Optimal hybrid PV/wind energy system sizing: Application of cuckoo search algorithm for Algerian dairy farms

The increase in energy demand has made the renewable resources more attractive. Representing the largest sources of renewable energy, solar and wind systems are expanding due to the rapid depletion of fossil fuel resources and the growing evidence of the global warming phenomena. However, variability and intermittency are some of the main features that characterize these renewable sources. The hybridization of multiple sources improves the system efficiency and the reliability of the supply. This paper presents an update literature review on optimization techniques used for the sizing and energy management of hybrid photovoltaic/wind/battery energy systems. Furthermore, a new sizing approach based on cuckoo search (CS) algorithm is proposed for grid-connected hybrid energy systems. The sizing optimization is a multi-objective problem with economic, technical and environmental constraints. The reliability criterion is modeled by a novel grid power absorption probability (GPAP) parameter. The new method is tested for both a residential load and an agricultural farm load located in the city of Ghardaia, Algeria. The proposed method have better accuracy, faster convergence and less computation time compared to the particle swarm sizing optimization (PSO) technique.