Banca de QUALIFICAÇÃO: ROMÊNIA GURGEL VIEIRA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : ROMÊNIA GURGEL VIEIRA
DATE: 08/12/2020
TIME: 09:00
LOCAL: Sala virtual Google Meet
TITLE:

Application of Artificial Intelligence Techniques for Fault Identification in Photovoltaic Modules

KEY WORDS:

Solar Energy; Photovoltaic Modules; PV Systems Faults; Artificial Intelligence.

PAGES: 104
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUBÁREA: Eletrônica Industrial, Sistemas e Controles Eletrônicos
SPECIALTY: Automação Eletrônica de Processos Elétricos e Industriais
SUMMARY:

Photovoltaic solar energy has proved to be a viable alternative that has contributed to sustainable development and guarantee energy supply around the world. The exponential growth in installed capacity in recent years has highlighted the need to ensure photovoltaic systems' safe and reliable operation. In this context, the occurrence of faults in such systems is crucial since they can significantly impact the power generated, shorten the lifetime, and cause potential risks in operation. Thus, this research proposes applying artificial intelligence techniques for detecting and diagnosing faults in photovoltaic panels. Initially, concepts related to photovoltaic panels are addressed and the types of faults that occur in these devices. The methodology used in the development of the research is described, dealing with the modeling and simulation developed, and the description of the methods for detecting faults together with the machine learning algorithms applied. The preliminary results obtained are presented and analyzed, and the next stages of the research are discussed.

BANKING MEMBERS:
Presidente - 1451883 - FABIO MENEGHETTI UGULINO DE ARAUJO
Interno - 1149567 - ANDRES ORTIZ SALAZAR
Interno - 350693 - ANDRÉ LAURINDO MAITELLI
Externo à Instituição - JOÃO TEIXEIRA DE CARVALHO NETO - IFRN
Externo à Instituição - MARCELO ROBERTO BASTOS GUERRA VALE - UFERSA