An auto-adaptive heat transfer model predicting the temperature evolution in photobioreactors

This work is a first step towards a generic and highly flexible dynamical heat transfer model for unravelling the complex nonlinear dynamics of microalgae growing in different cultivation systems and under different climates. Physical models for predicting reactor temperature are crucial to simulate a wide range of scenarios and therefore for applying a more efficient on-line system control, according to present and future weather conditions. However, adapting these models to different reactor designs is complex, since they require many parameters. In this work, a model predicting the temperature evolution in two pilot- scale outdoor reactors is developed, using weather measurements and records of temperature in the process. Firstly, we introduce the new model and demonstrate the identifiability of its parameters. Then, the model is calibrated and validated using experimental data from two different cultivation systems. The resulting model turns out to be flexible enough to predict temperature evolution in two different reactor configurations. The results show that the designed model is efficient to predict short/mid terms evolution, while it may require recalibration over longer time periods. Copyright (c) 2023 The Authors.