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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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Main Authors: M. Elsisi, Minh-Quang Tran, Vu, Thi Lien, Nguyen, Thi Thanh Nga
Format: Bài trích
Language:English
Published: Springer 2022
Subjects:
ANFIS
Genetic algorithm (GA)
Online Access: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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spelling 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 8.891145

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