Abstract
This paper presents a method of building a two-state multi-criteria Markov chain for stochastic solar generators. The design is based on different criteria which are defined using some statistical thresholds such as quartiles and averages. These thresholds have been used for classifying the state of all individual data samples. The proposed model is analyzed via computer simulation on Matlab environment using the historical data recorded over a period of 29 years by three meteorological stations in Algeria (Tamanrasset, Ghardaïa, and Oran). In order to validate and compare the performance of our model, several statistical tests were performed. The root mean square error and mean absolute error range, respectively, from 0.18 to 0.26 h and −0.10 h to 0.16. The obtained results proved that the model is effective to predict the data. Moreover, this study can be applied in its methodology not only in Algeria sites but also in other countries of the world and can serve as a reference for different climates, which are Mediterranean coastal climate, desert climate, and Sahel climate. Hence, it is useful to the designers of solar energy systems.