RESEARCH AND DEVELOPMENT

The project aims to integrate databases and map solar resources for South America (SA) through joint collaboration between research groups with proven experience in assessing incident solar radiation at the surface. This proposal includes Brazilian researchers (UNIFESP, INPE, UNIFEI, UFAL), and researchers from Uruguay (Universidad de la Republica UDELAR), Chile (Pontifícia Universidad Católica de Chile PUV-Chile), and Spain (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas CIEMAT). Solar resource mapping is a fundamental tool for promoting knowledge about this energy resource and is available with low uncertainty results for large areas of the globe. However, international databases present unknown uncertainty values for almost all of SA due to the small number of solarimetric stations used to assess the deviations presented by estimates of incident solar irradiance at the surface. This project proposes a collaborative effort to integrate surface-observed databases and to improve methodologies for estimating incident solar irradiation on the surface of the South American continent. This is based on the intercomparison between models developed specifically to simulate radiative processes in the atmosphere, considering the specificities found in South America, such as biomass burning events with transport of aerosols released into the atmosphere over large distances, densely populated urban centers, high altitudes in the Andes Mountains, the presence of deserts and arid regions, the transition between dry and rainy seasons in the center-west and north of Brazil, and the differentiated climatic regimes around large water reservoirs for multiple uses, including hydroelectric generation. Published studies demonstrate the ability to produce results with lower uncertainties than those presented by the international databases currently available. Throughout the implementation of the proposal, a series of actions will be carried out to bring together research groups from other South American countries and promote discussion on energy issues and their relationship to climate through workshops and forums for young researchers. The expected results will have an impact on all South American countries, considering the experience already gained in Brazil, Chile, and Uruguay, which are more advanced based on the literature review. Furthermore, the integration of efforts should contribute to a greater reduction in uncertainty in the models currently used in these three countries and will expand the coverage of information on the spatial and temporal variability of solar resources in South America. This context will provide the conditions for future research projects in various areas of knowledge and support planning and public policy development aimed at reducing the energy sector's climate vulnerabilities in line with the 2030 Agenda, particularly SDG 7 and SDG 13.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Enio Bueno Pereira, Arcilan Trevenzoli Assireu, Rodrigo A. Escobar, André Luiz Vizine Pereira, Rodrigo Santos Costa, André Rodrigues Gonçalves, Rosiberto Salustiano da Silva Junior, Rodrigo Alonso-Suárez, Rita Ximena Valenzuela Balderrama, Luis F. Z. Tirado, Agustin Laguarda, Francisco Ferreira Cobos

Funder:  

The project is underway.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Enio Bueno Pereira, André Rodrigues Gonçalves, Rodrigo Santos Costa, Alvaro Luiz Gayoso de Azeredo Coutinho, Antonio Andre Novotny, Argemiro Resende Secchi, Doris Regina Aires Veleda, Fernando Alves Rochinha, Frederic Gerard Christian Valentin, Gerson Zaverucha, Suzana Kahn Ribeiro, Olga de Castro Vilela, Segen Farid Estefen, Alexandre Carlos Araújo da Costa

Funder: Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The SOLTER project (https://labren.ccst.inpe.br/solter/) aims to develop diffusion bonding techniques for the construction of efficient, low-cost solar energy accumulators for use in small electric generators, in which phase-change materials attenuate the variations in solar energy typical of Brazil. The LABTUCAL/UFSC team has extensive previous knowledge in the development of solar receivers, compact heat exchangers and the diffusion bonding of special steels and alloys for a wide variety of applications. On the other hand, LABREN/INPE has accumulated decades of data on solar irradiation in Brazil, which is influenced by region and cloud variation. This project allows efforts in these areas to be directed towards the development of a full-scale prototype.

Coordinators: Marcia B. H. Mantelli (LABTUCAL/UFSC) / Rodrigo Santos Costa (LABREN/INPE)

Funder: FINEP

The project aims to develop methods to quantify solar potential in flooded areas and estimate the generation potential of UFFs in reservoirs of Brazilian hydroelectric plants. To this end, a new method for estimating cloud cover over flooded areas will be implemented in the BRASIL-SR model, which considers the satellite-Earth-sun geometry in calculating reflectance functions from visible channel images from the GOES16 satellite.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Enio Bueno Pereira, Alexandre Araujo dos Santos, Gilberto Fernando Fisch, Cledson Akio Sakurai, Marcelo Pizzuti Pes, Gerson Maximo Tiepolo, Madeleine Sánches Gácita Casagrande, Francisco José Lopes de Lima, Rodrigo Santos Costa, André Rodrigues Gonçalves, Ricardo da Silva Benedito, Edson Ricardo Calado Sabino, Manoel Henriques de Sá Campos Filho, Ruy Morgado de Castro

Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

This project will provide Brazil with a laboratory for testing and developing instrumental arrangements, equipment, methodologies, and structures for prospecting offshore wind potential. The National Laboratory for Micrometeorological and Methodological Studies Applied to Offshore Energy Use (LabWind) aims to be an advanced environmental laboratory for testing concepts, methods, and instruments relevant to offshore wind energy, in an easily accessible location that reproduces wind, wave, and wind-generated current fields at sufficient intervals to ensure preliminary testing and adjustments before such procedures, methods, instruments, and platforms can be deployed in the harsh and cost-intensive operating conditions typical of the offshore environment.

Coordinator: Arcilan Trevenzoli Assireu

Participants: Fernando Ramos Martins, Felipe Mendonça Pimenta, Enio Bueno Pereira, Gilberto Fernando Fisch, Rodrigo Santos Costa, André Rodrigues Gonçalves, Ramon Moraes de Freitas, Vinícius Siqueira Oliveira Carvalho, José Antônio Aravéquia, Shigeaki Leite de Lima

Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Coordinator: André Rodrigues Gonçalves, Rodrigo Santos Costa

Funder: ---

Project funded by GIZ with the aim of promoting integration and interaction between Latin American institutions involved in the acquisition of solarimetric and meteorological data applied to the energy sector.

Coordinator: Juan Steve Carceres Pacheco

Participants: Fernando Ramos Martins, Enio Bueno Pereira, Roberto Zilles, André Rodrigues Gonçalves, Rodrigo Santos Costa, Rodrigo Alonso-Suárez, Rosana Aristegui, Patricia Echeverria, Gilberto Figueiredo, Anahi Lanson

Funder: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH / Kreditanstalt fur Wiederaufbau

The project is ongoing.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Madeleine Sánches Gácita Casagrande, Francisco José Lopes de Lima

Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Cerrado and Caatinga biomes contain the largest stocks of land available for agricultural expansion in Brazil, in addition to possessing areas of high solar and wind potential. Their natural resources are essential for climate regulation and human well-being. The overall objective of this proposal is to propose strategies for transitioning to a sustainable future in these two biomes through a participatory approach that integrates qualitative and quantitative methods from the natural and social sciences at multiple scales. This approach involves defining scenarios and indicators that reconcile the economic, social, and environmental dimensions (the three pillars of sustainability) in agricultural production, energy, and natural resource use. The project is organized into phases with specific objectives. Phase 1 consists of producing indicators on the social, economic, institutional, and environmental dimensions of the study area, aiming to develop sustainability indices that reflect the current situation (past and present) in line with national demands. Phase 2 focuses on the future of the study area through the development of qualitative and quantitative scenarios, developed in a participatory manner. Elements of future stories will be quantified, generating spatially explicit projections of land use change, regional climate, and their impacts (translated into a comprehensive set of socio-environmental indicators, including water resources, vegetation, biodiversity, agriculture, energy, atmospheric lightning, biogeochemical cycles, among others). Finally, Stage 3 encompasses cross-scale synthesis activities, as well as analysis of social transformation mechanisms aimed at achieving sustainability (trajectories).

Coordinator: Jean Pierre Henry Balbaud Ometto

Participants: Fernando Ramos Martins, Felipe Siqueira Pacheco, Plínio Carlos Alvalá, Rodrigo Santos Costa, André Rodrigues Gonçalves, Evandro Albiach Branco, Gustavo Felipe Balué Arcoverde, Camille Lanzarotti Nolasco, Luciana de Souza Soler, João Arthur Pompeu Pavanelli, Laura de Simone Borma, Lincoln Muniz Alves, Angelica Giarolla, Flávio de Carvalho Magina, Francisco Gilney Silva Bezerra, Gilvan Sampaio de Oliveira, Guillermo Oswaldo Obregón Párraga, Jorge Alberto Bustamante, Luciano Marani, Marcos Barbosa Sanches, Maria Cristina Forti, Manoel Ferreira Cardoso, Viviane Regina Algarve

Funder: Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The main objective of this study was to enable the evaluation and characterization of the temporal variability of the cloud cover and its influence on the solar resource incident on the surface, important information for projects of energy generation systems that use solar technology. In order to do so, a methodology was developed to estimate the frequency of occurrence of each cloud thickness value for any point in the Brazilian territory from satellite images, generating clouds frequency statistics, translated in the form of specific indexes. These regional maps are useful to evaluate the impact that the cloudiness can cause on different heliothermic plants, due to the specific thermal inertia of each plant, or even to the energy transmission network, since it will allow to infer the expected transient spectrum for each region.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

The prediction of the availability of solar irradiation is of paramount importance for photovoltaic and heliothermic generating plants, since they are dependent on meteorological factors. The scale considered in the forecasts can range from minutes to days. The aim of this study was the development and integration of a hybrid solar irradiation prediction system through the combination of different methodologies. Forecasting methods were developed by sky imaging cameras installed on the ground for a 30-minute horizon through the projection of cloud motion. On the horizon of 1 to 6 hours, satellite images were used to obtain future cloud fields and, consequently, solar irradiance forecasts through radiative transfer models. Finally, it was used mesoscale meteorological modeling adjusted by artificial neural networks to provide forecasts in the horizon from 12 to 72 hours. The results were validated in a pilot heliothermic plant developed by INPE partner institutions. It is expected that the results bring a gain of predictability of solar generation in the country, reducing risks and bringing security to the insertion of solar generation in the national interconnected system.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

A consortium of more than 200 scientists from 38 research groups from 15 Brazilian states, with the support of 12 institutions from 11 countries, is involved in the 2nd INCT-Climatic Changes Project (INCT-MC). This new project is a continuation of the previous INCT-MC (2009 to 2014) and is based on the scientific and technological results obtained by it, where the following studies were approached and developed: scientific basis of global environmental changes; impacts, adaptation, vulnerability; mitigation and technological innovation efforts in climate system models, geo-sensors and the natural disaster prevention system. More information on the previous INCT-MC can be obtained at: http://inct.ccst.inpe.br/. In this continuation of INCT-MC will be applied the main scientific results of the previous INCT. Among them we can mention the great scientific contribution to the reports of the IPCC AR5 and the PBMC and also the scientific reinforcement of the CLIMA Network. The previous INCT-MC showed, among other things, that rain extremes (similar to those that caused floods and landslides in the Rio de Janeiro mountainous region in January 2011) have been more frequent and intense since 1950, generating vulnerability in areas of high population density in Southeast Brazil. This vulnerability may increase in the future if disaster risk reduction measures are not created and implemented.

Coordinator: Tercio Ambrizzi

Funders: National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Foundation for Research Support of the State of São Paulo (FAPESP)

Complementary project to the NoPa Project in partnership with Libiniz Universität Hannover funded by DAAD/GIZ for the involvement of undergraduate students from the Instituto do Mar, UNIFESP, Baixada Santista campus.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Wellington Winícius Ferreira Fonseca, Marcelo Pizzuti Pes, Tobias Emanuel Portis

Funders: Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Marcelo Pizzuti Pes, Eduardo Weide Luiz, Rodrigo Santos Costa, Francisco José Lopes de Lima, Gunther Seckmeyer

Funder: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

As energy from the Sun participates in several atmospheric processes, the mesoscale models for weather forecast estimate the solar radiation incident on the surface. These estimates find applications in agriculture, architecture and energy sector. In the energy sector, short-term solar radiation forecasts can be employed in the generation activities (operation of hybrid systems that use solar energy) and the distribution of electrical energy (prediction of load dispatch in transmission lines). The description of most atmospheric phenomena by means of differential equations involves uncertainties caused by modeling methods. A strategy to deal with uncertainty in numeric prediction models is to apply an Model Output Statistical (MOS), powered by the data produced by the numerical models. MOS methodology is a refinement technique that consists of determining a statistical relationship between a predictor and variables predicted by a numerical model in different forecast horizons. The use of this technique has been presented as fundamental in the operational practice of the numerical prediction. The proposed project has the goal of developing high resolution modeling methodology using the WRF (Weather Research and Forecasting) model for estimating and predicting solar irradiation on the surface considering the climate and environmental characteristics found in Brazilian territory, adopting methods of artificial intelligence as a technique of statistical refinement and reduction of uncertainty of estimates and forecasts.

Coordinator: Fernando Ramos Martins (UNIFESP)

Funder: National Council for Scientific and Technological Development (CNPq)

Scientific initiation with the purpose of studying the optical thickness of aerosols in cities on the coast of Southeast Brazil (Rio de Janeiro and Santos) based on data from MODIS products and surface observations from the AERONET network.

Coordenadora: Madeleine Sánches Gácita Casagrande

Participants: Fernando Ramos Martins, Giovanna Bonafé Maurício

Funder: Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Coordinator: Fernando Ramos Martins (UNIFESP)

Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The knowledge of the variability of energy resources as a function of climatic variability is relevant not only for the energy planning of the country, but also for the evaluation of the economic viability and technical detailing of projects and investments in production and insertion of these renewable sources into the electricity distribution system. The studies of economic viability and energy planning should take into account the climatic and environmental impacts of short, medium and long-term, such as increased or reduced precipitation, increased frequency of storms or changes in the coverage of the Soil, etc. As an example, the increase in the speed of winds above the tolerance values specified in the project of a wind farm can prevent the production of energy due to the risks of damage to the mechanical system of the installed generators. As a result, there may be economic and technical losses if this increase is not foreseen in the development of the project.

Coordinator: Fernando Ramos Martins (UNIFESP)

Funder: National Council for Scientific and Technological Development (CNPq)

This project aims to present a proposal for attracting a Young Talent currently pursuing a research career at a Japanese research institution in the area of numerical modeling applied to surface solar irradiance forecasting and photovoltaic generation. The Young Talent has been developing high-quality work that has yielded significant results, leading to publications in high-impact international journals.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Enio Bueno Pereira, Ana Paula Cruz de Sousa

Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

With the environmental impacts of water sources and fossil fuels, concerns about the depletion of these resources have increased the demand for alternative energy sources, especially renewable ones. The project aims to characterize the wind potential of the state of São Paulo, study the annual and seasonal behavior of the wind regime at the automatic meteorological stations of the National Institute of Meteorology (INMET), and compare them with data from the Wind Atlas of the State of São Paulo provided by the Subsecretariat of Renewable Energy of the State of São Paulo. The project also aims to develop numerical modeling methodologies to assess the energy potential available within the state. Studies are being initiated to assess the social impact of this energy resource in regions with lower human development.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Lucía Iracema Chipponelli Pinto, Henrique Cardoso Köpke de Vasconcellos Machado, Rafael Garcia, Eduardo Pádua Machado, Marcel Albertini Toledo de Paula, Maryana Ishi Mello

Funder:  

Project completed.

Coordinator: Fernando Ramos Martins (UNIFESP)

Participants: Luiz Eduardo Weide, Alice dos Santos Macedo, Ana Paula Cruz de Sousa, Jessika Carolina Biancamano Faria

Funder:  

Development of models for solar radiation transference in the atmosphere adapted to the climate characteristics and specific seasonal environmental conditions of the various Brazilian mesoclimatic regions, combining satellite data with surface data for the generation of synthetic series of global, direct, direct normal and diffuse solar radiation at the level of the earth's surface with less uncertainty.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

This project aimed to consolidate the investigation of the potential of wind power in hydroelectric reservoirs in view of the current scenario and future scenarios projected by the IPCC, facing the influence of climate change. This pilot study was carried out for four important hydroelectric reservoirs in the state of Minas Gerais: Furnas, Três Marias, Itumbiara (border of Minas Gerais and Goiás) and Estreito (border of Minas Gerais and São Paulo).

Coordinator: Arcilan Treviseu (UNIFEI)

Funder: Foundation for Research Support of the State of Minas Gerais (FAPEMIG)

The main objective of the project was to establish a long-term partnership between the LABREN / DIIAV / INPE and the Energy Meteorology group of the University of Oldenburg (EnMetol), Germany, for the development of methods and meteorological tools specifically applied to the demands of the energy sector regarding the spatial and temporal variability of the energy potential of solar and wind sources. The results and products generated by this partnership will contribute to boost the insertion of solar and wind renewable sources in the energy matrix. Within the scope of this project, part of the CAPES NoPa program, emphasis was placed on the qualification and training of human resources through the exchange of researchers and doctoral students, establishment of a joint agenda of research activities and development of methods and tools for services to the energy sector.

Coordinator: Enio Bueno Pereira

Funder: Coordination of Improvement of Higher Level Personnel (CAPES)

The project has estimated the impacts of future climate changes due to global warming on Brazil's solar and wind energy potentials for the periods 2010-2040, 2040-2070 and 2070-2100. The project also aimed to provide predictions of these impacts for three scenarios of greenhouse gas emissions: A2, B2 and A1B, according to the classification presented in IPCC reports.

Coordinator: Fernando Ramos Martins (UNIFESP)

Funder: National Council for Scientific and Technological Development (CNPq)

Creation of a model of radiative transfer in the atmosphere that allows to estimate the solar irradiation incident in the national territory of Chile with the processing of satellite images, taking into account its particular geographic and climatic conditions. For this, INPE Brazil-SR model was modified and adapted to the Chilean conditions.

Coordinator: Rodrigo Escobar Moragas (Universidade do Chile)

Funder: National Commission for Scientific and Technological Research (Cooperation) - Chile

Development of methodology for the forecasting of short-term wind energy suitable for the Northeast region of Brazil, based on numerical forecasts made operational in the country and compatible with the tropical climate, thus allowing wind power plants to become more competitive and the electricity system to be managed by optimized way. One of the greatest difficulties for the development of wind surveys for wind farms is the existing database. In addition to the scarcity of anemometric data, there is also a gap in terms of knowledge of the atmospheric boundary layer (ABL), especially in the region of greatest potential, the Northeast. The project was carried out through a partnership between three institutions: UFAL, INPE and CTA.

Coordinator: Roberto Fernando da Fonseca Lyra

Funder: National Council for Scientific and Technological Development (CNPq)

Generation and organization, in a geo-referenced database, of technical-scientific information containing environmental data, data of renewable resources and information on technology and infrastructure available in Brazil.

Coordinator: Enio Bueno Pereira

Funder: United Nations Environment Program (UNEP)

The subproject aims to conduct a study on the impacts of the various global climate change scenarios on the incident solar radiation flux and on the wind regime and, in this way, estimate how these changes will change their energy potentials in Brazil in the long-term, medium-term and short-term deadlines.

Coordinator: Enio Bueno Pereira

Funder: National Council for Scientific and Technological Development (CNPq)

Survey of solar energy resources in Brazil through the collection, qualification and distribution of solar data from the national environmental data collection network SONDA and by the modification of the BRASIL-SR radiation model for the use of semi-hourly satellite data.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

Coordinator: Enio Bueno Pereira

Funder: United Nations Environment Program (UNEP)

Brazil is crucial to mitigating climate change and preventing biodiversity loss. However, depending on the energy transition path, large-scale energy infrastructure projects can have negative consequences, such as land use and land cover conflicts and deforestation. Furthermore, climate change can affect the availability of renewable energy resources, resulting in the inappropriate deployment of new infrastructure in certain locations. To explore these complexities, we propose using the 'modeling to generate alternatives' (MGA) method incorporated in Calliope, a linear programming-based energy model that aims to minimize costs. MGA explores alternatives close to the optimal solution, not exceeding 5% of the total system cost. By combining five main layers—demand, policy, climate change, meteorological data, and alternatives—1,600 long-term energy solutions for Brazil will be generated. The model and scenarios rely on an extensive data approach prepared in a preprocessing step. First, we will perform a simulation and bias correction of wind and solar resources using ERA-5 reanalysis data. Second, geospatial data will be used to calculate land availability and the maximum energy capacity that can be deployed in a given area. Third, climate change factors (CCF) will be applied to renewable resources to assess their impacts on the Brazilian energy system. This proposal falls within the scope of INCT-Climate Change 2, Energy Security component, which implemented the methodology for calculating the CCF for solar and wind energy resources. Therefore, this proposal will continue with the development of adjustments to the Brazilian energy model. Finally, each scenario will be analyzed and categorized into sustainability and energy indicators.

Student: Paula Conde Santos Borba

Degree: Pós-doutorado

Advisor: Fernando Ramos Martins

Funder: FAPESP

The doctoral thesis currently underway seeks to evaluate variations in wind and solar resources in all Brazilian municipalities with power plants installed by 2024, between a future period and a reference period. To develop this study, global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) will be used, considering two GHG emission scenarios (SSP2 - 4.5 and SSP5 - 8.5).

At the end of 2024, 116 Brazilian municipalities had at least one wind power plant installed, and 48 municipalities had at least one solar photovoltaic plant. To enable an analysis of all these locations, in this study, the municipalities will be grouped homogeneously according to their energy resources using the K-means clustering methodology. By analyzing the clusters, it will be possible to identify variations in the intensity and variability of climate resources in each future scenario, allowing us to understand the trends in each region.

The results will show the clusters with the greatest variations between the periods analyzed, presenting both regions that may increase their energy potential in the future and regions that show a reduction in their capacity. It will also be possible to verify the seasonal and interannual impact caused by the variation in the frequency of occurrence of climatic events of greater and lesser intensity. This information can support the different planning and operating agencies of the Brazilian electrical system in making adjustments to the energy operation of a more renewable matrix, whether by identifying the interannual variability between sources and the consequent periods where energy security may be impacted, or by identifying the complementarity between them. Considering that the implementation of wind and solar photovoltaic plants is expected to remain high, this study can also support the expansion of the sector by identifying the locations that offer the best energy return considering different future climate scenarios.

Student: Felipe Husadel Poyer

Degree: Doutorado

Advisor: Enio Bueno Pereira

Funder: CAPES

The energy sector is one of the largest contributors to greenhouse gas emissions. Data from the Food and Agriculture Organization of the United Nations indicate that more than 30% of these emissions are associated with the production of energy and heat. The generation of electricity from renewable sources depends on prior assessments of the availability and variability of the associated resources. Computer models are one way to obtain this information for planning and management purposes in this area. To this end, the models must be able to accurately represent physical phenomena, taking into account local atmospheric factors. However, radiative transfer models employed in solar irradiance studies are limited and inefficient in separating the calculated global irradiance into its direct normal and diffuse components.

This work aims to implement mechanisms to separate these components and improve the spectral modeling adopted in the BRASIL-SR model, whose importance in the country is demonstrated by its use in the preparation of the Brazilian Solar Energy Atlas. The functionalities proposed here will enable the model to generate more accurate maps of the radiative components, contributing to the planning and development of the Brazilian energy matrix based on renewable sources and also to other sectors of society for which the spectral evaluation of solar irradiance is necessary information, such as health (ultraviolet radiation) and agricultural productivity (photosynthetically active radiation), among others.

Student: Antonio Maurício Zarzur

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

This study investigated the characterization and forecasting of solar irradiance (GHI) in the very short term in Central Amazonia, using surface irradiance measurements and cloud cover fraction estimates from an all-sky camera. Descriptive analyses of the variables involved were performed, verifying that variability is positively correlated with the number of overirradiance events and that low clouds are primarily responsible for intense overirradiance events and abrupt GHI ramps, within the proposed methodology. A new metric (the Dynamic Aggregate Overirradiance Index, DAOI) was proposed, capable of capturing seasonal patterns at the minute, daily, and annual levels associated with cloud dynamics. Nonlinear autoregressive models with exogenous inputs (NARX) were implemented with artificial neural networks and optimized using multiobjective genetic algorithms (MOGA), with different constraints and combinations of input variables. The models outperformed the persistence baseline, with RMSE reductions of up to 32.5% in the first 10 minutes of forecasting, even using significantly less input information than previous studies—a challenge compounded by the tropical region's atmospheric characteristics. The model with the best performance in very short-term GHI forecasting demonstrated high skill in detecting overirradiance events, especially under variable sky conditions, maintaining reliable performance up to 20–30 minutes ahead (average F1-measure of 0.65 in this range). These results contribute to the advancement of sub-hourly solar variability forecasting, with relevant implications for both applied meteorology and the planning and operation of photovoltaic systems.

Student: Vinicius Roggério da Rocha

Degree: Doutorado

Advisor: Gilberto Fisch

Funder: CAPES

The photovoltaic modules in general have been evaluated in very well controlled conditions taking into account the solar spectrum according to ASTM G 173-03 standard prepared with data from North America. Considering that North American climate is particular of that region and the spectrum in field tends to vary during the year, we can say that such evaluation may not be representative for the conditions found throughout the Brazilian territory. So, this work aims to carry out a preliminary assessment of the effect of spectral variations in the performance of photovoltaic modules of six different technologies in a particular region of Brazil.

Student: Guilherme Marques Neves

Degree: PhD

Advisors: Enio Bueno Pereira / Waldeir Amaral Vilela

Funder: CAPES

The global climate system presents variations that affect the availability of energy resources. The analysis of the variability of the energy resources is of great importance for the national energy planning, and can still bring benefits to other sectors of society. Studies on the influence of atmospheric variability on the availability of solar and wind resources are still scarce, especially for interannual and interdecadal scales. Based on climatic data that include reanalysis of atmospheric models, satellite images and surface observations, and using multivariate statistical analysis techniques, we intend to investigate, together, how solar, wind and hydraulic resources vary over the territory national, with emphasis on seasonal and interannual scales. This temporal variability between different sources allows to explore possible complementarities, while its spatial variability allows the quantification of the smoothing effect of load curves, a phenomenon of great importance in a country with continental dimensions such as Brazil. Therefore, it is intended to identify favorable regions for the installation of each type of generating plant from spatial optimization models, obtaining patterns of distribution of generating units that minimize the risk of energy shortage. Studies of this type become gradually more relevant as the trend towards a diversified electrical matrix is ​​observed and are evidenced as fundamental for the sustainability of the main economies of the world. It is expected that the results of this work will be another source of information to support the decisions of the government in planning the expansion of the national electricity system.

Student: André Rodrigues Gonçalves

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: Non-existent

In a scenario of global climate change and depletion of ecosystems, the growing demand for natural resources implies adopting new practices in human activities. The Nexus concept reads the interrelationship between Water, Energy and Food and how actions can systematically affect the three elements. It proposes appropriate management, based on information and governance, to ensure availability and access to resources in the long term.

In Brazil, the São Francisco river basin is emblematic territory for the Nexus concept, where water is demanded in energy generation, food production and direct use by the population. The periods of drought intensify the dispute over water, with social, economic and political effects. At the same time, solar irradiation is an abundant resource in the region, with an average level above 5 kWh / m² / day. Underutilized until now, its use to generate electricity has the potential to reduce water reserves, with the possibility of changing the region's sustainability index.

In this context, the research aims to analyze scenarios of application of solar source technologies to generate electricity in different functional, economic, spatial and land use arrangements. Nexus and Life Cycle Assessment will be methodological tools used to compose scenarios and quantify resource indicators. The scenarios will aim to provide information to decision making and subsidize governance and public policies focused on water, energy and food security in a region with an asymmetry in resource use.

Student: Érica Ferraz de Campos

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

The research is to analyze the spectral characteristics of the materials that make up the urban areas in Brazil, their relationship to the land use and energy demand. Aims to provide technical information that results in alleviating the phenomenon of warming of urban areas, called heat Island. The methodology consists of analyzing the phenomenon on the scale of the building and on the scale of cities and through models and simulations promote interaction with actual data: materials, construction methods, climate and use. The result of this project it is intended to complement information about the factors that determine the energy efficiency of cities, human well-being and environmental preservation and provide subsidies for the implementation of urban-related parameters.

Student: Fabiana Lourenço e Silva Ferreira

Degree: PhD

Advisors: Enio Bueno Pereira

Funder: CAPES

The radiative transfer model BRASIL-SR was developed by LABREN/CCST/INPE and uses satellite images in conjunction with monthly average climatological data to calculate estimates of incident solar irradiation, allowing the mapping of sites suitable for the use of solar resources. The estimates provided by the model focus on monthly results and also on atmospheric transmittance calculated only for hourly averages in the center of the monthly interval, due to the high computational cost. Despite being exhaustively validated and presenting errors in the same order as other computational tools in the literature, the extrapolations performed imply higher bias values in the estimates of hourly and daily irradiance. This work aimed at optimizing the computational performance of the BRASIL-SR model on multicore systems, through the use of parallelization directives of OpenMP with loop scheduling and changes in the input and output data to the NetCDF format. The processing time for the BRASIL-SR model was reduced from 27 hours to 1 hour and 30 minutes using 24 threads. Other traditional optimization techniques, such as blocking and vectorization, were also investigated, but did not show an improvement in performance due to the structure of the model code. With the initial results of this research, it was possible to change the mode of transmittance calculation, which was previously calculated for the center of the monthly interval, to a daily transmittance calculation. A script was developed to perform the preprocessing and processing of the model, obtaining a total preprocessing and processing time of 1 hour and 40 minutes, an improvement of 3700%. The use of the model parallelized with OpenMP, together with the Python scripts developed for the operationalization of the model, will be determinant for the development of short and very short term solar irradiation forecast models, being of extreme relevance for the decision making of several actors, such as the National Electric System Operator.

Available at Production / Theses and Dissertations

Aluno: Jefferson Gonçalves de Souza

Grau: Master

Orientador: Celso Luiz Mendes / Rodrigo Santos Costa

Funder: CAPES

The variability of solar energy is one of the most important issues in the integration of solar energy into the power grid. The development of methods for assessing the movement of clouds and the resulting buoyancy in power generation make this study of great importance to the Brazilian energy sector. In this way, the work aimmed to classify and study the clouds in different regions of the Brazilian territory, using sky imagers, for a regional climatological knowledge and possible short-term forecasts of the cloud movement.

Student: Eduardo Weide Luiz

Degree: PhD

Advisor: Enio Bueno Pereira

Funders: CAPES / CNPq

The objective of this work was to carry out a careful evaluation for estimation and prediction of short term and high resolution of the wind power potential at high spatial resolution through simulations with two versions of the WRF model (WRF-Real and WRF-LES) for some regions of Northeastern Brazil.

Student: Lucía Iracema Chipponelli Pinto

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

Being of knowledge that Brazil has enormous resource potential of solar energy, this project proposed to develop a methodology for the seasonal forecast of solar irradiance, aimed at commercial exploitation of photovoltaic plants, with the aim of contributing to the country's energy planning, reducing the need for operation of thermoelectric plants that use fossil fuels and alleviate national energy security risks. This will be done through an approach involving the treatment of historical data, numerical modeling and utilization of artificial neural networks in order to get a joint analysis of the information obtained.

Student: Maria Francisca Azeredo Velloso

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

A study was conducted for climate variability and change of the minimum and maximum extreme winds to 10 m starting from the Brazilian airfields database of 10 m wind along with the downscaling of the HadCM3 global model made by ETA regional climate model to South America targeting the future scenario of the 2010 to 2100 of the IPCC AR4 scenario A1B 2100. It was also made the bias correction of the EtaHadCM3 model using the method of Artificial Neural Networks.

Student: Marcelo Pizzuti Pes

Degree: PhD

Advisors: Enio Bueno Pereira / José A. Marengo

Funders: INCT / CAPES

The WRF model was used to generate forecasts of surface solar radiation to the Northeast of Brazil, which were adjusted by statistical models based on multiple linear regression and artificial neural networks.

Student: Francisco José Lopes Lima

Degree: PhD

Advisor: Enio Bueno Pereira

Funders: CAPES / CNPq

The research aimed to develop methodologies for estimating parameters of cloud cover using data from long-wave radiation incident on the surface, along with weather data measured in surface stations in two localities, Brasília (DF) and Petrolina (PE). The first methodology employed atmospheric physics concepts to estimate the fraction of cloud coverage and presented behavior similar to the climatology of the localities studied. The second method proposed the use of Artificial Neural Networks for estimating the Effective Cloud Coverage and featured good correlation with satellite measurements. In addition, the method was able to evaluate the non-linearities of the estimate, when compared with linear methods such as Multiple Linear Regression.

Student: Eduardo Weide Luiz

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

Estimates of surface solar irradiance fields were made for the territory of Northeast Brazil in the years 2008 to 2011. For this, it was employed a estimating method based on interpolation by kriging. For evaluation of his performance, it was made an inter-comparison of the values estimated by interpolation with values measured in sampling points represented by Data Collection Platforms (DCPs) and estimates performed by the physical model of radiative transfer BRASIL-SR. The evaluation was performed through statistical indexes allied to cross-validation method and the visual analysis of maps of spatial variability of solar irradiance.

Student: Roque Magalhães Brito dos Santos

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

Several studies have shown, over the past few decades, that in fact the solar radiation that reaches the Earth's surface does not remain unchanged over the decades, but suffers increases and decreases known as solar dimming and solar brightening, respectively. However, the shortage of solar radiation data measured in the surface on long-term in Brazil is still a problem for the evaluation of the occurrence of these phenomena. Given this, this study proposed to assess trends in cloudiness, main factor modulator of solar radiation, through the study of spatio-temporal variability of the coefficient of cloud cover, determined through satellite images. For this, it were developed methods of estimation of irradiances of clear sky and overcast, necessary for the estimation of the coefficient of effective cloud coverage. The clear sky radiance is determined by the histogram of visible radiance frequencies measured by satellites, by assigning to it the value more often observed in a given area of the images within one quarter. The radiance of overcast skies, in turn, is determined by a setting that relates texture in the cloudtops, through the standard deviation of the visible radiance whose infrared measurement exceeds 280 K, with the sun-pixel-satellite geometry. The cloud cover was estimated for all the images of GOES-8 satellite, GOES-10 and GOES-12, in 1145, 1445, 1745 and 2045 GMT, in the period from 1999 to 2012. The trends of these coefficients were then evaluated through the use of non-parametric test of Mann-Kendall, with a significance level of 5%.

Student: Márcio Cecconi

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

The influence of atmospheric aerosols in quantifying of the solar resource was assessed from three data sources of horizontal visibility: climatological base model, the interpolation of the values of visibility of 105 airports in South America and visibility estimates obtained through the optical thickness of the aerosols from the CATT-BRAMS model. The simulations that used the data of horizontal visibility observed at airports showed significant improvements in estimates of global irradiation values, while the results of the simulations with the base of horizontal visibility estimated showed best performance in months and in regions where there was a high load of aerosols, with specific bias and RMSE decreases of up to 11%. Even when the new bases did not indicate improvements, error values were close to those obtained in the model integrations using horizontal climatological visibility.

Student: Rodrigo Santos Costa

Degree: PhD

Advisors: Enio Bueno Pereira / Fernando Ramos Martins (UNIFESP)

Funders: CAPES / CNPq

The ETA model outputs have been adjusted by statistical models based on multiple linear regression and artificial neural networks for the forecast of wind in surface (50 m). The results showed a significant gain in the correlations and reduction of errors in the forecast of wind in a horizon of 36 hours.

Student: André Rodrigues Gonçalves

Degree: Master

Advisors: Enio Bueno Pereira / Fernando Ramos Martins (UNIFESP)

Funder: CAPES

The work has developed a new methodology of analysis, knowledge representation and classification of atmospheric patterns from the values of the pixels of images obtained on the surface. The methodology aims to replace the synoptic observers (SO) that classify the sky from tacit knowledge and subjective criteria. The methods of analysis raised in specialized literature and in commercially available equipment use a binary approach of the results and mathematical simplification. The proposed methodology establishes an appropriate task domain to map the data represented by the values of the pixels in knowledge, necessary for the classification of standards based on the theory of atmospheric physics. Preliminary results indicated that the methodology proposed is superior to the main technique existing in specialized literature in the following aspects: more rigorous mathematical modeling, precise breakdown of the atmospheric patterns observed in the images, invariance with respect to solar incidence angle (brightness), comparison of the images with solar radiation sensors and the identification of other weather phenomena from the same images.

Student: Sylvio Luiz Mantelli Neto

Degree: PhD (Engineering and Knowledge Management)

Advisors: Aldo von Wangenheim / Enio Bueno Pereira

The work consisted of developing a methodology for assessing the impacts of climate change on the wind potential in the southern region of Brazil. For this study were used observational climatic series, ERA40 reanalysis from 1960 to 2007 and projections of the climatic ETA HadCM model from CPTEC, for the climatic scenario A1B until 2100.

Student: Marcelo Pizzuti Pes

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

Marajó island, in the State of Pará, North Brazil, shows a low level of economic development compared to other regions of the country. Among other factors that limit this development is the low availability of energy which, today, is produced exclusively by thermoelectric plants in isolated systems. This work aimed to make a preliminary survey on the feasibility of wind power generation in the region. The results indicated that the best winds occur in the months of September to November along the coastal region, on the north-northwest of the island. For this region there was an average wind power density of 151 W / m², and a form factor of 1.7. Based on wind data obtained by the ETA model and using the commercial package WasP wind systems analysis, was developed a scenario of use of wind energy in cogeneration scheme with the thermoelectric plants today installed in the region.

Student: Eliude Introvini da Cruz Segundo

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CNPq

The ETA model outputs have been adjusted by statistical models based on multiple linear regression and artificial neural networks for the forecast of solar radiation at the surface, showing gains in the application of statistical models in post processing of atmospheric models.

Student: Ricardo André Guarnieri

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CNPq

The work describes the development of a prototype of an automatic mapping system of the fraction of cloud cover and the first results obtained. It was used a system consisting of a digital Pixera brand camera, model PCS20232, operating in the range of visible radiation, along with a wide angle lens FCE8, Nikon's manufacturing, with a nominal opening of 178°. The results were compared with the atmospheric transmittance (Kt) and the ratio of global and diffuse solar radiations (Kd), besides the BRASIL-SR model, which estimates the solar radiation at the surface. It were employed, comparatively, as input to the model, the clouds fractions generated by the new imager system and data obtained by the GOES-8 satellite. The results showed important differences that have been attributed to the fact that the data obtained by the imager does not contain information on the optical depth of the clouds.

Student: Mariza Pereira de Souza Echer

Degree: PhD (Space Geophysics)

Advisor: Enio Bueno Pereira

Funder: CNPq

In this study it were evaluated, developed and implemented in the BRASIL-SR model parameterizations of cloud cover index and aerosols released into the atmosphere in events of burning, seeking the improvement of estimates of solar irradiation. Two techniques were proposed for the composition of images of clear sky and overcast. The visual analysis of the compositions of images showed that the reason IR/VIS offers greater efficiency in identifying pixels with persistent conditions. The technique implemented for parameterization of aerosol from burning adopted optical properties obtained with the use of "Global Aerosol Data Set" and showed good agreement with values obtained in TRACE-A and SCAR-B missions. The studies showed that, with more appropriate parameterization for the determination procedures of cloud cover and the influence of aerosols, model performance is improved.

Student: Fernando Ramos Martins

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: FAPESP

The paper presents a method to increase the precision of estimates of cloud cover made from the surface and compare it with satellite images. Were used: an inexpensive digital camera from the surface, image processing algorithms, an atmospheric physical model for the calculation of solar radiation on the surface, solar irradiation data, synoptic data and images from the GOES-8 satellite. The proposed methodology concluded that the interpretation of the estimates of cloud cover can not be binary, assigning a pixel of an image corresponding representation of a cloud or not, with a range of intermediate values ​​of transparency. This classification can lead to misinterpretation, as there are in the sky a series of physical manifestations as scattering and atmospheric turbidity that, despite representing clear sky, can confuse an automated interpretation system to due to proximity of intensity values with a small cloud optical depth (such as cirrus and the edges of other types of clouds), super sizing the final amount of cloud cover. This finding was possible only after using anisotropic diffusion on the images of clouds.

Student: Sylvio Luiz Mantelli Neto

Degree: Master (Computer Science)

Advisors: Aldo von Wangenheim / Enio Bueno Pereira

The new method described in work employs a database obtained in surface through a digital camera with sensor type Charge Coupled Device (CCD), in the range of visible radiation and acquiring images in red, green and blue (RGB). To analyze the collected images it was developed an algorithm whose function is to classify the pixels based on a decision process established empirically by field observers, determining the fraction of the sky covered by clouds. RGB attributes were transformed to Intensity, Hue and Saturation (IHS) using the saturation (S) in the separation of the pixels that match the sky and the clouds. The methodology was tested on images collected in the Antarctic Brazilian Station "Comandante Ferraz" and the results showed that the technique is suitable for the proposed work. The hit percentage for the pixels classified as clear sky was among 94% and 99% and classified as fully covered between 99.96% and 100%. The hit percentage to partially overcast sky presents a great difficulty in validating due to the very subjective characteristic of the visual identification process, usually employed in weather stations. The evaluation of the results of the automatic classification method was obtained by analysis of case studies based in various sky coverage states. These cases were chosen in order to represent: (1) sky with cloud cover patterns well defined (outlines of clouds well defined) and (2) sky with vague patterns and large amount of cloudiness (clouds with poorly defined edges and / or indefinite coverage states). To these conditions the recognition program also displays response consistent with the subjective process of classification based on visual inspection. Images collected for different Zenithal angle values and states of cloud cover were classified by the method. The sorting algorithm divided the results in three separate cases: (1) effectively clouds (11% to 82.93%); (2) indefinite state (10% to 23.41%) and (3) clear sky (13.82% to 85.32%). All groups were tested with a confidence level of 99.73%.

Student: Mariza Pereira de Souza Echer

Degree: Master (Space Geophysics)

Advisor: Enio Bueno Pereira

Funder: CNPq