Simulation and Optimization of Recirculating Aquaculture Systems
Licentiate thesis, 2018

Recirculating aquaculture -- intensive fish farming with water treatment and reuse -- has great potential as a method for sustainable food production. Benefits over traditional aquaculture include opportunities to reduce nitrogen emissions to water, control of temperature, salinity and pH, reduced environmental impact of escapes and better protection against e.g. parasites and pathogens. Building a water treatment system is however a significant investment, which makes the optimality of the design important. Unfortunately, the biological nature of these plants leads to incredibly slow dynamics, which makes experimental development very tedious and expensive.

Water treatment in recirculating aquaculture systems (RAS) typically consist of particle removal (settling and/or filtering), degassing of carbon dioxide, biological removal of organics and nitrogenous waste, oxygenation of water and (optionally) application of ozone or UV against pathogens. Dimensioning the various units is often done using steady state mass balances that do not capture the complex interactions present in biological water treatment systems. Simulations of integrated dynamical models of fish growth, waste production and water treatment have previously been shown to be useful in exploring these interactions, and with enough fidelity, computer models can greatly improve the speed at which recirculating aquaculture can be developed.

In this thesis, a framework for dynamical modelling of recirculating aquaculture systems is presented. It is based on the well-established Activated Sludge Model no. 1 together with models of fish growth, feeding, digestion and evacuation. The model has been implemented in Modelica to produce a dynamic RAS simulator that is the successor to FishSim, with greatly improved performance and robustness. A genetic optimization routine was used with the simulator in order to investigate the impact of different layouts, or topologies, on the performance of the water treatment in a RAS.

Three different water treatment topologies, two fish species (Rainbow trout and Atlantic salmon), two influent oxygen saturation levels and both semi-closed and fully recirculating versions were compared, for a total of 24 cases. Each case was optimized in terms of required biofilter volume to maintain an acceptable total ammonia nitrogen (TAN) concentration in the fish tank. The results indicate that the smallest volume is obtained by introducing several bypass flows in the treatment system of a semi-closed RAS. In a fully closed system with minimal water exchange, denitrification is required to prevent excessive accumulation of nitrate, and then the flows of oxygen, carbon and nitrogen must be carefully considered. For several of the cases, no optimum with denitrification could be found.

We conclude that no overall best configuration and operation strategy for water treatment could be found, but rather that it varies depending on the conditions imposed by the fish culture. This highlights how simulations can be an important tool in gaining understanding about the behaviour of recirculating aquaculture systems.

dynamic modelling

optimization

biofilter

wastewater treatment

Recirculating aquaculture

EC, Hörsalsvägen 11
Opponent: Professor Bengt Carlsson, Department of Information Technology, Uppsala University, Sweden

Author

Simon Pedersen

Chalmers, Electrical Engineering, Systems and control

Pedersen, S., Wik, T. A comparison of topologies in recirculating aquaculture systems using simulation and optimization

Development of NOvel, high‐quality MArine aquaCULTURE in Sweden ‐ with focus on environmental and economic sustainability (NOMACULTURE)

The Swedish Foundation for Strategic Environmental Research (Mistra) (2013/75), 2014-06-01 -- 2018-08-31.

Subject Categories

Water Engineering

Water Treatment

Oceanography, Hydrology, Water Resources

Publisher

Chalmers

EC, Hörsalsvägen 11

Opponent: Professor Bengt Carlsson, Department of Information Technology, Uppsala University, Sweden

More information

Latest update

10/9/2018