Statistical analysis of self-affinity of energy dispatch in power generation in the Northeast region of Brazil
Análise estatística de autoafinidade do despacho de energia na geração de energia na região nordeste do brasil
Palavras-chave:
Detrended Fluctuatin Analysis (DFA), Analysis of long-range autocorrelations, Time series, Electric power dispatch, National Interconnected SystemResumo
In this article, we study the fractal dynamics in time series of energy generation in the Northeast region of Brazil, considering a database used by the National Electric System Operator referring to semi-hourly information on the generation of various energy sources. Applying the DFA technique between the years 2020 and 2022, it was found that the dispatch of solar energy fluctuated in all years from superdiffusive behavior in the short term to persistent in the long term, whereas wind generation in all years varied from superdiffusive short-term to long-term subdiffusive. In all observation periods, there was a repeatability of the dispatch behavior of wind and solar sources, which can be explained by the fact that these sources always maintain a standard of availability for the energy matrix. When analyzing the behavior of solar generation, a greater predictability of energy availability was found, which can therefore be considered as a more viable source to make up for the lack of hydraulic energy. This analysis is based on historical time series numbers, not considering the costs of each energy source, environmental license situations, among other factors.
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Referências
BRITO, A. A. et al. Cross-correlation in a turbulent flow: Analysis of the velocity field using the ρDCCA coefficient. Europhysics Letters, v. 123, n. 2, p. 20011, 2018.
CHEN, Zhi et al. Effect of nonstationarities on detrended fluctuation analysis. Physical review E, v. 65, n. 4, p. 041107, 2002. DOI: 10.1103/PhysRevE.65.041107.
DELIGNIÈRES, Didier; TORRE, Kjerstin; BERNARD, Pierre-Louis. Transition from persistent to anti-persistent correlations in postural sway indicates velocity-based control. PLoS computational biology, v. 7, n. 2, p. e1001089, 2011. DOI: 10.1371/journal.pcbi.1001089.
EKE, Andras et al. Physiological time series: distinguishing fractal noises from motions. Pflügers Archiv, v. 439, p. 403-415, 2000.
Energy Balance Database of ONS. ONS DESSEM DATABASE. In: https://dados.ons.org.br/dataset/balanco-energia-dessem. Accessed on 11 december 2023.
HU, Kun et al. Effect of trends on detrended fluctuation analysis. Physical Review E, v. 64, n. 1, p. 011114, 2001. DOI:10.1103/PhysRevE.64.011114.
National System Operator. ONS. In: https://sintegre.ons.org.br/. Accessed on 11 december 2023.
PENG, C.-K. et al. Mosaic organization of DNA nucleotides. Physical review e, v. 49, n. 2, p. 1685, 1994. DOI:10.1103/PhysRevE.49.1685.
PODOBNIK, Boris; STANLEY, H. Eugene. Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series.
Physical review letters, v. 100, n. 8, p. 084102, 2008. DOI:10.1103/PhysRevLett.100.084102.
RODRIGUES SANTOS, F. et al. Detection of the persistency of the blockages symmetry influence on the multi-scale cross-correlations of the velocity fields in internal turbulent flows in pipelines. Physica A: Statistical Mechanics and its Applications, v. 509, n. C, p. 294-301, 2018.
SANTOS, J. V. C. et al. Analysis of long-range correlations of wind speed in different regions of Bahia and the Abrolhos Archipelago, Brazil. Energy, v. 167, p. 680-687, 2019. DOI: 10.1016/j.energy.2018.11.015.
User Manual for Dessem. DESSEM. In: https://www.cepel.br/wpcontent/uploads/2022/05/DESSEM_ManualUsuario_v19.0.24.3.pdf. Accessed on 11 december 2023.
ZEBENDE, G. F.; DA SILVA, M. F.; MACHADO FILHO, A. DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches. Physica A: Statistical Mechanics and its Applications, v. 392, n. 8, p. 1756-1761, 2013. DOI: 10.1016/j.physa.2013.01.011.
ZEBENDE, Gillney Figueira. DCCA cross-correlation coefficient: Quantifying level of cross-correlation. Physica A: Statistical Mechanics and its Applications, v. 390, n. 4, p. 614-618, 2011. DOI: 10.1016/j.physa.2010.10.022.
ZEBENDE, Gilney Figueira et al. Uma visão hora a hora da autocorrelação em dados de temperatura e umidade relativa do ar na bahia. Revista Brasileira de Climatologia, v. 29, 2021. In: https://ojs.ufgd.edu.br/index.php/rbclima/article/view/15152. Accessed: jul 29 2023.