The share of electricity generation from Variable Renewable Energy Sources (VRES) has increased over the last 20 years. Despite promoting the decarbonization of the energy mix, these sources bring negative characteristics to the energy mix, such as power ramps, load mismatch, unpredictability, and fluctuation. One of the ways to mitigate these characteristics is the hybridization of power plants. This paper evaluates the benefits of hybridizing a plant using an AI-based methodology for optimizing the wind–solar ratio based on the Brazilian regulatory system. For this study, the hybrid plant was modeled using data collected over a period of 10 months. The measurements were obtained using two wind profilers (LIDAR and SODAR) and a sun tracker (Solys 2) as part of the EOSOLAR R&D project conducted in the state of Maranhão, Brazil. After the power plant modeling, a Genetic Algorithm (GA) was used to determine the optimal wind–solar ratio, considering costs with transmission systems. The algorithm achieved a monthly profit increase of more than 39% with an energy curtailment inferior to 1%, which indicates economic complementarity. Later, the same methodology was also applied to verify the wind–solar ratio’s sensitivity to solar energy pricing. The results show that a price increase of 15% would change the power plant’s optimal configuration.

The EOSOLAR project was designed to investigate the structure of the atmospheric boundary layer in an equatorial coastal zone, where the discontinuity of surface conditions induces non-stationarity gradients of wind speeds and the development of internal boundary layers. The proposed methodology considers several aspects of the sea–land transition meteorology that are essential for precisely estimating wind–solar energy potential and assessment of structural loads on wind turbines. Infrared (LIDAR) and acoustic (SODAR) ground-based remote sensing instruments and micrometeorological towers were installed in a near-shore equatorial area of northeast Brazil, in order to provide a comprehensive view of meteorological processes. This paper reports a description of the project study area, methodology, and instrumentation used. Details of instruments configurations, a validation of micrometeorology towers, and a comparison between the LIDAR and SODAR are presented. Results of the first field campaign measuring the coastal flow, integrating the micrometeorological tower and LIDAR observations are described.

The objective of this work is to assess the wind resources of the east coast of Maranhão, Brazil. Wind profilers were combined with micrometeorological towers and atmospheric reanalysis to investigate micro- and mesoscale aspects of wind variability. Field campaigns recorded winds in the dry and wet seasons, under the influence of the Intertropical Convergence Zone. The dry season was characterized by strong winds (8 to 12 m s${}^{-1}$) from the northeast. Surface heat fluxes were generally positive (250 to 320 W m${}^{-2}$) at midday and negative (−10 to −20 W m${}^{-2}$) during the night. Convective profiles predominated near the beach, with strongly stable conditions rarely occurring before sunrise. Further inland, convective to strongly convective profiles occurred during the day, and neutral to strongly stable profiles at night. Wind speeds decreased during the rainy season (4 to 8 m s${}^{-1}$), with increasingly easterly and southeasterly components. Cloud cover and precipitation reduced midday heat fluxes (77 W m${}^{-2}$). Profiles were convective during midday and stable to strongly stable at night. Terrain roughness increased with distance from the ocean ranging from smooth surfaces ($z_o$ = 0.95 mm) and rough pastures ($z_o$ = 15.33 mm) to crops and bushes ($z_o$ = 52.68 mm), and trees and small buildings ($z_o$ = 246.46 mm) farther inland. Seasonal variations of the mean flow and sea and land breezes produced distinct diurnal patterns of wind speeds. The strongest (weakest) breeze amplitudes were observed in the dry (rainy) period. Daily changes in heat fluxes and fetch over land controlled the characteristics of wind profiles. During sea breezes, winds approached the coast at right angles, resulting in shorter fetches over land that maintained or enhanced oceanic convective conditions. During land breezes, winds blew from the mainland or with acute angles against the coastline, resulting in large fetches with nighttime surface cooling, generating strongly stable profiles. Coastal observations demonstrated that with increasing monopiles from 100 to 130 m it is possible to obtain similar capacity factors of beachfront turbines.

The Caatinga biome represents around 10% of the Brazilian territory, and it has an estimated population of 28 million inhabitants. Its tree-shrub vegetation, adapted to semi-arid conditions, plays a fundamental role in maintaining the hydrological balance, feeding the energy matrix, and generating revenues for Brazil. Despite its importance, the Caatinga is one of the most neglected biomes by the scientific community. Therefore, this review article aims to present elements that contribute to updating the state-of-the-art on the use of optical Earth observation data in the conservation of Caatinga vegetation, based on the identification of mapping initiatives at different scales that consider the biome. To this end, this study carried out a systematic bibliographic review in which the main focus was the characterization of orbital sensors, image classification techniques, land-use and land-cover classes, validation strategies, and the time interval defined by each mapping initiative. This detailed overview allowed us to assess the degree of usability and reliability of the existing products. Therefore, this study looks to open up possibilities to fill current scientific gaps that need further investigation regarding the role of optical Earth observation data in mapping the vegetation of the Caatinga and subsidizing resources for new initiatives, restoration actions, and hence the improvement of public policies favoring the conservation and sustainable use of the Caatinga’s resources.

This article seeks to compare the performance of a LIDAR Windcube V2, manufactured by Leosphere, with that of a SODAR MFAS, manufactured by Scintec, in evaluating wind speed at different altitudes. The data from these two sensors were collected at three locations on the Brazilian equatorial margin in the state of Maranhão. The comparison of these sensors aims at their simultaneous use at different points. The horizontal velocity components, by altitude, showed Pearson correlation values above 0.9 and values for the vertical velocity component between 0.7 and 0.85. As for the sampling efficiency, the LIDAR had a performance slightly higher than that of SODAR, especially at the point closest to the coast. In general, both sensors showed similar values, despite the differences in sampling methods. The results showed that the joint performance of these sensors had good correlation, being reliable for application in estimating wind potential for power generation in coastal areas of the equatorial region.