In search of electricity use patterns for resource-efficient fish farming in recirculating aquaculture systems – A systematic review

Recirculating Aquaculture Systems (RAS) are increasingly utilised farming systems, renowned for being water- and nutrient-efficient, yet they are energy demanding. However, systematic and comparable evidence on their energy requirements remains limited. This study aims to identify, review and synthesise current knowledge on key trends and reported factors influencing electrical energy consumption in RAS and to investigate resource use reporting. For this, energy use in fish RAS was examined in studies from 2010 to 2024 ( n = 25). The information on energy use linked to water use and feeding was analysed through regression and correlation analysis. Non-parametric tests investigated the influence of different production and data factors on energy use. Contrary to expectations, the findings indicate no direct relationship between energy use, water use, and feeding. Instead, systems operating with higher maximum stocking density operate more energy efficiently than those with lower density. Furthermore, commercial RAS demonstrated lower energy use than research systems, and freshwater systems operated more energy-efficiently than saltwater systems. Energy use was also influenced by species cultivated. The major limitation of this study was the small dataset on energy use in RAS available in the literature. The heterogeneity in data reporting need to be considered when interpreting these results and drawing general conclusions about energy and resource trade-offs in RAS. Nevertheless, this review offers a standardised assessment of RAS electrical energy use and its connections to other resource use indicators. Supporting the future development of comparable datasets for cumulative knowledge building, more consistent metrics and harmonisation are recommended. • Quantitative and standardised synthesis of factors affecting electricity use in RAS. • Species selection and rearing density influence energy use in RAS. • Data standardisation is essential for robust resource-use benchmarking. • High-yield, high-density species show potential for improving energy efficiency in RAS.