Abstract: N. Bigdeli, M. S. Borujeni, K. Afshar (2017)

In this paper, nonlinear time series analysis and short-term prediction of solar irradiation were considered, simultaneously. The proposed methodology is to employ time series analysis methods as well as swarm and evolutionary algorithms in conjunction with well-known regression, fuzzy and neural network model structures to develop a simple but efficient and applicable model for solar irradiation forecasting. The employed experimental data was the hourly solar irradiation of Qazvin city in Iran for five years. At first, the solar irradiation data was normalized using the daily clear sky irradiation data which is an annually periodic time series. Then, the properties of normalized solar irradiation were characterized via time series analysis methods such as recurrence plots, autocorrelation and mutual information analysis. Based on these analyses, each year was divided into two seasons, the sunny and cloudy seasons which are noticeably different in dynamics. Next, a hybrid but simple model was developed to predict the solar irradiation in different seasons. For the sunny season, an optimized multivariate regression model was proposed; and for the cloudy season a bi-level model consisting of an optimized regression model and ANFIS was developed. The model parameters were tuned optimally by various evolutionary algorithms being GA, PSO, ABC, COA, and flower pollination algorithm (FPA). A Fourier-type model was also developed for modeling of the clear sky data. The results showed the out-performance of FPA method in tuning of the model parameters and convergence time. Besides, the performance of the proposed bi-level model was evaluated in comparison with some other model structures such as artificial neural networks, ANFIS networks, LSE-regression models, LS-support vector machines model, etc. The results showed that the proposed method performs considerably better than the other methods in forecasting the solar irradiation time series in both sunny and cloudy seasons.

Please note: The abstracts of the bibliography database may underly other copyrights.

Ihr Browser versucht gerade eine Seite aus dem sogenannten Internet auszudrucken. Das Internet ist ein weltweites Netzwerk von Computern, das den Menschen ganz neue Möglichkeiten der Kommunikation bietet.

Da Politiker im Regelfall von neuen Dingen nichts verstehen, halten wir es für notwendig, sie davor zu schützen. Dies ist im beidseitigen Interesse, da unnötige Angstzustände bei Ihnen verhindert werden, ebenso wie es uns vor profilierungs- und machtsüchtigen Politikern schützt.

Sollten Sie der Meinung sein, dass Sie diese Internetseite dennoch sehen sollten, so können Sie jederzeit durch normalen Gebrauch eines Internetbrowsers darauf zugreifen. Dazu sind aber minimale Computerkenntnisse erforderlich. Sollten Sie diese nicht haben, vergessen Sie einfach dieses Internet und lassen uns in Ruhe.

Die Umgehung dieser Ausdrucksperre ist nach §95a UrhG verboten.

Mehr Informationen unter www.politiker-stopp.de.

Time series analysis and short-term forecasting of solar irradiation, a new hybrid approach