This paper aims to address the issues related to renewable energy (RE) resources optimization in the areas where providing power from main grid is challenging. A region having ten different sub-regions has been considered for the optimization based on transportation algorithm. The partitions are made based on customer segmentation to ensure that various scattered demand for the RE is represented at the best location to enhance energy optimization by minimizing the energy loss during transmission. Three cases, i.e., when the demand and supply are equal, when there is more demand than supply, and when the supply is greater than demand are considered for the analysis. For the first case, the total energy requirement and the energy potential available from the regions is 1.26 GW h/year. For this scenario, most of the regions (seven regions) received the energy requirements from single RE source; three regions received the required energy from two different RE sources. The annual optimized total cost of energy supply for this scenario is determined to be 187,961.68. Results obtained from the transportation model have been validated based on other RE studies in the area. For the similar case study considered, it is noted that the minimized total cost obtained using transportation algorithm depicts an improvement in cost over integrated renewable energy system (IRES) models. The developed optimization model could be used as a decision making support tool to evaluate and select various alternative renewable energy resources and to determine the optimal locations for developing these resources. © 2016