Estimation of monthly global solar irradiation using the Hargreaves–Samani model and an artificial neural network for the state of Alagoas in northeastern Brazil

Lyra, Gustavo Bastos; Zanetti, Sandra Aparecida Serra; Santos, Anderson Amorim Rocha; Souza, José Leonaldo de; Lyra, Guilherme Bastos; Júnior, José Francisco Oliveira; Lemes, Marco Antonio Maringolo

doi:10.1007/s00704-015-1541-8

Cited by 17 publications

(22 citation statements)

References 28 publications

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“…It should be noted that the predisposition of weather stations, with a larger number of stations near the Atlantic Ocean and the two Bays, Sepetiba and Guanabara, favored the higher k r values. Analogous to this study, Hargreaves [17] and Lyra et al [15] also observed the highest k r values in stations located on the coast of Alagoas.…”

Section: Hargreaves-samani Methodssupporting

confidence: 88%

“…It is noteworthy that, from the 15 analyzed stations, only two presented r 2 lower than 0.7 (Petrópolis and Teresópolis-A618); therefore, in most stations, the Hargreaves-Samani method presented accuracy greater than 80% in relation to H g observations ( Table 6). The stations with less precision were located in the Serrana region (A610 and A618) of the state (interior) and the highest altitude 950 m. This result indicates that the precision was close to those observed by Lyra et al [15], which report r 2 between 0.62 and 0.87 for the state of Alagoas.…”

Section: Hargreaves-samani Methodssupporting

confidence: 86%

“…The above corrections for the coefficients did not necessarily result in improved accuracy and precision of H g estimates by the Hargreaves-Samani and Bristow-Campbell methods in other regions [4,15,24], or by considering only one factor climatic conditions (e.g., oceanity/continentality, altitude, air temperature and thermal amplitude) or corrections are valid only for the place where they were proposed. Therefore, the aim of the present study was to fit and to assess the empirical coefficients of the Hargreaves-Samani [12] and Bristow-Campbell [9] methods for the estimation of monthly average daily global solar irradiation in the state of Rio de Janeiro, Brazil, and to propose a simple approach to determine their empirical coefficients in function of the climate.…”

Section: Introductionmentioning

confidence: 96%

“…The method proposed by Hargreaves and Samani [12] stands out for its simplicity and for providing precise and accurate estimates of H g [4,[13][14][15]. It estimates H g based only on air temperature extremes (maximum and minimum) and H o .…”

Section: Introductionmentioning

confidence: 99%

“…However, for a good performance of the methods, it is necessary that the empirical coefficients represent the local conditions [14,15,17,18]. Hagreaves [17] comments that k r varies only with the proximity of large bodies of water or extensive continental areas and suggests for regions of coast (< 20 km of large bodies of water) k r = 0.19 and, in the case of interior, k r = 0.16 [17,18].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of monthly global solar irradiation estimates using air temperature in different climates of the state of Rio de Janeiro, Southeastern Brazil

et al. 2019

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The number of weather stations that measure solar global irradiance (I g ) is scarce, and when it is available, it does not present long-time series, without gaps and high quality. When I g is unavailable, it is possible to estimate its integral over time-solar global irradiation (H g )-using empirical methods. However, for a better performance these methods need to be fitted to the local climatic conditions. The aim of this study was to assess the Hargreaves-Samani (HS) and Bristow-Campbell (BC) methods to estimate monthly average daily H g in the state of Rio de Janeiro, Southeastern Brazil, and to propose a simple approach to determine the empirical coefficients in function of the climate. The methods are based on maximum and minimum air temperature and on extraterrestrial solar irradiation. Series of air temperature extremes and H g from 15 automatic weather stations between 2000 until 2013 were used. The methods were evaluated by the statistical indexes: determination coefficient (r 2 ) of the linear regression between observed and estimated monthly H g , root mean square error (RMSE), Willmott's index (d) and performance index (c). The methods (BC-r 2 > 0.60, d > 0.85 and RMSE < 2.99 MJ m −2 d −1 and HS-r 2 > 0.55, d > 0.75 and RMSE < 3.85 MJ m −2 d −1 ) had satisfactory performance in the estimation of monthly H g for the state of Rio de Janeiro, when their coefficients were fitted to local climatic conditions. The BC presented performance classified as "optimal" (c > 0.85) in approximately 80% of the stations analyzed, while for Hargreaves-Samani, only 55% of the stations were classified as "optimal. " The highest HS coefficients (k r ) occurred in Semiarid (0.246 ± 0,023) and Dry Sub-humid (0.181 ± 0.011) climates and were associated with coastal regions (< 20 km), while the stations in Humid (0.146 ± 0.008), Sub-humid (0.1524 ± 0.003) and Dry Sub-humid (0.162 ± 0.011) climates located in interior regions presented the lowest k r . Thus, it is possible to determine the k r coefficient based only on the climatic classification of the site and distance of the coastal environment. In general, the highest atmospheric transmittance (β 0 -BC method) was observed in Semiarid and Dry Sub-humid climate regions. β 1 and β 2 coefficients did not present a distribution pattern with the local climatology and with the proximity of large water bodies. The methods presented a better performance in Dry Sub-humid and Semiarid climates, due to the lower variability of cloudiness and greater thermal amplitude.

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Section: Hargreaves-samani Methodssupporting

confidence: 88%

Section: Hargreaves-samani Methodssupporting

confidence: 86%