Solar radiation time series analytics based on hadoop integrated programming language environment (Rhipe)

Abstract

. In this paper, one of the most important aspects of solar energy resources which are solar irradiation is addressed. A fast analysis and calculation of time series solar irradiation using Hadoop integrated programming environment (RHIPE) is performed. The proposed work is evaluated using data provided by London weather centre for the period from (1996–2005) that includes monthly mean daily irradiation on inclined planes in terms of scalability, speedup and accuracy. The speedup of RHIPE in computation is analysed through Gustafson’s law. This law is revised to enhance its capability to analyse the performance gain in computation for parallelizing data in a cluster computing environment. The experimental results showed that RHIPE improves the performance analysis from the aspects of speedup, scalability and accuracy in comparison with R language. After the revision of Gustafson’s law, the speedup of RHIPE was evaluated using Different sizes of data blocks ranging from 8 to 64 MB and showed that the execution time of RHIPE decreases with an increasing size of data blocks while the speedup of RHIPE increases. Furthermore, the results showed that the speedup of RHIPE is 2.2 times faster in computation using 64 than when using 8 MB.