Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling
Electromagnetic wave emission; Meteorology; Microgrids; Particle swarm optimization (PSO); Scheduling; Solar energy; Solar power generation; Wind; Battery status; BPSO algorithms; Learning rates; Optimal energy; Optimal values; Solar irradiation; Sustainable resources; Virtual power plants (VPP); Ne...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-259402023-05-29T17:05:40Z Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling Abdolrasol M. Mohamed R. Hannan M. Al-Shetwi A. Mansor M. Blaabjerg F. 35796848700 7005169066 7103014445 57004922700 6701749037 7004992352 Electromagnetic wave emission; Meteorology; Microgrids; Particle swarm optimization (PSO); Scheduling; Solar energy; Solar power generation; Wind; Battery status; BPSO algorithms; Learning rates; Optimal energy; Optimal values; Solar irradiation; Sustainable resources; Virtual power plants (VPP); Neural networks This letter proposes an enhancement for artificial neural network (ANN) using particle swarm optimization (PSO) to manage renewable energy resources (RESs) in a virtual power plant (VPP) system. This letter highlights the comparison of the ANN-based binary particle swarm optimization (BPSO) algorithm with the original BPSO algorithm. The comparison has been made upon searching the optimal value of the number of nodes in the hidden layers and the learning rate. These parameter values are used in ANN training for microgrid (MG) optimal energy scheduling. The proposed approach has been tested in the VPP system covering MGs involving RESs to minimize the power and giving priority to sustainable resources to participate instead of buying power from the utility grid. This model is tested using real load demand recorded for 24 h in Perlis state, the northern part of Malaysia. Besides, real weather condition data are recorded by Tenaga Nasional Berhad Research solar energy meteorology for a 1-h average (e.g., solar irradiation, wind speed, battery status data, and fuel level). The results show that ANN-PSO gives precise decision compared with BPSO algorithm, which in turn prove that the enhancement for the neural net reaches the optimum level of energy scheduling. � 1986-2012 IEEE. Final 2023-05-29T09:05:39Z 2023-05-29T09:05:39Z 2021 Article 10.1109/TPEL.2021.3074964 2-s2.0-85104625333 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104625333&doi=10.1109%2fTPEL.2021.3074964&partnerID=40&md5=2b686c8ae86b94cb5c4b3df074b9e455 https://irepository.uniten.edu.my/handle/123456789/25940 36 11 9411682 12151 12157 All Open Access, Green Institute of Electrical and Electronics Engineers Inc. Scopus |
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| description |
Electromagnetic wave emission; Meteorology; Microgrids; Particle swarm optimization (PSO); Scheduling; Solar energy; Solar power generation; Wind; Battery status; BPSO algorithms; Learning rates; Optimal energy; Optimal values; Solar irradiation; Sustainable resources; Virtual power plants (VPP); Neural networks |
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35796848700 |
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35796848700 Abdolrasol M. Mohamed R. Hannan M. Al-Shetwi A. Mansor M. Blaabjerg F. |
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Article |
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Abdolrasol M. Mohamed R. Hannan M. Al-Shetwi A. Mansor M. Blaabjerg F. |
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Abdolrasol M. Mohamed R. Hannan M. Al-Shetwi A. Mansor M. Blaabjerg F. Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling |
| author_sort |
Abdolrasol M. |
| title |
Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling |
| title_short |
Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling |
| title_full |
Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling |
| title_fullStr |
Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling |
| title_full_unstemmed |
Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling |
| title_sort |
artificial neural network based particle swarm optimization for microgrid optimal energy scheduling |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806428300054102016 |
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13.214268 |