Event-based predictive control of pH in tubular photobioreactors

A novel data-driven model for prediction and adaptive control of pH in raceway reactor for microalgae cultivation

This work proposes a new data-driven model to estimate and predict pH dynamics in freshwater raceway photobioreactors. The resulting model is based purely on data measured from the reactor and divides the pH dynamics into two different behaviors. One behavior is described by the variation of pH due to the photosynthesis phenomena made by microalgae; and the other comes from the effect of CO2 injections into the medium for control purposes. Moreover, it was observed that the model parameters vary throughout the day depending on the weather conditions and reactor status. Thus, a decision tree algorithm is also developed to capture the parameter variation based on measured variables of the system, such as solar radiation, medium temperature, and medium level. The proposed model has been validated for a data set of more than 100 days during 10 months in a semi-industrial raceway reactor, covering a wide range of weather and system scenarios. Additionally, the proposed model was used to design an adaptive control algorithm which was also experimentally tested and compared with a classical fixed parameter control approach.

A seasonal simulation approach for culture depth influence on the temperature for different characterized microalgae strains

Irradiance and temperature are among the most important variables that affect microalgae growth, being both difficult to control in outdoor raceway reactors utilized for large-scale production of microalgae biomass. They are mainly a function of the location of the reactors, thus, producing certain strains of microalgae in inappropriate places conduces to the failure of the systems. To be able to determine important parameters of any microalgae strains on the performance of the culture, such as the influence of irradiance and temperature, is a powerful tool in decision-making processes. In addition, whatever the strain and location, operation strategies must be defined for each specific case, such as the imposed dilution rate and culture depth, both influencing the light availability and temperature of the culture as major variables determining the biomass productivity. In this paper, a simulation-based methodology is proposed to establish the influence of season and culture depth on the 1-year age irradiance and temperature of the culture, and thus on the biomass productivity of different microalgae strains. Up to five of the most frequently produced strains, such as Spirulina platensis, Chlorella vulgaris, Nannochloropsis gaditana, Isochrysis galbana and Scenedesmus almeriensis have been considered. The challenge is to develop an easy-to-manage decision-making tool for the optimal design and operation of large-scale microalgae facilities. Especially, dates for microalgae production and culture depth at which the reactors must be operated will be provided, being valid for any microalgae strain. The proposed methodology will largely contribute to the risk of investment in this field, then to enlarge the relevance of the microalgae production industry. This article is protected by copyright. All rights reserved.

Diurnal and nocturnal pH control in microalgae raceway reactors by combining classical and event-based control approaches

The pH control in raceway reactors is crucial for an optimal performance of the system. Classical pH control is exclusively performed during the daytime period for cost saving reasons. This paper demonstrates that pH can be controlled 24 hours a day by using both a continuous-based and an event-based control approach, being able to improve the system's performance and reducing costs at the same time. Thus, experimental tests on a raceway reactor for several days are presented to show a comparison between traditional control algorithms during the daytime period versus an event-based control approach operating during both daytime and night-time periods. As a result, the combination of classical PI control for the daytime period and the event-based control for the night-time period is presented as a promising pH control architecture in raceway reactors.

Bioprocess strategies for enhancing the outdoor production of Nannochloropsis gaditana: an evaluation of the effects of pH on culture performance in tubular photobioreactors

A priority of the industrial applications of microalgae is the reduction of production costs while maximizing algae biomass productivity. The purpose of this study was to carry out a comprehensive evaluation of the effects of pH control on the production of Nannochloropsis gaditana in tubular photobioreactors under external conditions while considering the environmental, biological, and operational parameters of the process. Experiments were carried out in 3.0 m³ tubular photobioreactors under outdoor conditions. The pH values evaluated were 6.0, 7.0, 8.0, 9.0, and 10.0, which were controlled by injecting pure CO₂ on-demand. The results have shown that the ideal pH for microalgal growth was 8.0, with higher values of biomass productivity (P_b) (0.16 g L^-1 d^-1), and CO₂ use efficiency ([Formula: see text]) (74.6% w w^-1); [Formula: see text]_/biomass value obtained at this pH (2.42 [Formula: see text] g_biomass^-1) was close to the theoretical value, indicating an adequate CO₂ supply. At this pH, the system was more stable and required a lower number of CO₂ injections than the other treatments. At pH 6.0, there was a decrease in the P_b and [Formula: see text]; cultures at pH 10.0 exhibited a lower P_b and photosynthetic efficiency as well. These results imply that controlling the pH at an optimum value allows higher CO₂ conversions in biomass to be achieved and contributes to the reduction in costs of the microalgae production process.

Daytime/Nighttime Event-Based PI Control for the pH of a Microalgae Raceway Reactor

In this paper, a new solution to improve the traditional control operation of raceway microalgae reactors is presented. The control strategy is based on an event-based method that can be easily coupled to a classical time-driven proportional-integral controller, simplifying the design process approach. The results of a standard Proportional-Integral (PI) controller, as well as of two event-based architectures, are presented in simulation and compared with each other and with traditional On/Off control. It is demonstrated that the event-based PI controller—operating during the whole day instead of only during daytime—achieves a better performance by reducing the actuator effort and saving costs related to gas consumption.

Application of SSOD-PI and PI-SSOD event-based controllers to greenhouse climatic control

In this work, an application of the Symmetric Send-On-Delta (SSOD) event-based controllers to the inside air temperature control of the greenhouse production process is presented. The control technique analysis is split into two stages. The first stage is devoted to determine the proper controller parameters and to check the influence of the Send-On-Delta (SOD) threshold value through simulation study. At the second stage, experimental tests on the real greenhouse facilities are performed. The obtained results show that the analyzed control techniques handle the control task with desired accuracy and performance. In particular, the proposed control system saves costs related with energy consumption and wear minimization, by achieving a satisfactory performance at the same time.

Optimization of carbon dioxide supply in raceway reactors: Influence of carbon dioxide molar fraction and gas flow rate

Influence of CO2 composition and gas flow rate to control pH in a pilot-scale raceway producing Scenedesmus sp. was studied. Light and temperature determined the biomass productivity whereas neither the CO2 molar fraction nor the gas flow rate used influenced it; because pH was always controlled and carbon limitation did not take place. The CO2 molar fraction and the gas flow rate influenced carbon loss in the system. At low CO2 molar fraction (2-6%) or gas flow rate (75-100l·min(-1)) the carbon efficiency in the sump was higher than 95%, 85% of the injected carbon being transformed into biomass. Conversely, at high CO2 molar fraction (14%) or gas flow rate (150l·min(-1)) the carbon efficiency in the sump was lower than 67%, 32% of the carbon being fixed as biomass. Analysis here reported allows the pH control to be optimized and production costs to be reduced by optimizing CO2 efficiency.

Effective utilization of flue gases in raceway reactor with event-based pH control for microalgae culture

This work addresses effective utilization of flue gases through the proper pH control in raceway reactors. The pH control problem has been addressed with an event-based control approach using a Generalized Predictive Controller (GPC) with actuator deadband. Applying this control strategy it is possible to reduce the control effort, and at the same time saving control resources. In the pH process case, the event-based controller with actuator deadband can be tuned to supply only necessary amount of CO2 to keep the pH close to its optimal value. On the other hand, the evaluated control algorithm significantly improves the pH control accuracy, what has a direct influence on biomass production. In order to test the performance of the event-based GPC controller, several experiments have been performed on a real raceway reactor. Additionally, several control performance indexes have been used to compare the analyzed technique with commonly used on/off controller.