Abstract
This work aims to analyze the variability of average annual streamflow time series of the SIN (Brazil) and create a projection model of future streamflow scenarios from 3 to 10 years using wavelet transform. The streamflow time series were used divided into two periods: 1931 to 2005 and 2006 to 2017, for calibration and verification, respectively. The annual series was standardized, and by the wavelet transform, it was decomposed into two bands plus the residue for each Base Posts (BP) for later reconstruction. Then an autoregressive model per band and residue was made. The projection was obtained by adding the autoregressive models. For performance evaluation, a qualitative analysis of the cumulative probability distribution of the projected years and the likelihood were made. The model identified the probability distribution function of the projected years and obtained likelihood greater than 1 in most of the SIN regions, indicating that this methodology can capture the medium-range variability.
Highlights
The expansion planning of the Brazilian electric system is composed, among other activities, of computational simulations of future electric energy system configurations (Costa et al, 2007)
Considering the importance of hydroelectric generation for the Brazilian National Interconnected System (NIS) and the various mechanisms responsible for the climate variability in this region, which associate a risk to this system, this study aimed to propose a model for the medium-term projection for the NIS, based on the climatic variability of the series of naturalized streamflow of the ONS using the wavelet transform (WT) method
The principle of likelihood states that “a statistical inference must be consistent with the hypothesis that the best explanation of a data set is provided by θ, a value of θ which maximizes the likelihood function.”
Summary
The expansion planning of the Brazilian electric system is composed, among other activities, of computational simulations of future electric energy system configurations (Costa et al, 2007). In these simulations, it is sought to locate and measure future electricity and energy needs, as well as adjusting entry schedules of generation projects, among others. It is sought to locate and measure future electricity and energy needs, as well as adjusting entry schedules of generation projects, among others Such adjustments are made following criteria that mainly aim at the security of supply and minimization of investment and operating costs. The hydroelectric generation and planning of the hydropower sector in Brazil presents correlation with the water stocks in the hydroelectric power plants reservoirs and their inflows
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