Banca de DEFESA: ARTHUR DINIZ FLOR TORQUATO FERNANDES

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : ARTHUR DINIZ FLOR TORQUATO FERNANDES
DATE: 22/09/2023
TIME: 14:00
LOCAL: Núcleo de Pesquisa e Inovação em Tecnologia da Informação - nPITI
TITLE:

Machine Learning Technics for the prediction of extreme overirradiance events

KEY WORDS:

 Machine Learning, Artificial Intelligence, Solar Energy, Overirradiance, Random Forest, Suport Vector Machine, MLP, LSTM.

PAGES: 71
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

The current dissertation is centered on the forecasting of Overirradiance within intervals of up to five minutes, achieved through the utilization of machine learning methodologies. Overirradiance, a phenomenon characterized by solar irradiance surpassing anticipated values under clear-sky conditions at the Earth's surface, has generated scholarly interest within the sphere of solar energy research and its implications for photovoltaic power generation systems. To date, no dedicated studies investigating the application of Machine Learning techniques for forecasting this phenomenon have been identified.

In pursuit of this aim, the performance of four distinct machine learning algorithms has been meticulously examined: Random Forest, Support Vector Machines (SVM), Multilayer Perceptron (MLP), and Long Short-Term Memory (LSTM) neural networks. The present study endeavors to bridge a lacuna in research by scrutinizing the feasibility and efficacy of these algorithms in predicting Overirradiance events, thereby augmenting the comprehension and pragmatic application of this phenomenon within solar energy systems.

COMMITTEE MEMBERS:
Presidente - 347628 - ADRIAO DUARTE DORIA NETO
Externo à Instituição - DANIEL LOPES MARTINS
Externo à Instituição - IGNACIO SANCHEZ GENDRIZ
Externa à Instituição - SAMIRA DE AZEVEDO SANTOS EMILIAVACA - CTGás