Energy saving potential analysis of indoor aquaculture through optimal control strategies based on building energy simulation

Energy consumption in buildings relies primarily on their purpose, as opposed to the type of occupants. Representatively, land-based indoor fish farms are one of the most energy-consuming buildings which people do not live in Korea. Further, as the global demand for seafood increase continuously, indoor fish farms are expected to show continued growth to meet the increased demand. Therefore, it is critical to identify the status of energy consumption in indoor fish farms and reduce energy demand by analyzing consumption patterns.

Typical control in indoor fish farms relies heavily on the experience of the manager, leading to limited optimization and energy inefficiency. As a result, optimal control can offer significant energy savings and efficient cost reduction. However, only a few studies have focused on energy analysis and reduction measures for indoor fish farms that involve relatively high-power consumption.

Therefore, this study aims to develop an energy model for indoor fish farms and analyze energy-saving potential during the operational phase was analyzed using optimization tool. Recirculating aquaculture system(RAS) as the target facilities. This is because the energy consumption of RAS has increased due to the use of advanced water treatment systems with water circulation. These systems can be employed to use water more efficiently and increase the productivity. An energy model simulating various equipment in RAS, such as circulation pumps and water heating tanks, was developed using EnergyPlus.

The model was validated by measuring the indoor environment and energy consumption. The validation results show that the model demonstrated representative predictive performance, satisfying the hourly ASHRAE measurement and validation guidelines with an MBE of -0.37% and a Cv(RMSE) of 11.9%. Additionally, to improve predictive performance, the model was calibrated by deriving and applying water setpoints and operational scenarios that can be implemented in the field.

The calibrated model was used to derive optimal control strategies for heating setpoints of boilers and heat pumps, which are the largest energy consumers in aquaculture facilities, using the Genopt optimization tool. The setpoints were limited to the same ranges as in the field: 60-70°C for boilers and 50-60°C for heat pumps. The optimal control results showed an 8.9% reduction compared to the measured energy consumption. This study provides foundational data on the potential for energy savings and greenhouse gas emissions reduction in the aquaculture industry through the integration of model based optimal control.