Search

• An autonomous water pumping system (WPS) is suggested. • A hybrid energy system is optimized through seagull optimization algorithm (SOA). • The impacts of load management (LM) strategy in system sizing is analyzed. • Techno-economic evaluation in the presence and absence of load management is made. This study introduces an innovative irrigation system tailored for a tomato field in Algeria, optimizing its elements using Seagull Optimization Algorithm (SOA) over a 20-year lifespan. The system integrates photovoltaic (PV), wind turbine (WT), diesel generator (DG), battery, and tank storage for water pumping. The novelty lies in the incorporation of Load Management (LM), creating a dynamic water demand profile across four tomato development stages. Without LM, the optimal configuration yields a Net Total Present Cost (NTPC) of $14,140, corresponding to a Cost of Energy (COE) of 0.292 $/kWh. This configuration ensures a 24% Loss of Power Supply Probability (LPSP), a 41.2 % Loss of Water Supply Probability (LWSP), and an emission factor of 0.169 kg/kWh during 279 h of DG operation annually. With LM, the COE drops to $0.298/kWh, reducing the NTPC to $12,080. This LM strategy gives an 18 % LPSP, 20 % LWSP, and an Energy Fraction (EF) of 0.140 kg/kWh during 168 h of DG operation annually. The present application is a promising and cost-effective solution for optimizing Water Pumping Systems (WPS) in agricultural settings. [ABSTRACT FROM AUTHOR]