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This work focuses on designing the optimum raceway pond by considering the effects of sunlight availability, temperature fluctuations, and harvest time on algae growth, and introduces a dynamic programing model to do so. Culture properties such as biomass productivity, growth rate, and concentration, and physical properties, such as average velocity, pond temperature, and rate of evaporation, were estimated daily depending on the dynamic behavior of solar zenith angle, diurnal pattern of solar irradiance, and temperature fluctuations at the location. Case studies consider two algae species (Phaeodactylum. tricornutum and Isochrysis. galbana) and four locations (Tulsa, USA; Hyderabad, India; Cape Town, South Africa; and Rio de Janeiro, Brazil). They investigate the influences of the type of algae strain and geographical location on algae biomass production costs. From our case studies, the combination of I. galbana species grown in Hyderabad, India, with a raceway pond geometry of 30 cm channel depth, about a meter channel width, and 300 m in length, and a harvest interval of every six days yielded the minimum algal biomass production costs. The results of the sensitivity analysis reveal that smaller channel depths and longer ponds (within the ranges considered) are recommended to minimize the net present cost of algae biomass production.

A Dynamic Optimization Model for Designing Open-Channel Raceway Ponds for Batch Production of Algal Biomass