The present paper deals with the application of a Multi-Criteria Evaluation approach (MCE) to carry out site selection for Concentrating Solar Power plants (CSP). As this work demonstrates, multi-criteria analysis can provide a technical–scientific decision making tool capable of justifying choices in a clear and coherent manner, particularly in the renewable energy sector. The site selection for CSP is a complex topic. Although it has a significant impact on project costs, this issue has received little attention in the literature. A practical methodology based on a multi-criteria analysis is presented. Several potential sites called alternatives are compared, using a combination of Multi-Criteria Decision Making methods (MCDM) such as the Analytical Hierarchy Process (AHP), Scoring method and Benayoun and Tergny Algorithm. The relevance of this combination is examined through a case study of Algeria, a country with a high potential for CSP projects. The comparative analysis is carried out for a set of alternatives (Kenadsa, Abdala, Naâma and Hassi R’Mel). The assessment of alternatives and their ranking are discussed according to several scenarios, both for approaches used to estimate the criteria weights (AHP, weights affected in different manner) and for the two MCDM methods chosen for the present study. The methodology provides a better understanding of the site selection process for CSP, which would encourage their large-scale deployment on the green electricity market.

Il est inconcevable de dimensionner, de concevoir et de modéliser un système énergétique solaire sans avoir accès aux données météorologiques et plus particulièrement solaires du site d’implantation. Ces données sont souvent peu disponibles et il est important de disposer de méthodes efficaces pour les estimer. C’est l’objet de cet article qui fait une synthèse chronologique des dernières études relatives à l’utilisation des Réseaux de Neurones Artificiels (RNA) appliqués à l’estimation du potentiel énergétique solaire.