For future energy planning and sustainable development, the share of renewable energy in the national power production must be increased. For this reason, energy managers and deciders would impose models and strategies for future renewable energy planning development. The site selection of new renewable energy projects constitutes a huge challenge, due to the contributions of several factors in the decision-making process. This study has two main objectives, the first is to develop an alternative framework for site selection of large-scale parabolic trough concentrating solar power on-grid plants as an essential future solar power in Algeria. A Geographic Information System (GIS) based analysis combined with Multi Criteria Decision Making techniques to develop a high-resolution map that identify and classify the suitable locations for setting up these projects. Several criteria are used in GIS analysis process, a map of direct normal solar irradiation and sunshine duration were developed with high resolution of (92×92 m/pixel) and grid power map was presented in its updatable form. The prioritization degree of the available siting zones is presented through three scenarios where distinct opinions of different energy related groups are considered by using different weighting methods; EQual Weighted (EQW), Analytic Hierarchy Process(AHP) and Best Worst Method (BWM).Second, the paper assesses the theoretical and technical potential of energy generation using concentrating solar power plants. A sensitivity analysis is applied for the suitable lands and finally, the results show that approximately 11% of the study area is considered as available lands for concentrating solar power energy generation with yearly electricity generation 34,453 TWh. The provinces of Bechar, Naama, Elbayadh, Laghouat, Gherdaïa, and Ouargla presenting the large lands of most suitable class (approximately 15,384.73 km2 and 15,986.34 km2 in AHP and BWM scenario respectively. Where the energy generation can reach more than 2,100 TWh/year, which can cover 38 time the national electricity demand.