z-logo
open-access-imgOpen Access
Two-Stage Fault Diagnosis Method Based on the Extension Theory for PV Power Systems
Author(s) -
Menghui Wang,
Mu-Jia Chen
Publication year - 2012
Publication title -
international journal of photoenergy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.426
H-Index - 51
eISSN - 1687-529X
pISSN - 1110-662X
DOI - 10.1155/2012/892690
Subject(s) - troubleshooting , photovoltaic system , fault (geology) , computer science , reliability engineering , power (physics) , real time computing , electric power system , daylight , identification (biology) , electrical engineering , engineering , physics , optics , quantum mechanics , seismology , geology , operating system , botany , biology
In order to shorten the maintenance time and make sure of the photovoltaic (PV) power generation system steadily in operation, a fault diagnosis system for photovoltaic power generation system was proposed in this paper. First, a PSIM software is used to simulate a 2.2 kW PV system, it can take the operating date of the PV system under different sunlight intensity and temperature conditions. In this paper, a two-stage diagnosis system based on the extension theory for PV power systems is proposed; the proposed method is not only be able to troubleshoot the system fault but also the damaged module can also be located. The primary strategy is to utilize the diagnosis array of daylight identification and to use light scanning of the damage array at night. Via wireless network the data is transmitted back to the diagnosis system for identifying the location of damaged module. The time and energy of manually locating the fault module can be greatly saved. Finally, the methods as proposed in this paper have been compared with other existing methods, by which to verify its superiority and usability

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom