Abstract:

Inspired by the behavior of ants seeking the shortest path between their nest and a food source, ant colony optimization (ACO) is the most popular technique to effectively solve combinatorial optimization problems. Combinatorial optimization is a branch of optimization which is concerned with the optimization of functions with discrete decision variables. Finding optimum size of a PV/wind/battery hybrid system belongs to combinatorial optimization problems with the aim of determining three discrete decision variables, namely, number of PV panels, wind turbines and batteries. This paper proposes ACO to optimally size a PV/wind/battery hybrid system for having a reliable system. In order to evaluate the effectiveness of the proposed methodology, ACO performance is compared with that of two other well-known metaheuristic algorithms, namely, harmony search (HS) and particle swarm optimization (PSO). It is observed that ACO yields more promising results than the other studied methodologies

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