Optimizing off-grid energy-water systems: An improved metaheuristic framework with advanced dispatch modes

Designing off-grid energy-water systems for remote communities is challenged by renewable intermittency and high conventional fuel costs. This paper introduces, for the first time, an improved metaheuristic optimization algorithm coupled with three novel dispatch modes, Renewable Priority, Hybrid Load Following/Cycle Charging (HLF/CC), and Hybrid Load Following/Cycle Charging/Renewable Priority (HLF/CC/RP), alongside conventional Load Following and Cycle Charging strategies (the latter two widely used, while combined modes remain rare). The optimization framework simultaneously minimizes the total net annual cost while optimizing cost of desalinated water produced, renewable fraction, greenhouse gas emissions, levelized cost of energy, and system reliability, to optimally design a hybrid wind-diesel-battery-reverse osmosis system. Benchmarking against Harmony Search and extensive sensitivity analyses (emission taxes, wind speed, load demand, interest rate, and fuel cost) show that HLF/CC/RP and HLF/CC modes outperform conventional approaches in economic efficiency and environmental sustainability. This work delivers a scalable, low-carbon optimization framework for resilient off-grid energy-water systems, ensuring robust energy storage integration and system efficiency that has not been reported previously. • Novel metaheuristic optimization framework optimizes hybrid wind-diesel-battery-RO systems. • Three advanced dispatch modes boost cost-efficiency, reliability, renewable use, and emission reduction. • Validated against Harmony Search under both conventional and novel dispatch modes. • Sensitivity study spans emission taxes, wind variability, load profiles, fuel price, and interest rate. • Provides first-of-its-kind scalable, low-carbon design tool for off-grid energy-water systems.