The main aim of this paper is to select the best portfolio of renewable energy technologies (RETs) for electrifying an elected area which is not connected to any other grids. Minimizing total costs of the system is considered as the main factor in finding the best decision. In order to make the optimum plan more applicable, the technique of life cycle analysis is applied. This technique takes into account all costs of the system from the manufacturing stage of the different parts of a power plant until their disposal. Also, demand-side management alternatives are considered as competing solutions against the mentioned supply side options. To tackle the problem, an integrated and complex mathematical formulation is developed for finding the optimum energy plan regarding the real world assumptions. For the reason of NP-hard nature of the proposed model and it is hard-to-solve for real large sized problems, a genetic algorithm (GA) approach is additionally developed for solving the mixed integer non-linear model for the medium and large size problems. To evaluate the performance of the proposed GA, a range of random test problems are conducted. The obtained results show that the length of planning period is the core factor in selecting the appropriate portfolio of RETs. Furthermore, it is shown that the proposed GA is capable of producing good results in almost negligible processing times.