Item Infomation
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Elsisi, M. | - |
dc.contributor.author | Minh, Quang Tran | - |
dc.contributor.author | Vu, Thi Lien | - |
dc.contributor.author | Nguyen, Thi Thanh Nga | - |
dc.date.accessioned | 2022-05-05T07:26:18Z | - |
dc.date.available | 2022-05-05T07:26:18Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | https://link.springer.com/chapter/10.1007/978-3-030-92574-1_15 | - |
dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/5753 | - |
dc.description.abstract | 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 | vi |
dc.language.iso | en | vi |
dc.publisher | Springer | vi |
dc.subject | ANFIS | - |
dc.subject | Genetic algorithm (GA) | |
dc.title | Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS | vi |
dc.type | Bài trích | vi |
eperson.identifier.doi | https://doi.org/10.1007/978-3-030-92574-1_15 | - |
Appears in Collections | ||
Bài báo khoa học |
Files in This Item:
There are no files associated with this item.