Size optimization for hybrid photovoltaic–wind energy system using ant colony optimization for continuous domains based integer programming

• ACOR based integer programming is employed for size optimization.
• The objective function of the hybrid PV–wind system is the total design cost.
• Decision variables are number of solar panels, wind turbines and batteries.
• A complete data set, an optimization formulation and ACOR are benefits of this paper.

In this paper, ant colony optimization for continuous domains (ACOR) based integer programming is employed for size optimization in a hybrid photovoltaic (PV)–wind energy system. ACOR is a direct extension of ant colony optimization (ACO). Also, it is the significant ant-based algorithm for continuous optimization. In this setting, the variables are first considered as real then rounded in each step of iteration. The number of solar panels, wind turbines and batteries are selected as decision variables of integer programming problem. The objective function of the PV–wind system design is the total design cost which is the sum of total capital cost and total maintenance cost that should be minimized. The optimization is separately performed for three renewable energy systems including hybrid systems, solar stand alone and wind stand alone. A complete data set, a regular optimization formulation and ACOR based integer programming are the main features of this paper. The optimization results showed that this method gives the best results just in few seconds. Also, the results are compared with other artificial intelligent (AI) approaches and a conventional optimization method. Moreover, the results are very promising and prove that the authors’ proposed approach outperforms them in terms of reaching an optimal solution and speed.

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