18 resultados para CENTRO DE ENERGIA
Resumo:
The stabilization of energy supply in Brazil has been a challenge for the operation of the National Interconnected System in face of hydrological and climatic variations. Thermoelectric plants have been used as an emergency source for periods of water scarcity. The utilization of fossil fuels, however, has elevated the cost of electricity. On the other hand, offshore wind energy has gained importance in the international context and is competitive enough to become a possibility for future generation in Brazil. In this scenario, the main goal of this thesis was to investigate the magnitude and distribution of offshore wind resources, and also verify the possibilities of complementing hydropower. A data series of precipitation from the Climatic Research Unit (CRU) Blended Sea Winds from the National Climatic Data Center (NCDC/NOAA) were used. According to statistical criteria, three types of complementarity were found in the Brazilian territory: hydro × hydro, wind × wind and hydro × wind. It was noted a significant complementarity between wind and hydro resources (r = -0.65), mainly for the hydrographical basins of the southeast and central regions with Northeastern Brazil winds. To refine the extrapolation of winds over the ocean, a method based on the Monin-Obukhov theory was used to model the stability of the atmospheric boundary layer. Objectively Analyzed Air-Sea Flux (OAFLUX) datasets for heat flux, temperature and humidity, and also sea level pressure data from NCEP/NCAR were used. The ETOPO1 from the National Geophysical Data Center (NGDC/NOAA) provided bathymetric data. It was found that shallow waters, between 0-20 meters, have a resource estimated at 559 GW. The contribution of wind resources to hydroelectric reservoir operation was investigated with a simplified hybrid wind-hydraulic model, and reservoir level, inflow, outflow and turbine production data. It was found that the hybrid system avoids drought periods, continuously saving water from reservoirs through wind production. Therefore, from the results obtained, it is possible to state that the good winds from the Brazilian coast can, besides diversifying the electric matrix, stabilize the hydrological fluctuations avoiding rationing and blackouts, reducing the use of thermal power plants, increasing the production cost and emission of greenhouse gases. Public policies targeted to offshore wind energy will be necessary for its full development.
Resumo:
A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.
Resumo:
A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.