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Dynamic simulation is a valuable tool to assist the scale-up and transition of biofuel production from laboratory scale to potential industrial implementation. In the present study two dynamic models are constructed, based on the Aiba equation, the improved Lambert–Beer's law and the Arrhenius equation. The aims are to simulate the effects of incident light intensity, light attenuation and temperature upon the photo-autotrophic growth and the hydrogen production of the nitrogen-fixing cyanobacterium Cyanothece sp. ATCC 51142. The results are based on experimental data derived from an experimental setup using two different geometries of laboratory scale photobioreactors: tubular and flat-plate. All of the model parameters are determined by an advanced parameter estimation methodology and subsequently verified by sensitivity analysis. The optimal temperature and light intensity facilitating biohydrogen production in the absence of light attenuation have been determined computationally to be 34 °C and 247 μmol m− 2 s− 1, respectively, whereas for cyanobacterial biomass production they are 37 °C and 261 μmol m− 2 s− 1, respectively. Biomass concentration higher than 0.8 g L− 1 is also demonstrated to significantly enhance the light attenuation effect, which in turn inducing photolimitation phenomena. At a higher biomass concentration (3.5 g L− 1), cyanobacteria are unable to activate photosynthesis to maintain their lives in a photo-autotrophic growth culture, and biohydrogen production is significantly inhibited due to the severe light attenuation

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Dynamic simulation models for cyanobacterial hydrogen production process. Parameter estimation via dynamic optimisation. Proposed modified models exhibit higher accuracy for real process simulation. Interpretation of higher performance of CSTR over PFR for this process. Fed-batch processes are proposed as the optimal reactor operation. a b s t r a c t Cyanothece sp. ATCC 51142 is considered a microorganism with the potential to generate sustainable hydrogen in the future. However, few kinetic models are capable of simulating different phases of Cyanothece sp. ATCC 51142 from growth to hydrogen production. In the present study four models are constructed to simulate Cyanothece sp. batch photoproduction process. A dynamic optimisation method is used to determine parameters in the models. It is found that although the piecewise models fit experimental data better, large deviation can be induced when they are used to simulate a process whose operating conditions are different from the current experiments. The modified models are eventually selected in the present study to simulate a two-stage continuous photoproduction process. The current simulation results show that a plug flow reactor (PFR) shows worse performance compared to a continuous stirred-tank reactor (CSTR) in the current operating conditions since it lowers the total hydrogen production. The finding is that nitrate and oxygen concentration change along the direction of culture movement in PFR, and hydrogen is only generated in the zone where both of them are low. The reactor area thereby is not well utilised. Additionally, as hydrogen production rate is primarily influenced by biomass concentration, which increases initially and decreases eventually along the direction of culture movement, the overall hydrogen production rate in a PFR may be lower than that in a CSTR. Finally, in this study fed-batch photoproduction processes are proposed containing only one photobioreactor based on the current simulation.

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The green alga Chlamydomonas reinhardtii has the ability to produce molecular hydrogen (H 2 ), a clean and renewable fuel, through the biophotolysis of water under sulphur-deprived anaerobic conditions. The aim of this study was to advance the development of a practical and scalable biophotolytic H 2 production process. Experiments were carried out using a purpose-built flat-plate photobioreactor, designed to facilitate green algal H 2 production at the laboratory scale and equipped with a membrane-inlet mass spectrometry system to accurately measure H 2 production rates in real time. The nutrient control method of sulphur deprivation was used to achieve spontaneous H 2 production following algal growth. Sulphur dilution and sulphur feed techniques were used to extend algal lifetime in order to increase the duration of H 2 production. The sulphur dilution technique proved effective at encouraging cyclic H 2 production, resulting in alternating Chlamydomonas reinhardtii recovery and H 2 production stages. The sulphur feed technique enabled photobioreactor operation in chemostat mode, resulting in a small improvement in H 2 production duration. A conceptual design for a large-scale photobioreactor was proposed based on these experimental results. This photobioreactor has the capacity to enable continuous and economical H 2 and biomass production using green algae.The success of these complementary approaches demonstrate that engineering advances can lead to improvements in the scalability and affordability of biophotolytic H 2 production, giving increased confidence that H 2 can fulfil its potential as a sustainable fuel of the future.

Hydrogen produced by microalgae is intensively researched as a potential alternative to conventional energy sources. Scaling-up of the process is still an open issue, and to this end, accurate dynamic modeling is very important. A challenge in the development of these highly nonlinear dynamic models is the estimation of the associated kinetic parameters. This work presents the estimation of the parameters of a revised Droop model for biohydrogen production by Cyanothece sp. ATCC 51142 in batch and fed-batch reactors. The latter reactor type results in an optimal control problem in which the influent concentration of nitrate is optimized which has never been considered previously. The kinetic model developed is demonstrated to predict experimental data to a high degree of accuracy. A key contribution of this work is the prediction that hydrogen productivity can achieve 3365 mL/L through an optimally controlled fed-batch process, corresponding to an increase of 116% over other recently published strategies