A New Predicting Method for Long-Term Photovoltaic Storage Using Rescaled Range Analysis: Application to Two Algerian Sites
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A new predicting approach of long-term storage capacity for autonomous PV installations has been developed using the rescaled range analysis (R/S). The method consists mainly in establishing a mathematical law between the (R/S) τ ratio and the time period τ. The method has been tested over one year for two autonomous PV systems located in the huge desert of Algeria. Data used are converted solar energy which are not stationary. The experimental results show that even if the condition of stationarity is not satisfied, the rescaled range is well described by a power function of the time, this is possible by introducing a new exponent E. Using the power law the PV storage capacity is predicted for periods ranging from 1 to 5 years. The obtained results show that for an energy demand equalling the mean of converted energy, a storage of several months is needed to obtain the autonomy of the PV systems, consequently it will be too expensive to set-up such PV installations. Thus, an optimization method has been proposed to reduce the size of the storage. Application of this method for the two studied systems has led to significant reduction of the PV storage size.
KeywordsSolar irradiation Photovoltaic storage Fractal Hurst Rescaled range analysis Prediction
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- 8.Hurst, H.E., Black, R.P., Simaika, Y.M.: Long-term Storage: An Experimental Study. Constable, London (1965)Google Scholar
- 9.Mitra, S.K.: Trends in stock prices and range to standard deviation ratio. Int. J. Bus. Manage 6, 223–234 (2011)Google Scholar
- 12.Tricot, C., Quiniou, J.F., Wehbi, D., Roques-Carmes, C., Dubuc, B.: Evaluation de la dimension fractale d’un graphe. Rev. Phys. 23, 111–124 (1988)Google Scholar
- 16.Harrouni, S., Guessoum, A.: New method for estimating the time series fractal dimension: application to solar irradiances signals. In: Solar Energy: New Research, pp. 277–307. Nova Science Publishers, New York (2006)Google Scholar
- 19.Bouligand, G.: Ensembles impropres et nombre dimensionnel. Bull. Sci. Math. II-52, 320–344, 361–376 (1928)Google Scholar