Banca de DEFESA: GRACE ANNE SANTOS LIMA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : GRACE ANNE SANTOS LIMA
DATE: 24/04/2023
TIME: 15:00
LOCAL: Videoconferência
TITLE:

Solar Irradiation Forecast Using Time Series Models

KEY WORDS:

Solar irradiance forecast; time series.

PAGES: 53
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUBÁREA: Sistemas Elétricos de Potência
SPECIALTY: Geração da Energia Elétrica
SUMMARY:

This dissertation presents a methodology for predicting solar irradiance data using short-term
time series models (72-hour horizon), with hourly discretization, for a photovoltaic park located
in Jequié-BA. This tool will help to integrate photovoltaic technology into the electrical system,
as it will help the grid operator in the tasks of energy dispatch planning, contracting auxiliary
and reserve services, managing maintenance actions and grid congestion, and general management
of the park. The model proposed in this dissertation uses Box and Jenkins modeling, an
iterative procedure that fits Auto-Regressive Integrated Moving Averages (ARIMA) models to a
data set. The Auto-Regressive (AR) and Periodic Auto-Regressive (PAR) models were considered
as forecasting methods, whose parameters were adjusted based on hourly measurements
of irradiance, carried out over a period of one year. In order to compare the performance of the
AR and PAR models in predicting hourly values of solar irradiance, tests were carried out considering
variations in the order of these models. The forecasts of days with different luminosity
characteristics were also evaluated. Regarding the order of the models, tests were initially carried
out considering AR and PAR models of order 1 (AR(1) and PAR(1), respectively). In this
case, the adjustment of the model parameters takes into account that the prediction of irradiance
in a given hour depends only on the occurrence of irradiance in the previous hour. It should be
noted that, for the PAR (1) model, 24 parameters were adjusted, that is, an order 1 model for
each hour of the day. Tests were also performed using the AR model of order p and the PAR
model of order pm. In the case of the PAR(pm) model, the model order varies according to the
forecast time. The performance of the considered forecasting methods was evaluated through
error analysis.

COMMITTEE MEMBERS:
Presidente - 1484412 - FERNANDO AUGUSTO MOREIRA
Interno - 1666309 - FABIANO FRAGOSO COSTA
Externo à Instituição - DURVAL DE ALMEIDA SOUZA - IFBA