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Small autonomous power systems (SAPS) that include renewable energy sources are a promising option for isolated power generation at remote locations. The optimal sizing problem of SAPS is a challenging combinatorial optimization problem, and its solution may prove a very time-consuming process. This paper initially investigates the performance of two popular metaheuristic methods, namely, simulated annealing (SA) and tabu search (TS), for the solution of SAPS optimal sizing problem. Moreover, this paper proposes a hybrid SA-TS method that combines the advantages of each one of the above-mentioned metaheuristic methods. The proposed method has been successfully applied to design an SAPS in Chania region, Greece. In the study, the objective function is the minimization of SAPS cost of energy (€/kWh), and the design variables are: 1) wind turbines size, 2) photovoltaics size, 3) diesel generator size, 4) biodiesel generator size, 5) fuel cells size, 6) batteries size, 7) converter size, and 8) dispatch strategy. The performance of the proposed hybrid optimization methodology is studied for a large number of alternative scenarios via sensitivity analysis, and the conclusion is that the proposed hybrid SA-TS improves the obtained solutions, in terms of quality and convergence, compared to the solutions provided by individual SA or individual TS methods.