Bi-objective optimization of hybrid renewable energy systems with ice storage vs. battery storage for sustainable dairy farming

The integration of energy storage is key to the effective deployment of hybrid renewable energy systems in the agricultural sector. This paper presents a bi-objective optimization model to determine the optimal energy storage configuration for a sustainable dairy farm, conducting a direct techno-economic and environmental comparison between battery energy storage (BES) and ice-based cold thermal energy storage (CTES). Using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the model minimizes net present cost and (Formula presented) emissions for a case study farm in Ecuador, evaluating scenarios with photovoltaic, wind, biogas, and solar thermal technologies. The results indicate that both storage types are effective; however, ice storage stands out as the more cost-efficient option for reducing emissions in scenarios with high cooling demand. The scenario with renewable energy technologies such as PV, biogas, solar collectors, and ice storage achieved a 64% reduction in (Formula presented) emissions. In contrast, batteries offer greater flexibility once the cooling demand is saturated. This study underscores that the choice of energy storage technology is a critical determinant in balancing sustainability and affordability for small-scale food processors.