Model-based versus model-free control designs for improving microalgae growth in a closed photobioreactor: Some preliminary comparisons

Controlling microalgae cultivation, i.e., a crucial industrial topic today, is a challenging task since the corresponding modeling is complex, highly uncertain and time-varying. A model-free control setting is therefore introduced in order to ensure a high growth of microalgae in a continuous closed photobioreactor. Computer simulations are displayed in order to compare this design to an input-output feedback linearizing control strategy, which is widely used in the academic literature on photobioreactors. They assess the superiority of the model-free standpoint both in terms of performances and implementation simplicity.Comment: The 24th Mediterranean Conference on Control and Automation (MED'16), Athens, Greece (June 21-24, 2016

Adaptive control for optimizing microalgae production

International audienceIn this paper, we propose a nonlinear adaptive controller for light-limited microalgae culture. This controller regulates the light absorption factor, defined by the ratio between the incident light and the light at the bottom of the reactor. Then, we propose a set-point for the light absorption factor which allows to optimize biomass productivity under constant illumination. Finally, we show by numerical simulation that the adaptive controller can be used to obtain near optimal productivity under day-night cycles

Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems

Outdoor biofuel production from microalgae is a complex dynamical process submitted to climatic variations. Controlling and optimizing such a nonlinear process strongly influenced by weather conditions is therefore tricky, but it is crucial to make this process economically sustainable. The strategy investigated in this study uses weather forecast coupled to a detailed predictive model of algal productivity for online optimization of the rates of fresh medium injection and culture removal into and from the pond. This optimization strategy was applied at various climatic conditions and significantly increased productivity compared to a standard operation with constant pond depth and dilution rate, by up to a factor of 2.2 in a Mediterranean climate in summer. A thorough analysis of the optimizer strategy revealed that the increase of productivity in summer was achieved by finding a trade-off between algal concentration to optimally distribute light and pond temperature to get closer to optimal growth temperature. This study also revealed that maintaining the temperature as high as possible is the best strategy to maximize productivity in cold climatic conditions

Análisis del impacto económico de control predictivo basado en modelo económico en fotobiorreactores

In this thesis it was proposed a formulation to evaluate the economic impact of the use of Economic Model Predictive Control (EMPC). For this, a model of a photobioreactor (PBR) was proposed by combining different phenomena within the reactor for the cultivation of microalgae such as: fluid dynamics, photosynthesis kinetics and mass balances. The proposed model has a new characteristic, it is the inclusion of an empirical equation which takes into account the performance of the Light - Dark cycles in a dynamic mathematical model for the predictions of productivity in the PBR. Besides of that, an economic optimization was proposed, which takes into account both the pumping energy of the system and the energy produced, by translating the productivity of biomass to energy, through some expressions proposed in this thesis, this expression combined with the model previously proposed is able to reach optimal regions for the PBR operation in accurate way. Finally, it was found that the economic impact of the use of economic control was positive for the system, due to the fact that its objective function and prediction model take into account not only the productivity of the system, but also the energy costs associated with pumping and mixing.Abstract: En esta tesis se propuso una formulación para evaluar el impacto económico del uso del control predictivo basado en modelo económico (CPBME). Para ello, se propuso un modelo para un fotobiorreactor (FBR) combinando diferentes fenómenos dentro del reactor para el cultivo de microalgas tales como: dinámica de fluidos, cinética de fotosíntesis y balances de materia. El modelo propuesto tiene una nueva característica, esta es la inclusión de una ecuación empírica la cual toma en cuenta el desempeño de los ciclos luz – oscuridad en un modelo matemático de carácter dinámico para las predicciones de la producción en el FBR. De igual forma, se propone una optimización económica, en la cual se tiene en cuenta tanto la energía de bombeo del sistema, como la energía producida, al traducir la productividad de la biomasa a energía, por medio de algunas expresiones propuestas en esta tesis. Al combinar la optimización y el modelo propuesto es posible establecer de forma precisa regiones de funcionamiento óptimo para el sistema de FBR. Finalmente, se encontró que el impacto económico del uso de control económico fue positivo para el sistema, ya que a través de su función objetivo y modelo de predicción se tenía en cuenta no sólo la productividad del sistema, sino también los costos energéticos asociados con el bombeo, agitación y mezclado.Maestrí

Pathways to Water Sector Decarbonization, Carbon Capture and Utilization

The water sector is in the middle of a paradigm shift from focusing on treatment and meeting discharge permit limits to integrated operation that also enables a circular water economy via water reuse, resource recovery, and system level planning and operation. While the sector has gone through different stages of such revolution, from improving energy efficiency to recovering renewable energy and resources, when it comes to the next step of achieving carbon neutrality or negative emission, it falls behind other infrastructure sectors such as energy and transportation. The water sector carries tremendous potential to decarbonize, from technological advancements, to operational optimization, to policy and behavioural changes. This book aims to fill an important gap for different stakeholders to gain knowledge and skills in this area and equip the water community to further decarbonize the industry and build a carbon-free society and economy. The book goes beyond technology overviews, rather it aims to provide a system level blueprint for decarbonization. It can be a reference book and textbook for graduate students, researchers, practitioners, consultants and policy makers, and it will provide practical guidance for stakeholders to analyse and implement decarbonization measures in their professions