A model predictive control approach for recirculating aquaculture systems integrated with sustainable hybrid energy systems

Aquaculture is a growing industry that provides high-quality protein, however, the growth of aquaculture production has a range of environmental concerns. Recirculating aquaculture systems (RAS) are a popular solution to accomplish intensifying fish production, and integrating renewable technologies is an attractive option that may provide low-carbon energy and promote sustainability. This paper presents an optimisation model for the control and operation of a grid-connected distributed energy system (DES) integrated with an RAS. A linear optimal power flow (OPF) combined with model predictive control (MPC) strategy is developed which simulates the thermal and electricity balances present throughout the renewable energy integrated electricity network and RAS, to make real-time optimal operation scheduling plans on different time horizons. The optimal results show that the MPC strategy improves the control performance of system operation and improves the process economics. With renewable energy sources (RES), operational costs can be reduced by up to 27%. Compared with a conventional scheduling plan, the rolling horizon approach can provide 3% energy cost saving, while maintaining fish well-being and system safety.