Design of PV powered smart drip irrigation system in modern fruit (Dwarf cherry) growing

In this thesis, the dissemination of using and increasing of the applicability of the renewable energy sources, to optimize energy and water consumption by reference to the value of soil moisture under control of a drip irrigation system is provided. Regardless of the water demand of trees in the land, the conventional irrigation systems cause that led to excessive irrigation of a part, lack irrigation of the other part and actually leads to decrease in the efficiency of water and energy. In this study, control of irrigation was provided by soil moisture sensors which of location and number was detected by the Genetic Algorithm (GA) with using moisture distribution which obtained by Artificial Neural Networks (ANN). Moisture distribution map of the land was obtained by training ANN data of 15 pieces soil moisture sensors which communicates with the radio frequency. On the distribution map, optimum number of sensors and these sensors will be placed points is achieved through the GA to provide optimum power and water consumption. The developed system has been reduced by 36% daily energy and water consumption.Key Words : Drip Irrigation, Solar Energy, Dwarf Cherry, Soil Moisture Sensor, Neural Network, Genetic Algorithm