Name: Noéle Bissoli Perini de Souza
Type: PhD thesis
Publication date: 03/11/2021

Namesort descending Role
Davidson Martins Moreira Advisor *

Examining board:

Namesort descending Role
Alex Álisson Bandeira Santos External Examiner *
Bruno Furieri Internal Examiner *
Davidson Martins Moreira Advisor *
Erick Giovani Sperandio Nascimento Co advisor *
Gisele de Lorena Diniz Chaves Internal Examiner *
José Vicente Cardoso Santos External Examiner *
Marcelo Romero de Moraes External Examiner *

Summary: This work has as main objective the elaboration of an onshore and offshore wind map
of the state of Bahia using the WRF mesoscale model with a spatial resolution of 3 km
and a time period of 5 years (2015-2020). Initially, to evaluate the best physical
parameterizations in the model, simulations were performed with a spatial resolution
of 1 km to compare with observational data of approximately one year obtained in
towers equipped with anemometers at heights of 80, 100, 120 and 150 m, strategically
positioned in three locations far apart in the state of Bahia (Esplanada, Mucuri and
Mucugê). The combination of PBL-YSU and LSM-RUC regimens showed the best
results. After this analysis, velocity field simulations were carried out for a period of 5
years and the results compared with surface data from 41 automatic anemometric
stations covering the state of Bahia and one located in the Abrolhos Archipelago. The
results showed that the winter period presents higher mean values of wind speed for
the onshore region (9 to 14 m/s), and the northern and southwestern regions of the
state stand out for the generation of wind energy. In the offshore case, spring presents
the highest averages for wind speed (7 to 8 m/s), followed by the summer season,
highlighting the maritime coast in the extreme south of the state (7 to 10 m/s). The
nocturnal wind regime is more intense than the daytime one, indicating a great
complementarity with solar energy. It should be noted that the year 2017 had the
highest average values of wind speed in the region, being considered one of the
warmest years without the influence of the El Niño phenomenon recorded globally
since the year 1850. In addition, the DFA (Detrended Fluctuation Analysis) technique
was used to analyze the scale behavior of the data measured at the stations and in the
numerical simulations. Most regions showed persistent behavior for wind speed,
especially those in which, in addition to high values in average wind speeds, they
obtained high self-similarity exponent values within the range of persistent long-range
correlations, characterized as excellent locations in terms of high values of energy and
wind persistence.

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