Modeling and Optimization of Algae Growth

Abstract

Microalgae is a promising source of renewable biofuels, and optimization and control of the biomass growth stage can make techno-economic improvements. This work explores the development of an algae growth model from first-principles, which includes the impact of natural vagaries of weather (and such) associated with production in an open system. Consequently, the process simulation is stochastic as well as fundamental; it returns a distribution of results representing the day-to-day realizations from natural variability. It also expresses day-to-night variation in the cycling solar energy. The simulation is then used to optimize pond design and management (the growth time, raceway depth, pH control, etc.) to improve profitability. Since the simulation is stochastic, nonlinear, and with multiple optima, a multiplayer direct search optimization technique with steady state convergence criteria is used for optimization. Conclusions are that (1) accounting for natural variation in the optimization leads to noticeable improvement in profitability, (2) sensitivity analysis of the model reveals where fundamental science research is needed to underpin critical techno-economic phenomena, and (3) the stochastic optimization approach has wide ranging applicability.

Quantifying photosynthetic performance of phytoplankton based on photosynthesis–irradiance response models

“…In phytoplankton, some classical models describing the P-I curves were developed by Webb et al [18], Platt et al [19][20][21] and Eilers and Peeters [22], respectively. Later, some mechanistic models characterizing P-I curves with considering the underlying biophysical processes of photosynthesis were mainly used to investigate properties of photosynthetic physiology for phytoplankton [23][24][25][26][27][28], for example, photoinhibition, photoacclimation and dynamic down-regulation of photosynthesis. However, most of mechanistic models have many parameters and complex relationship between photosynthetic rate and irradiance.…”

Investigation and modelling of high rate algal ponds utilising secondary effluent at Western Water, Bacchus Marsh Recycled Water Plant

“…The Monod model has previously been used to describe the algal growth rate based on nutrient levels and is described in equation 2 (Wu et al 2013, Béchet et al 2015, Jayaraman and Rhinehart 2015.…”

“…These models tend to be species specific and less reliable for ambient open HRAPs that contain numerous species. In general, most models focus on one or two growth aspects, such as light and temperature, and the models are proven to be useful in a controlled laboratory setting (Jayaraman andRhinehart 2015, Undurraga et al 2016). However, they are less applicable to large-scale open ponds due to fluctuations in weather, nutrient concentrations and microalgal species.…”

Sustainability Research Project: Research of Suitable Locations, Design and Operation of Microalgae Production Plants for Biofuel’s

“…The oil content of microalgae can be very high which is one of its many features that have attracted scientist and engineers alike to continue research and development of this technology. Oil content of some microalgae can be as high as 90% of dry biomass weight under extreme growth conditions, and the potential high oil content and dense biomass makes algae an interesting renewable fuel source [6] …”

“…Algae grown in an open system is prone to various environmental uncertainties like temperature fluctuation, weather change, consumption of the nutrients by other organisms in the pond, and stray pathogens [6] (Jayaraman S. K. & Rhinehart R. R. 2015). Closed systems (photobioreactors) have been developed recently by the Japanese, French and German governments offering better control of the environment but higher development and operational cost but can return better yields.…”