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Small off-grid photovoltaic (PV) pumping irrigation systems with storage tanks are an environmentally friendly, cost effective and efficient way of taking advantage of solar energy to irrigate crops, and they are increasingly being used today. However, finding the optimal design of this type of system is cumbersome since there are many possible designs. In this work, a new heuristic method based on the hybrid approach, which uses search space reduction, is developed and adapted to the optimal design for this type of PV irrigation system. At different stages, the proposed approach iteratively combines a bounding strategy based on the application of engineering rules with the aim of reducing the search space with a genetic algorithm to find the optimal design within this search space. The proposed methodology was applied to minimize the cost of a benchmark case study consisting of a real farm placed in the province of Almería (Spain). The proposed methodology was able to provide a faster and an accurate convergence due to the reduction of the search space. This fact led to a reduced total cost of the system. This study proved that the most sensitive variables were the number of modules and the type of pump, whereas the diameter of the pipe and volume of the storage tank remained more stable.

Multistage Bounded Evolutionary Algorithm to Optimize the Design of Sustainable Photovoltaic (PV) Pumping Irrigation Systems with Storage