Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic technique
The elevated demand for electrical power, expeditious expenditure of fossil fuels, and degradation of the environment because of power generation have renewed attentiveness to renewable energy resources (RER). The rapid augmentation of RER increases the convolutions in leveling the demand and genera...
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AIMS Press
2022-08-01
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author | Sunimerjit Kaur Yadwinder Singh Brar Jaspreet Singh Dhillon |
author_facet | Sunimerjit Kaur Yadwinder Singh Brar Jaspreet Singh Dhillon |
author_sort | Sunimerjit Kaur |
collection | DOAJ |
description | The elevated demand for electrical power, expeditious expenditure of fossil fuels, and degradation of the environment because of power generation have renewed attentiveness to renewable energy resources (RER). The rapid augmentation of RER increases the convolutions in leveling the demand and generation of electrical power. In this paper, an elaborated α-constrained simplex method (ACSM) is recommended for multi-objective power dispatch problems. This methodology is devised after synthesizing the non-linear simplex method (SM) with the α-constrained method (ACM) and the evolutionary method (EM). ACSM can transfigure an optimization technique for the constrained problems by reinstating standard juxtapositions with α-level collations. The insertion of mutations and multi-simplexes can explore the periphery of the workable zone. It can also manage the fastness of convergence and therefore, the high precision solution can be obtained. A real-time multi-objective coordinated solar-wind-thermal power scheduling problem is framed. Two conflicting objectives (operating cost and emission) are satisfied. The case studies are carried out for Muppandal (Tamil Nadu), Jaisalmer (Rajasthan), and Okha (Gujarat), India. The annual solar and wind data are analyzed by using Normal Distribution and Weibull Distribution Density Factor, respectively. The presented technique is inspected on numerous archetype functions and systems. The results depict the prevalence of ACSM over particle swarm optimization (PSO), simplex method with mutations (SMM), SM, and EM. |
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spelling | doaj.art-b84e8fe77b724321b4c9e66047f5203d2022-12-22T03:55:16ZengAIMS PressAIMS Energy2333-83342022-08-0110494397110.3934/energy.2022043Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic techniqueSunimerjit Kaur0Yadwinder Singh Brar1Jaspreet Singh Dhillon21. Research Scholar, I.K. Gujral Punjab Technical University, Kapurthala 144603, Punjab, India2. vElectrical Engineering Department, I.K. Gujral Punjab Technical University, Kapurthala 144603, Punjab, India3. Electrical and Instrumentation Engineering Department, Sant Longowal Institute of Engineering and Technology, Sangrur 148106, Punjab, IndiaThe elevated demand for electrical power, expeditious expenditure of fossil fuels, and degradation of the environment because of power generation have renewed attentiveness to renewable energy resources (RER). The rapid augmentation of RER increases the convolutions in leveling the demand and generation of electrical power. In this paper, an elaborated α-constrained simplex method (ACSM) is recommended for multi-objective power dispatch problems. This methodology is devised after synthesizing the non-linear simplex method (SM) with the α-constrained method (ACM) and the evolutionary method (EM). ACSM can transfigure an optimization technique for the constrained problems by reinstating standard juxtapositions with α-level collations. The insertion of mutations and multi-simplexes can explore the periphery of the workable zone. It can also manage the fastness of convergence and therefore, the high precision solution can be obtained. A real-time multi-objective coordinated solar-wind-thermal power scheduling problem is framed. Two conflicting objectives (operating cost and emission) are satisfied. The case studies are carried out for Muppandal (Tamil Nadu), Jaisalmer (Rajasthan), and Okha (Gujarat), India. The annual solar and wind data are analyzed by using Normal Distribution and Weibull Distribution Density Factor, respectively. The presented technique is inspected on numerous archetype functions and systems. The results depict the prevalence of ACSM over particle swarm optimization (PSO), simplex method with mutations (SMM), SM, and EM.https://www.aimspress.com/article/doi/10.3934/energy.2022043?viewType=HTMLα-constrained simplex methodα-level comparisonsmulti-simplexesmutationsnormal distributionweibull distribution density factorfuzzy cardinal priority ranking |
spellingShingle | Sunimerjit Kaur Yadwinder Singh Brar Jaspreet Singh Dhillon Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic technique AIMS Energy α-constrained simplex method α-level comparisons multi-simplexes mutations normal distribution weibull distribution density factor fuzzy cardinal priority ranking |
title | Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic technique |
title_full | Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic technique |
title_fullStr | Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic technique |
title_full_unstemmed | Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic technique |
title_short | Multi-objective real-time integrated solar-wind-thermal power dispatch by using meta-heuristic technique |
title_sort | multi objective real time integrated solar wind thermal power dispatch by using meta heuristic technique |
topic | α-constrained simplex method α-level comparisons multi-simplexes mutations normal distribution weibull distribution density factor fuzzy cardinal priority ranking |
url | https://www.aimspress.com/article/doi/10.3934/energy.2022043?viewType=HTML |
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