Energy cost optimization in irrigation system of smart farm by using genetic algorithm

• Main Authors: De Ocampo, Anton Louise P., Dadios, Elmer P.
• Format: text
• Published: Animo Repository 2017
• Subjects: Irrigation farming > Cost of operation; Genetic algorithms; Manufacturing
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/3363; https://animorepository.dlsu.edu.ph/context/faculty_research/article/4365/type/native/viewcontent/HNICEM.2017.8269497
• Institution: De La Salle University

The challenge of increasing crop yield to suffice the food demand is being addressed by using modern technology in agriculture or by implementing a Smart Farm. Irrigation plays a very important role in Smart Farm but also requires optimized operating conditions to maintain sufficient water supply while minimizing energy consumption. In this study, operation of water pumps in the irrigation system limited by the amount of available energy from the solar power station, are simulated and optimized to minimize the energy cost. Genetic algorithm is performed several times under different optimization parameters to obtain the most optimal solutions. Operating conditions are handled as penalty functions for the objective functions. The performance of the algorithm in solving multi-objective optimization problem is evaluated and presented. © 2017 IEEE.