dc.contributor.author |
Kandasamy, Kalaiselvi |
|
dc.contributor.author |
Perumal, Renuga |
|
dc.contributor.author |
Velu, Suresh Kumar |
|
dc.date.accessioned |
2025-02-17T11:34:47Z |
|
dc.date.available |
2025-02-17T11:34:47Z |
|
dc.date.issued |
2018 |
|
dc.identifier.citation |
Kandasamy, Kalaiselvi; Perumal,Renuga; Velu,Suresh Kumar. ELM-ANFIS based controller for plug-in electric vehicle to grid integration. Timişoara: Editura Politehnica, 2018. |
en_US |
dc.identifier.issn |
1582-4594 |
|
dc.identifier.uri |
https://dspace.upt.ro/xmlui/handle/123456789/7180 |
|
dc.description.abstract |
In this paper, the authors propose adaptive
neuro fuzzy inference system (ANFIS) algorithm, based
on extreme learning machine (ELM) concepts for
designing a controller for electric vehicle to grid (V2G)
integration. First, learning speed and accuracy of the
proposed algorithm is checked and second the transient
response of the ELM-ANFIS (e-ANFIS) based controller
is analyzed. The proposed new learning technique
overcomes the slow learning speed of the conventional
ANFIS algorithm without sacrificing the generalization
capability. Thus, even with an involvement of a large
number of plug-in hybrid electric vehicles (PHEV), a
control technique for their charge and discharge pattern
can be easily designed. To study the computational
performance and transient response of the e-ANFIS
based controller, it is compared with conventional
ANFIS based controller. To implement the vehicle to
grid integration concept, IEEE 33 bus radial
distribution system is modelled in MATLAB
environment. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Timișoara : Editura Politehnica |
en_US |
dc.relation.ispartofseries |
Journal of Electrical Engineering;Vol 18 No 4 |
|
dc.subject |
Grid integration |
en_US |
dc.subject |
Electric vehicle |
en_US |
dc.subject |
Distribution system |
en_US |
dc.subject |
Extreme learning machine |
en_US |
dc.subject |
ANFIS |
en_US |
dc.title |
ELM-ANFIS based controller for plug-in electric vehicle to grid integration [articol] |
en_US |
dc.type |
Article |
en_US |