Banca de QUALIFICAÇÃO: CASIMIRO WAETE AGOSTINHO

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : CASIMIRO WAETE AGOSTINHO
DATE: 29/01/2025
TIME: 15:00
LOCAL: Sala virtual Google Meet
TITLE:

MPPT Optimization in Intelligent Photovoltaic Systems through Deep Learning

KEY WORDS:

MPPT, Deep Neural Networks, Energy Optimization, Sustainability

PAGES: 67
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUBÁREA: Sistemas Elétricos de Potência
SPECIALTY: Geração da Energia Elétrica
SUMMARY:

Photovoltaic (PV) systems are influenced not only by their non-linearity and complexity but also by dynamic environmental variables. As a result, Maximum Power Point Tracking (MPPT) techniques become crucial for optimizing the energy efficiency of these systems. This study is focused on the use of deep neural networks including RNN, LSTM, and GRU in increasing the effectiveness of MPPT strategies in the context of growing global demand for renewable energy which has fostered the system through a new application as a substitute solution to energy deficit. Although conventional MPPT methods are well known for their low complexity and ease of implementation, they are to the highest degree restricted considering environmental changes and efficiency. Conversely, deep learning architectures, especially LSTM and GRU, are well known for their capability to predict seasonal trends and solar radiation peaks, which are typical issues with photovoltaic systems. These neural networks are utilized to get better the accuracy of prediction of the most important meteorological variables like temperature, humidity, wind speed, and atmospheric pressure in order to make the systems work at their optimal point. The usage of advanced deep learning techniques to MPPT strategies increases the operational flexibility and precision of these. At the same time, it should be careful to note that these may raise the computational load during the training. On the other hand, over time, these models can be easily and efficiently executed. The connection of these technologies results in the main issue of the stability or the energy quality of the solar cells; this is a real technical progress in energy optimization and very useful for global sustainability goals.

COMMITTEE MEMBERS:
Presidente - 1451883 - FABIO MENEGHETTI UGULINO DE ARAUJO
Interno - 350693 - ANDRE LAURINDO MAITELLI
Interno - 1149567 - ANDRES ORTIZ SALAZAR
Externa à Instituição - MARIA IZABEL DA SILVA GUERRA - UFERSA
Externa à Instituição - ROMÊNIA GURGEL VIEIRA - UFERSA