Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks
Controllers; Cost reduction; Electric load dispatching; Energy management; Microgrids; Neural networks; Control approach; Intelligent controllers; Microgrid; Multi micro-grids; Network-based; Performance; Power plant system; Scheduling control; System conditions; Virtual power plants; Scheduling
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my.uniten.dspace-259592023-05-29T17:05:47Z Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks Abdolrasol M.G.M. Hannan M.A. Suhail Hussain S.M. Ustun T.S. Sarker M.R. Ker P.J. 35796848700 7103014445 22035146400 43761679200 57537703000 37461740800 Controllers; Cost reduction; Electric load dispatching; Energy management; Microgrids; Neural networks; Control approach; Intelligent controllers; Microgrid; Multi micro-grids; Network-based; Performance; Power plant system; Scheduling control; System conditions; Virtual power plants; Scheduling This study uses an artificial neural network (ANN) as an intelligent controller for the management and scheduling of a number of microgrids (MGs) in virtual power plants (VPP). Two ANN-based scheduling control approaches are presented: the ANN-based backtracking search algorithm (ANN-BBSA) and ANN-based binary practical swarm optimization (ANN-BPSO) algo-rithm. Both algorithms provide the optimal schedule for every distribution generation (DG) to limit fuel consumption, reduce CO2 emission, and increase the system efficiency towards smart and economic VPP operation as well as grid decarbonization. Different test scenarios are executed to evaluate the controllers� robustness and performance under changing system conditions. The test cases are different load curves to evaluate the ANN�s performance on untrained data. The untrained and trained load models used are real-load parameter data recorders in northern parts of Malaysia. The test results are analyzed to investigate the performance of these controllers under varying power system conditions. Additionally, a comparative study is performed to compare their performances with other solutions available in the literature based on several parameters. Results show the superiority of the ANN-based controllers in terms of cost reduction and efficiency. � 2021 by the authors. Licensee MDPI, Basel, Switzerland. Final 2023-05-29T09:05:47Z 2023-05-29T09:05:47Z 2021 Article 10.3390/en14206507 2-s2.0-85117415327 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117415327&doi=10.3390%2fen14206507&partnerID=40&md5=6bb64f94db43fc6ea3a3275134058f92 https://irepository.uniten.edu.my/handle/123456789/25959 14 20 6507 All Open Access, Gold MDPI Scopus |
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description |
Controllers; Cost reduction; Electric load dispatching; Energy management; Microgrids; Neural networks; Control approach; Intelligent controllers; Microgrid; Multi micro-grids; Network-based; Performance; Power plant system; Scheduling control; System conditions; Virtual power plants; Scheduling |
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35796848700 |
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35796848700 Abdolrasol M.G.M. Hannan M.A. Suhail Hussain S.M. Ustun T.S. Sarker M.R. Ker P.J. |
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Abdolrasol M.G.M. Hannan M.A. Suhail Hussain S.M. Ustun T.S. Sarker M.R. Ker P.J. |
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Abdolrasol M.G.M. Hannan M.A. Suhail Hussain S.M. Ustun T.S. Sarker M.R. Ker P.J. Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks |
author_sort |
Abdolrasol M.G.M. |
title |
Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks |
title_short |
Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks |
title_full |
Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks |
title_fullStr |
Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks |
title_full_unstemmed |
Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks |
title_sort |
energy management scheduling for microgrids in the virtual power plant system using artificial neural networks |
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MDPI |
publishDate |
2023 |
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1806425897003122688 |