposed technique is examined by utilizing Java-Madura-Bali (JAMALI) 500 kV power system grid as the test system. From the simulation results, the PSO and ABC algorithms are providing satisfactory results in obtaining the capacitor size and can reduce the total power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
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.
Multi-Population Methods with Adaptive Mutation for Multi-Modal Optimization ...ijscai
This paper presents an efficient scheme to locate multiple peaks on multi-modal optimization problems by
using genetic algorithms (GAs). The premature convergence problem shows due to the loss of diversity,
the multi-population technique can be applied to maintain the diversity in the population and the
convergence capacity of GAs. The proposed scheme is the combination of multi-population with adaptive
mutation operator, which determines two different mutation probabilities for different sites of the
solutions. The probabilities are updated by the fitness and distribution of solutions in the search space
during the evolution process. The experimental results demonstrate the performance of the proposed
algorithm based on a set of benchmark problems in comparison with relevant algorithms.
For years, the Machine Learning community has focused on developing efficient
algorithms that can produce very accurate classifiers. However, it is often much easier
to find several good classifiers based on dataset combination, instead of single classifier
applied on deferent datasets. The advantages of using classifier dataset combinations
instead of a single one are twofold: it helps lowering the computational complexity by
using simpler models, and it can improve the classification accuracy and performance.
Most Data mining applications are based on pattern matching algorithms, thus improving
the performance of the classification has a positive impact on the quality of the overall
data mining task. Since combination strategies proved very useful in improving the
performance, these techniques have become very important in applications such as
Cancer detection, Speech Technology and Natural Language Processing .The aim of this
paper is basically to propose proprietary metric, Normalized Geometric Index (NGI)
based on the latent properties of datasets for improving the accuracy of data mining tasks.
AN IMPROVED METHOD FOR IDENTIFYING WELL-TEST INTERPRETATION MODEL BASED ON AG...IAEME Publication
This paper presents an approach based on applying an aggregated predictor formed by multiple versions of a multilayer neural network with a back-propagation optimization algorithm for helping the engineer to get a list of the most appropriate well-test interpretation models for a given set of pressure/ production data. The proposed method consists of three stages: (1) data decorrelation through principal component analysis to reduce the covariance between the variables and the dimension of the input layer in the artificial neural network, (2) bootstrap replicates of the learning set where the data is repeatedly sampled with a random split of the data into train sets and using these as new learning sets, and (3) automatic reservoir model identification through aggregated predictor formed by a plurality vote when predicting a new class. This method is described in detail to ensure successful replication of results. The required training and test dataset were generated by using analytical solution models. In our case, there were used 600 samples: 300 for training, 100 for cross-validation, and 200 for testing. Different network structures were tested during this study to arrive at optimum network design. We notice that the single net methodology always brings about confusion in selecting the correct model even though the training results for the constructed networks are close to 1. We notice also that the principal component analysis is an effective strategy in reducing the number of input features, simplifying the network structure, and lowering the training time of the ANN. The results obtained show that the proposed model provides better performance when predicting new data with a coefficient of correlation approximately equal to 95% Compared to a previous approach 80%, the combination of the PCA and ANN is more stable and determine the more accurate results with lesser computational complexity than was feasible previously. Clearly, the aggregated predictor is more stable and shows less bad classes compared to the previous approach.
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.
Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensem...IJECEIAES
Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process to hypothesize useful knowledge from the extensive data. Based upon the classical statistical prototypes the data can be exploited beyond the storage and management of the data. Cluster analysis a primary investigation with little or no prior knowledge, consists of research and development across a wide variety of communities. Cluster ensembles are melange of individual solutions obtained from different clusterings to produce final quality clustering which is required in wider applications. The method arises in the perspective of increasing robustness, scalability and accuracy. This paper gives a brief overview of the generation methods and consensus functions included in cluster ensemble. The survey is to analyze the various techniques and cluster ensemble methods.
VOLTAGE PROFILE IMPROVEMENT AND LINE LOSSES REDUCTION USING DG USING GSA AND ...Journal For Research
In recent years, the power industry has experienced significant changes on the power distribution systems primarily due to the implementation of smart-grid technology and the incremental implementation of distributed generation. Distributed Generation (DG) is simply defined as the decentralization of power plants by placing smaller generating units closer to the point of consumption, traditionally ten mega-watts or smaller. The distribution power system is generally designed for radial power flow, but with the introduction of DG, power flow becomes bidirectional. Therefore this thesis focuses on testing various indices and using effective techniques for the optimal placement and sizing of the DG unit by minimizing power losses and voltage deviation. A 14-bus radial distribution system has been taken as the test system. The feasibility of the work lies on the fast execution of the programs as it would be equipped with the real time operation of the distribution system and it is seen that execution of the DG placement is quite fast and feasible with the optimization techniques used in this work.
ATTRIBUTE REDUCTION-BASED ENSEMBLE RULE CLASSIFIERS METHOD FOR DATASET CLASSI...csandit
Attribute reduction and classification task are an essential process in dealing with large data
sets that comprise numerous number of input attributes. There are many search methods and
classifiers that have been used to find the optimal number of attributes. The aim of this paper is
to find the optimal set of attributes and improve the classification accuracy by adopting
ensemble rule classifiers method. Research process involves 2 phases; finding the optimal set of
attributes and ensemble classifiers method for classification task. Results are in terms of
percentage of accuracy and number of selected attributes and rules generated. 6 datasets were
used for the experiment. The final output is an optimal set of attributes with ensemble rule
classifiers method. The experimental results conducted on public real dataset demonstrate that
the ensemble rule classifiers methods consistently show improve classification accuracy on the
selected dataset. Significant improvement in accuracy and optimal set of attribute selected is
achieved by adopting ensemble rule classifiers method.
A progressive domain expansion method for solving optimal control problemTELKOMNIKA JOURNAL
Electricity generation at the hydropower stations in Nigeria has been below the expected value. While the hydro stations have a capacity to generate up to 2,380 MW, the daily average energy generated in 2017 was estimated at around 846 MW. A factor responsible for this is the lack of a proper control system to manage the transfer of resources between the cascaded Kainji-Jebba Hydropower stations operating in tandem. This paper addressed the optimal regulation of the operating head of the Jebba hydropower reservoir in the presence of system constraints, flow requirement and environmental factors that are weather-related. The resulting two-point boundary value problem was solved using the progressive expansion of domain technique as against the shooting or multiple shooting techniques. The results provide the optimal inflow required to keep the operating head of the Jebba reservoir at a nominal level, hence ensuring that the maximum number of turbo-alternator units are operated.
Power System Reliability Assessment in a Complex Restructured Power SystemIJECEIAES
The basic purpose of an electric power system is to supply its consumers with electric energy as parsimoniously as possible and with a sensible degree of continuity and quality. It is expected that the solicitation of power system reliability assessment in bulk power systems will continue to increase in the future especially in the newly deregulated power diligence. This paper presents the research conducted on the three areas of incorporating multi-state generating unit models, evaluating system performance indices and identifying transmission paucities in complex system adequacy assessment. The incentives for electricity market participants to endow in new generation and transmission facilities are highly influenced by the market risk in a complex restructured environment. This paper also presents a procedure to identify transmission deficiencies and remedial modification in the composite generation and transmission system and focused on the application of probabilistic techniques in composite system adequacy assessment
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.
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.
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.
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.
Utilization of Industrial Waste Material in GSB LayerIJERA Editor
India has series of steel plant clusters located along its length and breadth of the territory. Several million metric tons of iron and steel are produced in these plants annually. Along with the production of iron and steel, huge quantities of solid wastes like blast furnace slag and steel slag as well as other wastes such as flue dust, blast furnace sludge, and refractories are also being produced in these plants. These solid wastes can be used as non-traditional/non-conventional aggregates in pavement construction due to acute scarcity of traditional/conventional road construction materials. A study was conducted to investigate the possibility of using Granulated Blast Furnace Slag (GBFS) with various blended mixes of traditional/conventional aggregates in subbase layer with different percentages. This study also presents the result of experimental investigation on the influence of Rice husk ash (RHA) on the index properties of Red soil which is used as filler material in subbase layer.
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.
Synthesis and Structural Characterization of Cu Substituted Ni-Zn Nano-Ferrit...IJERA Editor
The ferrite nano particles having chemical formula Ni0.2CuxZn0.8-xFe2O4 (where x=0.0 to 0.8 with step of 0.2) were synthesized by Citrate-Gel Auto Combustion method at low temperature. The synthesized powders were sintered at 500oC for 4 hours in air and characterised by XRD, SEM with EDS. XRD analysis of prepared samples were confirmed the single phase cubic spinel Structure. The crystallite size (D) of prepared ferrites were in the range of 24-73nm. The values of lattice parameter (a) decreased and X-ray density (dx) were increased with the increasing of Cu substitution. The surface morphology of the prepared samples was investigated by Scanning Electron Microscope(SEM). An elemental composition of the samples was studied by Energy Dispersive Spectroscopy(EDS). The observed results can be explained on the basis of composition and crystal size.
Design and Simulation of First Order Sigma-Delta Modulator Using LT spice ToolIJERA Editor
A switched-capacitor single-stage Sigma-Delta ADC with a first-order modulator is proposed. Efficient low power first Order 1-Bit Sigma-Delta ADC designed which accepts input signal bandwidth of 10 MHz. This circuitry performs the function of an analog-to-digital converter. A first-order 1-Bit Sigma-Delta (Σ-Δ) modulator is designed, simulated and analyzed using LTspice standard 250nm CMOS technology power supply of 1.8V. The modulator is proved to be robustness, the high performance in stability. The simulations are compared with those from a traditional analog-to-digital converter to prove that Sigma-Delta is performing better with low power and area.
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.
Ship Detection from SAR Imagery Using CUDA and Performance Analysis of the Sy...IJERA Editor
Synthetic aperture radar (SAR) Ship Detection System SDS is an important application from the point of view of Maritime Security monitoring. It allows monitoring traffic, fisheries, naval warfare. Since full-resolution SAR images are heavily affected by the presence of speckle, ship detection algorithms generally employ speckle reduced SAR images at the expense of a degradation of the spatial resolution. The proposed Parzen-window-kernel-based algorithm and CFAR algorithm can be considered an alternative to manual inspection for large ocean areas. Promising results and high detection rates for the ships have been achieved. In Parzen-window-kernel-based algorithm for ship detection in synthetic aperture radar (SAR) images, first, the data-driving kernel functions of Parzen window are utilized to approximate the histogram of real SAR image, in order to complete the accurate modeling of SAR images. Then ship detection is implemented using a Constant False Alarm Rate (CFAR). After detecting threshold, the output is added to edge detection algorithm employed on SAR image. Clearer detection of ship candidates is obtained by applying Parzen-window-kernel-based algorithm by changing its window size. Experimental results show that SDS implemented using CUDA is faster than on CPU.
MHD convection flow of viscous incompressible fluid over a stretched vertical...IJERA Editor
The effect of thermal radiation, viscous dissipation and hall current of the MHD convection flow of the viscous incompressible fluid over a stretched vertical flat plate has been discussed by using regular perturbation and homotophy perturbation technique with similarity solutions. The influence of various physical parameters on velocity, cross flow velocity and temperature of fluid has been obtained numerically and through graphs.
Experimental Study for the Different Methods of Generating Millimeter WavesIJERA Editor
In this paper a analytical comparison and experimental implementation of different methods used in generating a low phase noise millimeter wave signals is presented. Four techniques were experimented and compared, Multiplication, phase lock loop (PLL), Injection locking (IL), and Injection locking with phase lock loop (ILPLL). The comparison and experimental results of a laboratory discussed.
My slides for presentation in Copenhagen 11 November 2011 on Creative Commons at the "Sharing is caring: Digitized cultural heritage for all" seminar organized by the Association of Danish Museums
“Livro de Estilo. PÚBLICO”, páginas 64 a 73. Edição do jornal Público, Lisboa, 1998.
Site oficial de Dinis Manuel Alves: www.mediatico.com.pt
Encontre-nos no twitter (www.witter.com/dmpa) e no facebook (www.facebook.com/dinis.alves).
Outros sítios de DMA: www.youtube.com/mediapolisxxi, www.youtube.com/fotographarte, www.youtube.com/tiremmedestefilme, www.youtube.com/camarafixa, http://videos.sapo.pt/lapisazul/playview/2, http://videos.sapo.pt/lapisazul/playview/3 e em www.mogulus.com/otalcanal
Ainda: www.mediatico.com.pt/diasdecoimbra/ , www.mediatico.com.pt/redor/ ,
www.mediatico.com.pt/fe/ , www.mediatico.com.pt/fitas/ , www.mediatico.com.pt/redor2/, www.mediatico.com.pt/foto/yr2.htm ,www.mediatico.com.pt/manchete/index.htm , www.mediatico.com.pt/nimas/
www.mediatico.com.pt/foto/index.htm , www.mediatico.com.pt/luanda/, www.slideshare.net/manchete/ , www.slideshare.net/dmpa , www.panoramio.com/user/765637, http://torgaemsms.blogspot.com
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.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Harmony Search Algorithmic Rule for Optimum Allocation and Size of Distribute...Dr. Amarjeet Singh
Various benefits earned by desegregation Distributed
Generation (DG) in distribution systems. Such advantages are
often achieved and increased if DGs area unit optimally sized
and placed within the systems. The current work presents
distribution generation (DG) allocation strategy with objective
of up node voltage and minimizes power loss of radial
distribution systems victimization improved multi objective
harmony search algorithmic program (IMOHS).IMOHS
algorithmic program uses sensitivity analysis for distinctive
the optimum locations of distribution generation units, the
successively reduces the real power loss and improves the
voltage profile in distribution system. The target is to scale
back active power losses to minimum, whereas to attain
voltage profiles within the network in needed and determined
limit. Within the gift work the optimum decigram placement
and size drawback is developed as a multi-objective
improvement drawback to attain the above mentioned
situation.
An IEEE 33-node and IEEE 69-node radial
distribution check systems are wont to show the effectiveness
of the Improved multi objective Harmony Search rule
(IMOHS). The results obtained from the IMOHS methodology
shows that vital loss reduction is feasible mistreatment
multiple optimum sized decigram units. It’s shown that the
IMOHS methodology provides higher ends up in comparisons
thereto obtained mistreatment alternative optimization ways
like GA and PSO.
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.
Transforming an Existing Distribution Network Into Autonomous MICRO-GRID usin...IJERA Editor
A distribution network with renewable and fossil-based resources can be operated as a micro-grid, in autonomous or nonautonomous modes. Autonomous operation of a distribution network requires cautious planning. In this context, a detailed methodology to develop a sustainable autonomous micro-grid is presented in this paper. The proposed methodology suggests novel sizing and siting strategies for distributed generators and structural modifications for autonomous micro-grids. This paper introduces the Particle Swarm Optimization (PSO) algorithm to solve the optimal network reconfiguration problem for power loss reduction. The PSO is a relatively new and powerful intelligence evolution method for solving optimization problems. It is a population-based approach. The PSO was inspired from natural behavior of the bees on how they find the location of most flowers. The proposed PSO algorithm is introduced with some modifications such as using an inertia weight that decreases linearly during the simulation. This setting allows the PSO to explore a large area at the start of the simulation.
Neuro-Genetic Optimization of LDO-fired Rotary Furnace Parameters for the Pro...IJERD Editor
The rising demand for high quality homogenous castings necessitate that vast amount of
manufacturing knowledge be incorporated in manufacturing systems. Rotary furnace involves several critical
parameters like excess air, flame temperature, rotational speed of the furnace drum, melting time, preheat air
temperature, fuel consumption and melting rate of the molten metal which should be controlled throughout the
melting process. A complex relationship exists between these manufacturing parameters and hence there is a
need to develop models which can capture this complex interrelationship and enable fast computation. In the
present work, we propose a generic approach where the applicability and effectiveness of neural network in
function approximation is used for rapid estimation of melting rate and they are integrated into the framework
of genetic evolutionary algorithm to form a neuro-genetic optimization technique. A neural network model is
trained with the experimental results. The results indicate that the heuristic converges to better solutions rapidly
as it provides the values of various process parameters for optimizing the objective in a single run and thus
assists for the improvement of quality in development of sound parts
COMPARISON BETWEEN THE GENETIC ALGORITHMS OPTIMIZATION AND PARTICLE SWARM OPT...IAEME Publication
Close range photogrammetry network design is referred to the process of placing a set of
cameras in order to achieve photogrammetric tasks. The main objective of this paper is tried to find
the best location of two/three camera stations. The genetic algorithm optimization and Particle
Swarm Optimization are developed to determine the optimal camera stations for computing the three
dimensional coordinates. In this research, a mathematical model representing the genetic algorithm
optimization and Particle Swarm Optimization for the close range photogrammetry network is
developed. This paper gives also the sequence of the field operations and computational steps for this
task. A test field is included to reinforce the theoretical aspects.
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.
Tap changer optimisation using embedded differential evolutionary programming...journalBEEI
Over-compensation and under-compensation phenomena are two undesirable results in power system compensation. This will be not a good option in power system planning and operation. The non-optimal values of the compensating parameters subjected to a power system have contributed to these phenomena. Thus, a reliable optimization technique is mandatory to alleviate this issue. This paper presents a stochastic optimization technique used to fix the power loss control in a high demand power system due to the load increase, which causes the voltage decay problems leading to current increase and system loss increment. A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). Consequently, EDEP was for solving optimizations problem in power system through the tap changer optimizations scheme. Results obtained from this study are significantly superior compared to the traditional EP with implementation on the IEEE 30-bus reliability test system (RTS) for the loss minimization scheme.
Decision Support System for Energy Saving Analysis in Manufacturing IndustryIJRES Journal
Nowadays the attempts to optimize energy efficiency and environmental impact are increasingly present in all activity areas and specifically in manufacturing industry. An innovative approach to achieve these optimizations lies in advanced combination of decision support technologies and Knowledge Management. A benchmarking energy saving tool (decision support tool) was carried out in four (4) different years, 2007 to 2010 in Niger mills limited, located in Calabar to generate energy intensity and energy intensity index of the period. The result obtained for energy intensity in 2007 was 2.30GJ/m3, Energy intensity for 2008 was 2.30GJ/m3, Energy intensity for 2009 was 2.40GJ/m3, and energy intensity for 2010 was 2.30GJ/m3. This result shows that for the period of these four years, that the energy consumed is in an average range of 2.30GJ/m3. That if the productivity increase as the result of increase in production, the energy intensity will increase to 2.40GJ/m3 or there about as the case maybe as a result of increase in production.
El artículo presenta los resultados obtenidos del cálculo: potencia óptima de generación, conectada en un punto requerido de la red, que minimice las pérdidas del sistema de distribución. Para la búsqueda de dicha potencia se hizo uso del algoritmo de optimización por enjambre de partículas o PSO (por sus siglas en inglés), en el entorno del lenguaje de programación de DIgSILENT (DPL).
Los resultados mostraron que el algoritmo resultó muy eficiente en la codificación, así como se consiguió una rápida convergencia. Ello, hace posible su aplicación en redes de distribución, balanceadas y desbalanceadas.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Communications Mining Series - Zero to Hero - Session 1
O044049498
1. Manikanda Prabhu. J et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 4( Version 4), April 2014, pp.94-98
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Literature Survey on Voltage Profile Management Methods of
Distributed Generation
Chandragupta Mauryan. K. S1
, Manikanda Prabhu. J2
, Senapathi. N. K3
,
Madhumitha. D 4
1
Assistant Professor, 2, 3, 4
PG Scholars, Power System Engineering, Sri Krishna College of Technology,
Tamilnadu, India.
ABSTRACT
Distributed Generation (DG) has been utilized in some electrical networks in order to manage the low level
demand. Environmental and economical issues have driven significant increase in the development of
distributed generation. DG connected to the distribution systems, however, may impose negative influences with
respect to power quality and efficiency. This negative influence is based on the location of the DG in the
distributed system. In order to optimally positioning the DG in the system to improve the power quality and
efficiency many algorithms are used. In this paper we made a literature survey on different algorithms used for
positioning and sizing of DG in order to reduce losses, maintaining voltage profile. Also we have explained the
methodology of each algorithms used.
Keywords - Artificial Bee Colony, Ant Colony Optimization, Distributed Generation, Genetic Algorithm,
Optimization Algorithms.
I. INTRODUCTION
Distributed generation for a moment is
loosely defined as small scale electricity generation,
is a fairly new concept in the economics literature
about electricity markets, but the idea behind it is not
new at all. Interconnecting DG to an existing
distribution system provides various benefits for
example an enhanced power quality, higher
reliability. DG is a method of generating electricity
on a small scale from renewable and non-renewable
energy sources. DG systems are located close to
where the electricity is being used and hence the
position of DG places an important role in achieving
better efficiency. And so many optimizing algorithms
are used for optimally positioning and sizing the DG
systems. Each algorithm gives different results since
their methodology is entirely different from each
other. In this paper we have discussed about various
algorithms used for positioning and sizing of DG.
The introduction about algorithms and their
methodology have been described. This paper gives
the clear idea about the concepts of different
optimization algorithms.
II. OVERVIEW OF DISTRIBUTED
GENERATION
Before launching into an overview of
distributed generation, it is appropriate to put forward
a definition or at least an operational confine related
to distributed generation. It is generally agreed upon
that any electric power production technology that is
such that it is integrated within distribution systems
fits under the distributed generation umbrella. The
designations “distributed” and “dispersed” are used
interchangeably. The single line diagram of DG is
shown in fig.1
Fig.1: Single Line Diagram of Two Bus System
Distributed generation (or DG) generally
refers to small-scale (typically 1 kW – 50 MW)
electric power generators that produce electricity at a
site close to customers or that are tied to an electric
distribution system. Distributed generation, also
called on-site generation, dispersed
generation, embedded generation, decentralized
generation, decentralized energy, distributed energy
or district energy generates electricity from many
small energy sources.
Distributed generation is an approach that
employs small-scale technologies to produce
electricity close to the end users of power.
DG technologies often consist of modular
(and sometimes renewable-energy) generators, and
they offer a number of potential benefits. In many
cases, distributed generators can provide lower-cost
RESEARCH ARTICLE OPEN ACCESS
2. Manikanda Prabhu. J et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 4( Version 4), April 2014, pp.94-98
www.ijera.com 95 | P a g e
electricity and higher power reliability and security
with fewer environmental consequences than can
traditional power generators.
One can further categorize distributed
generation technologies as renewable and
nonrenewable.
Renewable technologies include:
Solar, photovoltaic or thermal
Wind
Geothermal
Ocean.
Nonrenewable technologies include:
Internal combustion engine, ice
Combined cycle
Combustion turbine
Micro turbines
Fuel cell.
Distributed generation should not to be
confused with renewable generation. Distributed
generation technologies may be renewable or not; in
fact, some distributed generation technologies could,
if fully deployed, significantly contribute to present
air pollution problems.
III. OPTIMIZATION ALGORITHMS
3.1 ANT COLONY OPTIMIZATION (ACO):
Since it was proposed as an optimization
method in 1991 by Dorigo et al., ACO techniques
have been attracting the attention of more researchers
[1]. The ACO algorithm is originally inspired by the
biological behavior of the ants and, specifically, their
way of communication [1]. In this algorithm the ant’s
movement is taken into account for placing of
distributed generators in the distributed side. Such
that each ants are placed at the home colony and are
allocated the next node. Also pheromone (link) is
given to each ant. The ant does not communicate
with each other directly and each follows a different
path to reach the node. Thus an n number of paths for
reaching the nodes are obtained and from that the
shortest and low cost path is chosen for optimizing.
This process is iterated until a stopping criterion is
reached where the Table.1 shows the process of
genetic algorithm.
TABLE 1: A Genetic ACO Algorithm.
In the optimal placement of DG in the
distribution network, ACO minimizes the DG
investment cost and total operating cost. It improves
quality and reliability. But the theoretical value
calculation is difficult. It is not independent and time
to convergence is uncertain.
3.2 VECTOR SWARM ALGORITHM (VSA):
VSO same as most of the evolutionary
techniques is started with an initial population
randomly and the steps of algorithm are iteratively
repeated until a termination criterion is met such as a
maximum number of generations or when there has
been no change in the solution found of the problem
for a given number of generations.
VSO algorithm can be simplified as below:
1) Initialize population of random vectors (the
parents population of the first iteration)
2) Calculate the fitness of each vector
3) Generate a new population of vectors based on
fitness children of population is obtained by changing
in the value of each dimension of each parental
population based on four operators: Participation,
Mutation, Conformation and Selection.
4) Repeat steps 2 and 3 until a termination criterion
is met.
This operator is introduced by suitable combines of
multiple vectors for problem search space, which is
consist of two sections:
a) Vector Direct Cooperation,
b) Vector Difference Cooperation.
3.3 HARMONY SEARCH ALGORITHM
(HSA):
The HSA is a new meta-heuristic population
search algorithm proposed by Geem et al, Daset al
[4]., proposed an explorative HS (EHS) algorithm to
many benchmarks problems successfully. HSA was
derived from the natural phenomena of musicians’
behavior when they collectively play their musical
instruments (population members) to come up with a
pleasing harmony (global optimal solution) [4].
The main steps of HS are as follows:
Step1-Initialize the problem and algorithm
parameters:
In this step the problem statement is
formulated and the required variables and parameters
are defined.
Step2-Initialize the harmony memory:
The initialization of the harmony memory is
made. Such that the memory space and the memory
for the defined variables and parameters are also
allocated.
Step3-Improvise a new harmony:
After the first two steps are over, the
harmony search is started and many harmonies are
STEP 1 INITIALIZATION
initialize
pheromone trail
STEP 2
SOLUTION
CONSTRUCTION
For each and
repeat solution
construction using
pheromone trail.
STEP 3
UPDATE THE
PHEROMONE
TRAIL
until stopping
criteria
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generated for the defined problem. The selection of
the best harmony and rejection of the worst harmony
are also made in this step.
Step 4-Update the harmony memory:
After selecting the new harmony (best one),
the space for the new one is allocated and that of old
harmony is erased.
Step 5-Check the termination criterion:
This step is for redirecting as well as
terminating the process. A check is made to ensure
whether a best result is obtained for the stated
problem. If the result achieved satisfies the condition
then the process gets terminated or else the steps 3 &
4 are executed until the condition gets satisfied.
3.4 GENETIC ALGORITHM (GA):
Genetic algorithm is based on techniques on
principles from the genetic and evolution mechanism
observed from the natural system and living beings
[2]. In general it consists of three types of searches
1. Initial population creation
2. Evaluation of the fitness function
3. New population production
A genetic first starts with then initial
population searches, where each individual is
evaluated by its fitness function. Subsequent values
are eliminated by its fitness values. This GA leads
generation of high performing individuals. The GA
has three different types of operators. In first
operator, an individual makes performs a high fitness
value. In second operator, it selects two individuals
within generation and carries a swapping operation.
3. Third operator used to explore some of invested
point in search space, called mutation operator.
Using GA in distributed generation minimizes
the total real power losses. Also it works on both
discrete and continuous parameters. But the main
drawback is the lack of accuracy when a high quality
solution is required.
3.5 ARTIFICIAL BEE COLONY ALGORITHM
(ABC):
The artificial bee colony algorithm is a new meta-
heuristic optimization approach, introduced in 2005
by Karabog [3]. Used for both constrained and
unconstrained optimization problems and also the
results obtained in this method is better than the other
methods of optimization. The colony of artificial bees
consists of three types of bees-employed, onlookers
and scout bees [3]. The employed bees are those who
search for food sources (solutions) and share them to
the onlookers that are waiting in the dance area of the
hive. As the information are shared by means of
dancing only. The duration of the dance is
proportional to the nectar content (fitness value) of
the food source currently being exploited by the
employed bees. The dances performed by the
employed bees are watched by onlookers and scout
bees and they choose the best food source and avoids
the bad ones. Once the onlookers choose the food
source (solution) they change their status and become
employed bees. Meanwhile if the food source is fully
visited means the corresponding employed bee
becomes scout bees or onlookers. The total size of
the algorithm is divided into two halves- one half is
assigned to employed bees, in which each individual
represents the separate food source. And the other
half represents the onlookers. The entire algorithm
process comprises of three steps.
1.Finding the possible food source by sending the
employed bees and also calculating the fitness
value.
2.Selecting the best food source and rejecting the
bad ones by using the onlookers, i.e., sharing the
information between employed and onlookers.
3.Determining the scout bees and then sending them
into entirely new food source positions [3].
On using the ABC algorithm, we can
minimize the total system real power loss subject to
equality and inequality constraints. Unless other
metaheuristic algorithms, ABC has only 2 parameters
to be tuned which avoids complexity. The only
drawback is that the efficiency of the process is
confirmed only by tuning the parameters.
3.6 DIFFERENTIAL EVOLUTION
ALGORITHM (DEA):
Differential evolution (DE) is a method that
optimizes a problem by iteratively trying to improve
a candidate solution with regard to a given measure
of quality. A basic variant of the DE algorithm works
by having a population of candidate solutions (called
agents). These agents are moved around in the
search-space by using simple mathematical formulae
to combine the positions of existing agents from the
population. If the new position of an agent is an
improvement it is accepted and forms part of the
population, otherwise the new position is simply
discarded. The process is repeated and by doing so it
is hoped, but not guaranteed, that a satisfactory
solution will eventually be discovered.
IV. COMPARISON
The Table.2 shows the different algorithms
such as Ant Colony, Artificial Bee Colony, Genetic
Algorithm, Vector Swarm Algorithm, Harmony
Search Algorithm and Differential Evolution
Algorithm.
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Table 2: Difference Between Various Algorithms:
SL.NO. ALGORITHM METHODOLOGY OBJECTIVE BENEFITS DRAWBACKS
1. ACO
Based on the
movement of ants. The
result generated
depends on the path
developed by the ants.
Minimizing the
DG investment
cost and total
operating cost
It improves quality
and reliability.
Theoretical value is
difficult. It is not
independent. Time
to convergence is
uncertain.
2. GA
It is a population
search technique.
Based on the fitness
value generated the
results are obtained.
Minimization of
total real power
losses.
It works on both
discrete and
continuous
parameters.
Lack of accuracy
when a high quality
solution is required.
3. VSA
It is an evolutionary
technique based on
population search. But
this population search
is different from the
GA search.
Reduces the size
of step velocity.
The convergence
rate is improved. It
controls the
movement of
particle.
More sophisticated
finite element
formulation.
4. HSA
It is the concept from
natural musical
performance process.
The solution depends
on the harmony
generated by the
musical instruments.
Minimization of
power loss.
Diversification is
controlled.
It requires more
number of
parameters.
5. ABC
It is a new concept
based on the path of
honey bees. The path
used by honey bees to
collect honey gives the
solution.
To minimize the
total system real
power loss
subject to
equality and
inequality
constraints.
Unless other
metaheuristic
algorithms, ABC
has only 2
parameters to be
tuned.
The efficiency is
confirmed by
tuning of
parameters.
6 DEA
It is a method to
optimize a problem by
maintaining a
population of
candidate solutions and
creating new candidate
solutions by combining
existing ones.
By using
Differential
Evolution (DE)
for the
placement of DG
units in electrical
distribution
systems to
reduce the power
losses and to
improve the
voltage profile.
It improves the
overall efficiency
of power system
and the
performance of
distribution system
must be improved.
DE is used for
multidimensional
real-valued
functions but does
not use the gradient
of the problem
being optimized
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ISSN : 2248-9622, Vol. 4, Issue 4( Version 4), April 2014, pp.94-98
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V. CONCLUSION
In this paper the different algorithms used
for the optimization of distributed generation in the
distribution networks are presented. The
methodology of each algorithm is described and
finally a comparison is made on the methodology and
their effect in the distributed generation. The
comparison shows us that one algorithm is superior
to one another.
REFERENCE
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[3] Fahad S. Abu-Mouti, EL-Hawary, “Optimal
Distributed Generation Allocation and
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2011.
[4] R. Srinivasa Rao, K. Ravindra, K. Satish,
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