The BP network Design of MPPT with Photovoltaic Power System

DOI

10.2991/itoec-16.2016.69How to use a DOI?

Keywords

photovoltaic power system; BP neural; network; MPPT; algorithm

Abstract

Photovoltaic power system has bigger time-vary nature, so it is difficult to build accurate mathematic model. BP neural network has the capability of expression nonlinearity and also has the self study and adaptive function BP neural network control makes full use of neural network approximation capability, and with better control in resolving the highly nonlinear seriously uncertain systems. Simulated result indicates this control is able to make system reach satisfied control effect, accurately track the maximum power point of PV cells. 1

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Huaizhong Chen
AU  - Xiaoliang Wu
AU  - Tao Jin
PY  - 2016/05
DA  - 2016/05
TI  - The BP network Design of MPPT with Photovoltaic Power System
BT  - Proceedings of the 2nd Information Technology and Mechatronics Engineering Conference (ITOEC 2016)
PB  - Atlantis Press
SP  - 365
EP  - 368
SN  - 2352-5401
UR  - https://doi.org/10.2991/itoec-16.2016.69
DO  - 10.2991/itoec-16.2016.69
ID  - Chen2016/05
ER  -