Research on feedback control of the intelligent grid-connected photovoltaic systems based on micro-inverters

DOI

10.2991/iccsae-15.2016.24How to use a DOI?

Keywords

grid-connected PV system, micro-inverter, acquisition controller, intelligent feedback control, self-diagnose, autonomous maintenance

Abstract

Recently, the grid-connected photovoltaics power stations are extensively installed. Nevertheless, to save the maintenance time, improve the safety performance, solve the complexities of traditional overhaul methods and eliminate restrictions further research is needed. Therefore, in this paper, a method of self-diagnose control for photovoltaic system connected grid based on micro-inverter was proposed. The smartPV software used to monitor the parameters of each module and the whole system. Subsequently, we develop a new software to self-diagnose the specific location of the fault or shadow. The feasibility and rationality of the self-diagnose method to the system state were verified by a simulation model and experiment. Results showed that this method can provide a number of functions: such as, the sub-system grouping contrast, the system self-started, found the specific position of the battery plate, divide the degree of the shielding, and protect the system and the system self-closed. In conclusion, this method makes the maintenance of the photovoltaic connected grid more safe and efficient. Moreover, it can be applied to on-line maintenance and autonomous maintenance for the household and the large scale grid-connected photovoltaics systems.

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/).

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TY  - CONF
AU  - Fangmei Wang
AU  - Rui Wang
AU  - Reda Hassanien Emam Hassanien
AU  - Ming Li
AU  - Ziyang Zhang
AU  - Jin Gao
PY  - 2016/02
DA  - 2016/02
TI  - Research on feedback control of the intelligent grid-connected photovoltaic systems based on micro-inverters
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 114
EP  - 122
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.24
DO  - 10.2991/iccsae-15.2016.24
ID  - Wang2016/02
ER  -