Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS
Managing procedure for charging and discharging battery system plays an essential contributor in improving the performance of energy storage system for example increment of utilizing batteries. This paper aims to develop a new hybrid genetic algorithm-based proportional integral (GA-based PI) contro...
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| Ngôn ngữ: | English |
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Springer
2022
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| Truy cập trực tuyến: | https://link.springer.com/chapter/10.1007/978-3-030-92574-1_15 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5895 https://doi.org/10.1007/978-3-030-92574-1_15 |
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oai:localhost:PNK-58952022-08-17T05:54:55Z Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS M. Elsisi Minh-Quang Tran Vu, Thi Lien Nguyen, Thi Thanh Nga ANFIS Genetic algorithm (GA) Managing procedure for charging and discharging battery system plays an essential contributor in improving the performance of energy storage system for example increment of utilizing batteries. This paper aims to develop a new hybrid genetic algorithm-based proportional integral (GA-based PI) controller with an adaptive neuro-fuzzy inference system (ANFIS) for the charging balance of batteries. The dataset is generated by using the GA-based PI controller, then a training strategy is introduced for the ANFIS controller. The proposed approach is evaluated by the GA-based PI controller and the PI controller based on Ziegler Nichols method. 2022-07-13T01:59:50Z 2022-07-13T01:59:50Z 2022 Bài trích https://link.springer.com/chapter/10.1007/978-3-030-92574-1_15 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5895 https://doi.org/10.1007/978-3-030-92574-1_15 en Springer |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
ANFIS Genetic algorithm (GA) |
| spellingShingle |
ANFIS Genetic algorithm (GA) M. Elsisi Minh-Quang Tran Vu, Thi Lien Nguyen, Thi Thanh Nga Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS |
| description |
Managing procedure for charging and discharging battery system plays an essential contributor in improving the performance of energy storage system for example increment of utilizing batteries. This paper aims to develop a new hybrid genetic algorithm-based proportional integral (GA-based PI) controller with an adaptive neuro-fuzzy inference system (ANFIS) for the charging balance of batteries. The dataset is generated by using the GA-based PI controller, then a training strategy is introduced for the ANFIS controller. The proposed approach is evaluated by the GA-based PI controller and the PI controller based on Ziegler Nichols method. |
| format |
Bài trích |
| author |
M. Elsisi Minh-Quang Tran Vu, Thi Lien Nguyen, Thi Thanh Nga |
| author_facet |
M. Elsisi Minh-Quang Tran Vu, Thi Lien Nguyen, Thi Thanh Nga |
| author_sort |
M. Elsisi |
| title |
Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS |
| title_short |
Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS |
| title_full |
Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS |
| title_fullStr |
Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS |
| title_full_unstemmed |
Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS |
| title_sort |
adaptive energy management in microgrid based on new training strategy for anfis |
| publisher |
Springer |
| publishDate |
2022 |
| url |
https://link.springer.com/chapter/10.1007/978-3-030-92574-1_15 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5895 https://doi.org/10.1007/978-3-030-92574-1_15 |
| _version_ |
1751856317371252736 |
| score |
8.881002 |