{"title":"Solving OPF Problems using Biogeography Based and Grey Wolf Optimization Techniques","authors":"Kingsuk Majumdar, Puja Das, P. Roy, Subrata Banerjee","doi":"10.4018/IJEOE.2017070103","DOIUrl":"https://doi.org/10.4018/IJEOE.2017070103","url":null,"abstract":"Thispaperpresentsbiogeography-basedoptimization(BBO)andgreywolfOptimization(GWO)for solvingthemulti-constrainedoptimalpowerflow(OPF)problemsinthepowersystem.Inthispaper, theproposedalgorithmshavebeentestedin9-bussystemundervariousconditionsalongwithIEEE 30bustestsystem.Acomparisonofsimulationresultsrevealsoptimizationefficacyoftheproposed schemeoverevolutionaryprogramming(EP),geneticalgorithm(GA),mixed-integerparticleswarm optimization(MIPSO)fortheglobaloptimizationofmulti-constraintOPFproblems.Itisobserved thatGWOisfarbetterincomparisontootherlistedoptimizationtechniquesandcanbeusedfor aforesaidproblemswithhighefficiency. KEyWORdS Biogeography Based Optimization, Grey Wolf Optimization, Migration, Mutation, Optimal Power Flow","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131686129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-01DOI: 10.4018/IJEOE.2017070102
P. Balachandar, S. Ganesan, N. Jayakumar, S. Subramanian
The electrical power generation from fossil fuel releases several contaminants into the air and this become excrescent if the generating unit is fed by Multiple Fuel Sources MFS.The ever more stringent environmental regulations have forced the power producers to produce electricity not only at the cheapest price but also at the minimum level of pollutant emissions. Inclusion of this issue in the operational task is a welcome perspective. The cost effective and environmental responsive power system operations in the presence of MFS can be recognized as a multi-objective constrained optimization problem with conflicting operational objectives. The modern meta-heuristic algorithm namely, Ant Lion Optimizer ALO has been applied for the first time to obtain the feasible solution. The fuzzy decision-making mechanism has been integrated to determine the Best Compromise Solution BCS in the multi-objective framework. The intended algorithm is implemented on the standard test systems considering valve-point effects, CO2 emission and tie-line limits.
{"title":"Multi-Fuel Power Dispatch in an Interconnected Power System using Ant Lion Optimizer: Multi-Fuel Dispatch Considering Tie-Line Limits","authors":"P. Balachandar, S. Ganesan, N. Jayakumar, S. Subramanian","doi":"10.4018/IJEOE.2017070102","DOIUrl":"https://doi.org/10.4018/IJEOE.2017070102","url":null,"abstract":"The electrical power generation from fossil fuel releases several contaminants into the air and this become excrescent if the generating unit is fed by Multiple Fuel Sources MFS.The ever more stringent environmental regulations have forced the power producers to produce electricity not only at the cheapest price but also at the minimum level of pollutant emissions. Inclusion of this issue in the operational task is a welcome perspective. The cost effective and environmental responsive power system operations in the presence of MFS can be recognized as a multi-objective constrained optimization problem with conflicting operational objectives. The modern meta-heuristic algorithm namely, Ant Lion Optimizer ALO has been applied for the first time to obtain the feasible solution. The fuzzy decision-making mechanism has been integrated to determine the Best Compromise Solution BCS in the multi-objective framework. The intended algorithm is implemented on the standard test systems considering valve-point effects, CO2 emission and tie-line limits.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115785703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.4018/IJEOE.2017040102
L. Ngubevana
Global warming due to greenhouse gas emissions and the growing energy needs of the world, has forced the world into thinking differently about energy sources and sustainable development, giving rise to the field of biofuels. Research and introduction of new technologies do, by their very nature, look to bring about positive change in society. Often though, changes result in unintended, unexpected, unforeseen, unforeseeable and unaddressed consequences. It often becomes the role of ethics protocols to militate against these negative consequences. In trying to establish the levels of awareness among South African researchers and producers of biofuels, to the sustainable development dilemmas brought about by their work; the “Five Capitals Framework†and a research ethics protocol, research was carried out at three South African businesses, generating data from interviews and collaborating with data from company publications. The study concluded that industry was indeed aware of the dilemmas that face their industry albeit that it was not in the context of a defined necessary framework.
{"title":"Sustainable Development Dilemmas of Biofuels Research and Production: A Snapshot in South Africa","authors":"L. Ngubevana","doi":"10.4018/IJEOE.2017040102","DOIUrl":"https://doi.org/10.4018/IJEOE.2017040102","url":null,"abstract":"Global warming due to greenhouse gas emissions and the growing energy needs of the world, has forced the world into thinking differently about energy sources and sustainable development, giving rise to the field of biofuels. Research and introduction of new technologies do, by their very nature, look to bring about positive change in society. Often though, changes result in unintended, unexpected, unforeseen, unforeseeable and unaddressed consequences. It often becomes the role of ethics protocols to militate against these negative consequences. In trying to establish the levels of awareness among South African researchers and producers of biofuels, to the sustainable development dilemmas brought about by their work; the “Five Capitals Framework†and a research ethics protocol, research was carried out at three South African businesses, generating data from interviews and collaborating with data from company publications. The study concluded that industry was indeed aware of the dilemmas that face their industry albeit that it was not in the context of a defined necessary framework.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129274351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.4018/IJEOE.2017040105
Moumita Pradhan, P. Roy, T. Pal
In this paper, an oppositional backtracking search algorithm (OBSA) is proposed to solve the large scale economic load dispatch (ELD) problem. The main drawback of the conventional backtracking search algorithm (BSA) is that it produces a local optimal solution rather than the global optimal solution. The proposed OBSA methodology is a highly-constrained optimization problem has to minimize the total generation cost by satisfying several constraints involving load demand, generation limits, prohibited operating zone, ramp rate limits and valve point loading effect. The proposed method is applied for three test systems and provides the unique and fast solutions. The new heuristic OBSA approach is successfully applied in three test systems consisting of 13 and 140 thermal generators. The test results are judged against various methods. The simulation results show the effectiveness and accuracy of the proposed OBSA algorithm over other methods like conventional BSA, oppositional invasive weed optimization (OIWO), Shuffled differential evolution (SDE) and oppositional real coded chemical reaction optimization (ORCCRO). This clearly suggests that the new OBSA method can achieve effective and feasible solutions of nonlinear ELD problems.
{"title":"Economic Load Dispatch Using Oppositional Backtracking Search Algorithm","authors":"Moumita Pradhan, P. Roy, T. Pal","doi":"10.4018/IJEOE.2017040105","DOIUrl":"https://doi.org/10.4018/IJEOE.2017040105","url":null,"abstract":"In this paper, an oppositional backtracking search algorithm (OBSA) is proposed to solve the large scale economic load dispatch (ELD) problem. The main drawback of the conventional backtracking search algorithm (BSA) is that it produces a local optimal solution rather than the global optimal solution. The proposed OBSA methodology is a highly-constrained optimization problem has to minimize the total generation cost by satisfying several constraints involving load demand, generation limits, prohibited operating zone, ramp rate limits and valve point loading effect. The proposed method is applied for three test systems and provides the unique and fast solutions. The new heuristic OBSA approach is successfully applied in three test systems consisting of 13 and 140 thermal generators. The test results are judged against various methods. The simulation results show the effectiveness and accuracy of the proposed OBSA algorithm over other methods like conventional BSA, oppositional invasive weed optimization (OIWO), Shuffled differential evolution (SDE) and oppositional real coded chemical reaction optimization (ORCCRO). This clearly suggests that the new OBSA method can achieve effective and feasible solutions of nonlinear ELD problems.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117055026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.4018/IJEOE.2017040101
T. Page
The aim of the study was to investigate as to whether piezoelectric energy harvesting could be a viable contributor to a source of renewable energy for the future. Here, a keyboard usage study was conducted using a data gathering computer program called WhatPulse in which participants and their keyboards were monitored for one week. The results were used in conjunction with power output figures from work done by Wacharasindhu and Kwon (2008) who prototyped a piezoelectric keyboard and found it was capable of producing 650 µJ of energy per keystroke. The results from this study suggest piezoelectric keyboards could not be used to create self-sustaining systems for any of the devices proposed. Further uses for the stored energy have been suggested but the question to the viability of piezoelectric keyboards as a useful energy source looks discouraging. Other applications for the technology could be explored to enhance power output and utilise larger amounts of vibrational energy.
{"title":"A Feasibility Study in Energy Harvesting from Piezoelectric Keyboards","authors":"T. Page","doi":"10.4018/IJEOE.2017040101","DOIUrl":"https://doi.org/10.4018/IJEOE.2017040101","url":null,"abstract":"The aim of the study was to investigate as to whether piezoelectric energy harvesting could be a viable contributor to a source of renewable energy for the future. Here, a keyboard usage study was conducted using a data gathering computer program called WhatPulse in which participants and their keyboards were monitored for one week. The results were used in conjunction with power output figures from work done by Wacharasindhu and Kwon (2008) who prototyped a piezoelectric keyboard and found it was capable of producing 650 µJ of energy per keystroke. The results from this study suggest piezoelectric keyboards could not be used to create self-sustaining systems for any of the devices proposed. Further uses for the stored energy have been suggested but the question to the viability of piezoelectric keyboards as a useful energy source looks discouraging. Other applications for the technology could be explored to enhance power output and utilise larger amounts of vibrational energy.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127725297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.4018/IJEOE.2017040104
Ashwani Kharola, P. Patil
This paper presents an offline control of ball and beam system using fuzzy logic. The objective is to control ball position and beam orientation using fuzzy controllers. A Matlab/Simulink model of the proposed system has been designed using Newton's equations of motion. The fuzzy controllers were built using seven gbell membership functions. The performance of proposed controllers was compared in terms of settling time, steady state error and overshoot. The simulation results are shown with the help of graphs and tables which illustrates the effectiveness and robustness of proposed technique.
{"title":"Neural Fuzzy Control of Ball and Beam System","authors":"Ashwani Kharola, P. Patil","doi":"10.4018/IJEOE.2017040104","DOIUrl":"https://doi.org/10.4018/IJEOE.2017040104","url":null,"abstract":"This paper presents an offline control of ball and beam system using fuzzy logic. The objective is to control ball position and beam orientation using fuzzy controllers. A Matlab/Simulink model of the proposed system has been designed using Newton's equations of motion. The fuzzy controllers were built using seven gbell membership functions. The performance of proposed controllers was compared in terms of settling time, steady state error and overshoot. The simulation results are shown with the help of graphs and tables which illustrates the effectiveness and robustness of proposed technique.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129882596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-01DOI: 10.4018/IJEOE.2017040103
Ajit Kumar Barisal, T. Panigrahi, S. Mishra
This article presents a hybrid PSO with Levy flight algorithm (LFPSO) for optimization of the PID controllers and employed in automatic generation control (AGC) of nonlinear power system. The superiority of the proposed LFPSO approach has been demonstrated with comparing to recently published Lozi map-based chaotic optimization algorithm (LCOA) and Particle swarm optimization to solve load-frequency control (LFC) problem. It is found that the proposed LFPSO method has robust dynamic behavior in terms of settling times, overshoots and undershoots by varying the system parameters and loading conditions from their nominal values as well as size and locations of disturbance. Secondly, a three-area thermal power system is considered with nonlinear as Generation Rate Constraints (GRC) and outperforms to the results of Bacteria Foraging algorithm based integral controller as well as hybrid Differential Evolution and Particle Swarm Optimization based fuzzy PID controller for the similar power system. Finally, the proficiency of the proposed controller is also verified by random load patterns.
{"title":"A Hybrid PSO-LEVY Flight Algorithm Based Fuzzy PID Controller for Automatic Generation Control of Multi Area Power Systems: Fuzzy Based Hybrid PSO for Automatic Generation Control","authors":"Ajit Kumar Barisal, T. Panigrahi, S. Mishra","doi":"10.4018/IJEOE.2017040103","DOIUrl":"https://doi.org/10.4018/IJEOE.2017040103","url":null,"abstract":"This article presents a hybrid PSO with Levy flight algorithm (LFPSO) for optimization of the PID controllers and employed in automatic generation control (AGC) of nonlinear power system. The superiority of the proposed LFPSO approach has been demonstrated with comparing to recently published Lozi map-based chaotic optimization algorithm (LCOA) and Particle swarm optimization to solve load-frequency control (LFC) problem. It is found that the proposed LFPSO method has robust dynamic behavior in terms of settling times, overshoots and undershoots by varying the system parameters and loading conditions from their nominal values as well as size and locations of disturbance. Secondly, a three-area thermal power system is considered with nonlinear as Generation Rate Constraints (GRC) and outperforms to the results of Bacteria Foraging algorithm based integral controller as well as hybrid Differential Evolution and Particle Swarm Optimization based fuzzy PID controller for the similar power system. Finally, the proficiency of the proposed controller is also verified by random load patterns.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127784674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.4018/IJEOE.2016100102
Y. Oğuz, M. Şahin, Yılmaz Güven, Hatice Zeliha Tugcu
The quality of energy has been defined to control harmonics caused by non-linear loads and international standards were brought to overcome the harmonic related problems. In determining the power quality, parameters like current-voltage harmonic, transient, flicker, current and voltage imbalance between phases, K factor are examined according to these international standards. The biggest disadvantage of harmonics is that they do not affect the power quality over an individual network but also affect the entire energy system primarily neighbouring facilities. Therefore, the energy system of Opium Alkaloids Plant was examined by using measurements information of current and voltage harmonics affecting the energy quality. And, it has been determined that the harmonics have a negative impact on energy quality. According to these findings, it has been proposed to install a well-designed filter for elimination of harmonics. Besides, it has been emphasised that new hardwares and devices should be chosen to support this harmonic filtering system in the future. KEywORdS Capacitor, Energy Quality, Harmonics, Power Systems, Reactive Power
{"title":"Analysing of Harmonics Affecting the Energy Quality in Opium Alkaloids Plant's Power System","authors":"Y. Oğuz, M. Şahin, Yılmaz Güven, Hatice Zeliha Tugcu","doi":"10.4018/IJEOE.2016100102","DOIUrl":"https://doi.org/10.4018/IJEOE.2016100102","url":null,"abstract":"The quality of energy has been defined to control harmonics caused by non-linear loads and international standards were brought to overcome the harmonic related problems. In determining the power quality, parameters like current-voltage harmonic, transient, flicker, current and voltage imbalance between phases, K factor are examined according to these international standards. The biggest disadvantage of harmonics is that they do not affect the power quality over an individual network but also affect the entire energy system primarily neighbouring facilities. Therefore, the energy system of Opium Alkaloids Plant was examined by using measurements information of current and voltage harmonics affecting the energy quality. And, it has been determined that the harmonics have a negative impact on energy quality. According to these findings, it has been proposed to install a well-designed filter for elimination of harmonics. Besides, it has been emphasised that new hardwares and devices should be chosen to support this harmonic filtering system in the future. KEywORdS Capacitor, Energy Quality, Harmonics, Power Systems, Reactive Power","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132764377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.4018/IJEOE.2016100103
M. Omran
In this work, quantum particle swarm optimization (QPSO1) algorithm method is applied to the problem of impurity at the center of a spherical quantum dot for infinite confining potential case. For this purpose, a trial variational wave function is considered for ground state, and then energy values are calculated as a function of the radius of a spherical quantum dot. Also, the evolution of the energy eigenvalue for different dot radii and different optimized parameter is determined. The energy converges remarkably fast, after a few numbers of iteration. In comparison with the two other available methods, standard variational procedure and genetic algorithm method (GA), the results coming out from QPSO algorithm are in more satisfactory agreement with the real values.
{"title":"Computing of the Ground State Energy of a Hydrogen Like Impurity in a Spherical Quantum Dot using QPSO Algorithm","authors":"M. Omran","doi":"10.4018/IJEOE.2016100103","DOIUrl":"https://doi.org/10.4018/IJEOE.2016100103","url":null,"abstract":"In this work, quantum particle swarm optimization (QPSO1) algorithm method is applied to the problem of impurity at the center of a spherical quantum dot for infinite confining potential case. For this purpose, a trial variational wave function is considered for ground state, and then energy values are calculated as a function of the radius of a spherical quantum dot. Also, the evolution of the energy eigenvalue for different dot radii and different optimized parameter is determined. The energy converges remarkably fast, after a few numbers of iteration. In comparison with the two other available methods, standard variational procedure and genetic algorithm method (GA), the results coming out from QPSO algorithm are in more satisfactory agreement with the real values.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116694043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.4018/IJEOE.2016100101
Sumit Banerjee, C. K. Chanda, D. Maity
This article presents a novel improved teaching learning based optimization (I-TLBO) technique to solve economic load dispatch (ELD) problem of the thermal plant without considering transmission losses. The proposed methodology can take care of ELD problems considering practical nonlinearities such as ramp rate limit, prohibited operating zone and valve point loading. The objective of economic load dispatch is to determine the optimal power generation of the units to meet the load demand, such that the overall cost of generation is minimized, while satisfying different operational constraints. I-TLBO is a recently developed evolutionary algorithm based on two basic concepts of education namely teaching phase and learning phase. The effectiveness of the proposed algorithm has been verified on test system with equality and inequality constraints. Compared with the other existing techniques demonstrates the superiority of the proposed algorithm.
{"title":"A Comparative Study of Improved Teaching Learning Based Optimization Technique on Economic Load Dispatch Problem with Generator Constraints","authors":"Sumit Banerjee, C. K. Chanda, D. Maity","doi":"10.4018/IJEOE.2016100101","DOIUrl":"https://doi.org/10.4018/IJEOE.2016100101","url":null,"abstract":"This article presents a novel improved teaching learning based optimization (I-TLBO) technique to solve economic load dispatch (ELD) problem of the thermal plant without considering transmission losses. The proposed methodology can take care of ELD problems considering practical nonlinearities such as ramp rate limit, prohibited operating zone and valve point loading. The objective of economic load dispatch is to determine the optimal power generation of the units to meet the load demand, such that the overall cost of generation is minimized, while satisfying different operational constraints. I-TLBO is a recently developed evolutionary algorithm based on two basic concepts of education namely teaching phase and learning phase. The effectiveness of the proposed algorithm has been verified on test system with equality and inequality constraints. Compared with the other existing techniques demonstrates the superiority of the proposed algorithm.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131669833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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