Smart energy management systems for reliable solar microgrids
This research study addresses a significant limitation of conventional solar photovoltaic microgrids, that is, their inability to provide power during grid outages. Therefore, a smart energy management system is proposed to effectively control load demand and power supply, thereby reducing power los...
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my.utm.1076702024-09-25T07:47:42Z http://eprints.utm.my/107670/ Smart energy management systems for reliable solar microgrids Tajjour, Salwan Chandel, Shyam Singh Abdul Aziz, Mohd. Junaidi Malik, Hasmat TK Electrical engineering. Electronics Nuclear engineering This research study addresses a significant limitation of conventional solar photovoltaic microgrids, that is, their inability to provide power during grid outages. Therefore, a smart energy management system is proposed to effectively control load demand and power supply, thereby reducing power losses and enabling power supply during grid outages. The system encompasses two crucial stages. First, a Multi-Layer perceptron network is employed for accurate power production forecasting, followed by the utilization of a smart load demand management controller system, optimized using the Grey Wolf optimizer, to efficiently regulate load consumption. An experimental microgrid setup is established to assess the performance of the proposed system under real outdoor conditions. The experimental results on a typical sunny day indicate impressive system performance for supplying 100% of the load during the power cut off hours. This study contributes to the advancement of smart energy management solutions for conventional microgrid applications, aligning with sustainable development goals. 2023 Conference or Workshop Item PeerReviewed Tajjour, Salwan and Chandel, Shyam Singh and Abdul Aziz, Mohd. Junaidi and Malik, Hasmat (2023) Smart energy management systems for reliable solar microgrids. In: 2023 IEEE Conference on Energy Conversion (CENCON), 23 October 2023-24 October 2023, Kuching, Malaysia. http://dx.doi.org/10.1109/CENCON58932.2023.10369719 |
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TK Electrical engineering. Electronics Nuclear engineering Tajjour, Salwan Chandel, Shyam Singh Abdul Aziz, Mohd. Junaidi Malik, Hasmat Smart energy management systems for reliable solar microgrids |
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This research study addresses a significant limitation of conventional solar photovoltaic microgrids, that is, their inability to provide power during grid outages. Therefore, a smart energy management system is proposed to effectively control load demand and power supply, thereby reducing power losses and enabling power supply during grid outages. The system encompasses two crucial stages. First, a Multi-Layer perceptron network is employed for accurate power production forecasting, followed by the utilization of a smart load demand management controller system, optimized using the Grey Wolf optimizer, to efficiently regulate load consumption. An experimental microgrid setup is established to assess the performance of the proposed system under real outdoor conditions. The experimental results on a typical sunny day indicate impressive system performance for supplying 100% of the load during the power cut off hours. This study contributes to the advancement of smart energy management solutions for conventional microgrid applications, aligning with sustainable development goals. |
format |
Conference or Workshop Item |
author |
Tajjour, Salwan Chandel, Shyam Singh Abdul Aziz, Mohd. Junaidi Malik, Hasmat |
author_facet |
Tajjour, Salwan Chandel, Shyam Singh Abdul Aziz, Mohd. Junaidi Malik, Hasmat |
author_sort |
Tajjour, Salwan |
title |
Smart energy management systems for reliable solar microgrids |
title_short |
Smart energy management systems for reliable solar microgrids |
title_full |
Smart energy management systems for reliable solar microgrids |
title_fullStr |
Smart energy management systems for reliable solar microgrids |
title_full_unstemmed |
Smart energy management systems for reliable solar microgrids |
title_sort |
smart energy management systems for reliable solar microgrids |
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2023 |
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http://eprints.utm.my/107670/ http://dx.doi.org/10.1109/CENCON58932.2023.10369719 |
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