Banca de DEFESA: RICARDO MOURA DE SOUZA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : RICARDO MOURA DE SOUZA
DATE: 27/02/2024
TIME: 08:30
LOCAL: Departamento de Engenharia Elétrica - sala 14 (Galpão)
TITLE:

POWER VARIABILITY IN PHOTOVOLTAIC GENERATION: SMOOTHING METHODS, METRICS, AND CHARACTERIZATION.

KEY WORDS:

Energy storage systems; renewable energy sources; power variability; intermittency; ramp rate.

PAGES: 69
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

Human-induced climate change, primarily caused by greenhouse gas emissions, poses a significant threat to the sustainability of life on Earth. To mitigate this problem, renewable energy sources (RESs), such as photovoltaic (PV) and wind generation, have gained substantial relevance as economically viable alternatives. Recent price drops in these technologies have accelerated their adoption as significant contributors to countries’ power grids. Although relatively clean, these alternatives are not free of negative impacts, particularly concerning their integration into power grids. Literature reports highlight issues such as voltage flickers, frequency deviations, and the need for larger power reserves, all stemming from the hard-to-anticipate nature of power variability. In the described scenario, this study addresses one of these impacts: the increase in power variability, with an emphasis on the use of energy storage systems in AC microgrids aimed at power smoothing. The literature review highlights works that tackle the issue of power variability, methods for generating reference signals for power smoothing, and the characterization of variability through probability density functions, providing theoretical support for the evaluation of current metrics and the proposal of alternatives. In this context, a set of experimental data from the NREL (National Renewable Energy Laboratory) is used, exposing the limitations of commonly used metrics to assess reference signal generation methods for power smoothing. Also, based on the data, an assessment of power variability characterization methods is conducted, employing a subset of the most common methods in the literature. Given the limitations found in this study, new metrics are developed, drawing on best practices from the field of Statistics.

COMMITTEE MEMBERS:
Externo à Instituição - FERNANDO APARECIDO DE ASSIS - UFSJ
Interno - 1237647 - JOSE FILHO DA COSTA CASTRO
Interno - 1882484 - JULIANO BANDEIRA LIMA
Presidente - 1146270 - RAFAEL CAVALCANTI NETO