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Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction

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dc.citedby41
dc.contributor.authorRoslan M.F.en_US
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorJern Ker P.en_US
dc.contributor.authorBegum R.A.en_US
dc.contributor.authorIndra Mahlia T.M.en_US
dc.contributor.authorDong Z.Y.en_US
dc.contributor.authorid57220188085en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid57222032755en_US
dc.contributor.authorid14007780000en_US
dc.contributor.authorid56997615100en_US
dc.contributor.authorid57221211074en_US
dc.date.accessioned2023-05-29T09:07:10Z
dc.date.available2023-05-29T09:07:10Z
dc.date.issued2021
dc.descriptionCarbon dioxide; Controllers; Cost effectiveness; Cost reduction; Emission control; Energy management systems; Energy resources; Learning algorithms; Operating costs; Power management; Cost saving; Distributed Energy Resources; Emission reduction; Energy; Management systems; Micro grid; Optimization algorithms; Optimized controllers; Scheduling controllers; Uncertainty; Scheduling; algorithm; carbon dioxide; energy resource; lightning; optimization; smart grid; Malaysia; Perlis; West Malaysiaen_US
dc.description.abstractThis study deals with the development of an optimal power scheduling controller for energy management of distributed energy resources in the microgrid system. The developed optimized controller is implemented using lightning search algorithm to overcome the uncertainties of microgrid energy management and to provide an optimum power delivery to loads with minimum cost. The primary objectives of the proposed optimized controller are to: (i) develop an optimized controller for microgrids energy management, (ii) minimize the total operating cost of the distributed energy resources units, (iii) reduce the environmental emission, and (iv) solve the complicated constraint optimization problems. The proposed optimization algorithm is implemented in the modified IEEE 14-bus test system to optimize the microgrid power management schedule. The optimized controller is executed based on the real load varying conditions recorded in Perlis, Malaysia. It is observed that the optimized controller successfully reduced the amount of power consumption from 971.65 MW to 364.3 MW which in turn saving cost of RM 265432.06. The proposed scheduling optimized controller performance is compared with the recent reported work of backtracking search algorithm optimization for validation. Result shows that the lightning search algorithm based MG controller produced a cost-effective system with 62.5% of cost saving and 61.98% of carbon dioxide emission reduction which is much higher compared to with MG and backtracking search algorithm based MG optimization, respectively. The effectiveness of the proposed approach outperformed other techniques in terms of minimum total operating cost of distributed energy resources and solving complicated constraints in optimization problems. � 2021 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.ArtNo116883
dc.identifier.doi10.1016/j.apenergy.2021.116883
dc.identifier.scopus2-s2.0-85103981904
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85103981904&doi=10.1016%2fj.apenergy.2021.116883&partnerID=40&md5=d8e16e7f5e2365ab374b31758556d375
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26146
dc.identifier.volume292
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleApplied Energy
dc.titleScheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reductionen_US
dc.typeArticleen_US
dspace.entity.typePublication
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