PPGENE PÓS-GRADUAÇÃO EM ENERGIA FUNDAÇÃO UNIVERSIDADE FEDERAL DO ABC Phone: Not available http://propg.ufabc.edu.br/ppgene

Banca de QUALIFICAÇÃO: VINICIUS DE LIRA TEIXEIRA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE : VINICIUS DE LIRA TEIXEIRA
DATA : 05/07/2022
HORA: 10:00
LOCAL: Sala 306 do Bloco B do Campus de Santo André da Universidade Federal do ABC
TÍTULO:

MODEL FOR THE POWER CURVE OF WIND GENERATORS FROM EXPERIMENTAL DATA


PÁGINAS: 99
GRANDE ÁREA: Outra
ÁREA: Multidisciplinar
RESUMO:

One of the fastest growing primary sources of renewable energy in Brazil and in the world is wind power. One of the challenges implicit in this type of energy conversion is the estimation of the energy generated during the lifetime of a wind farm, which depends both on the stochastic nature of wind speed and on the performance of the wind turbines. A tool that can be used to measure the performance of wind turbines is the power curve, which is generally provided by the manufacturer. However, the wind turbine power curve is affected by aging over the years or by its wear related to specific problems, such as malfunctions or controller configuration problems. In addition, the power curves can also be affected by characteristics related to atmospheric conditions such as the intensity of turbulence. The intensity of turbulence is a determining factor for the design of a wind turbine both from the point of view of efforts and from the point of view of the impact on the production of instantaneous electrical energy. Monitoring the temporal evolution of the power curve is important, as it can be used as information for predictive maintenance. This dissertation presents a new parametric model to determine the power curve based on data collected directly from the Supervisory Control and Data Acquisition (SCADA), for any turbulence index. The proposed parametric model is based on the behavior of the control curve in relation to the power curve, assuming that there are 6 different regions in the power curve, instead of the 4 characteristics of the most used models. The adopted regions are associated with the wind turbine control systems. The model was applied in three different wind farms installed in southern Brazil. The parameters of the proposed model were obtained by Genetic Algorithms. The resulting power curve of the proposed model is compared with the power curve normalized by IEC61400-12-1. The result of this comparison was considered satisfactory. Furthermore, the transitions between the 6 regions were compared with experimental data, with adequate results.


MEMBROS DA BANCA:
Presidente - Interno ao Programa - 1671344 - JULIO CARLOS TEIXEIRA
Membro Titular - Examinador(a) Interno ao Programa - 1544340 - PATRICIA TEIXEIRA LEITE ASANO
Membro Titular - Examinador(a) Externo à Instituição - ELIANE APARECIDA FARIA AMARAL FADIGAS - USP
Membro Suplente - Examinador(a) Interno ao Programa - 1671333 - EDMARCIO ANTONIO BELATI
Membro Suplente - Examinador(a) Interno ao Programa - 550.684.647-91 - JOAO MANOEL LOSADA MOREIRA - OUTRA
Membro Suplente - Examinador(a) Externo ao Programa - 2128150 - JOAO VICENTE AKWA
Notícia cadastrada em: 03/06/2022 08:49
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