The component selection plays an important role in the performance of the off-grid system. In this paper, an alternative method for optimal component selection, among a list of commercially available equipment, of the off-grid integrated renewable energy system has been developed. The proposed method identifies the optimal components based on their contribution to the overall cost and power reliability of the system. The practicability of the proposed method has been evaluated by modeling the integrated renewable energy system to electrify the rural area. The impact of system components on the overall cost and power reliability has been evaluated by using the multi-variable linear regression technique along with the gradient descent algorithm. Then, the best components have been identified based on the trade-off between their impacts on the overall cost and power reliability of the system by using an analytical hierarchy process. The performance of the proposed method has been validated using the particle swarm optimization algorithm. At last, the sensitivity analysis has been performed to investigate the effect of variation in most influencing parameters. The comparative assessment of the proposed method with the existing method indicates its superiority in identifying the optimal components of the off-grid integrated renewable energy system. (C) 2019 Elsevier Ltd. All rights reserved.