Treffer: Implementation of supervisory controller for solar PV microgrid system using adaptive neural model

Title:
Implementation of supervisory controller for solar PV microgrid system using adaptive neural model
Authors:
Source:
Electrical power & energy systems. 63:1023-1029
Publisher Information:
Oxford: Elsevier, 2014.
Publication Year:
2014
Physical Description:
print, 23 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
FEEE, DCSELAB, Ho Chi Minh City University of Technology, VNU-HCM, Viet Nam
ISSN:
0142-0615
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Electrical engineering. Electroenergetics
Accession Number:
edscal.28711498
Database:
PASCAL Archive

Weitere Informationen

This paper investigates a novel forward adaptive neural model which is applied for modeling and implementing of the supervisory controller of the solar PV microgrid system. The nonlinear features of the solar PV microgrid system were thoroughly modeled based on the adaptive identification process using experimental input-output training data. This paper proposes the novel use of a back propagation (BP) algorithm to generate the adaptive neural-based supervisory controller for the solar PV microgrid system. The simulation results show that the proposed adaptive neural-based supervisory controller trained by Back Propagation learning algorithm yields outstanding performance and perfect accuracy.