Fertilizer assisted optimal cultivation of microalgae using response surface method and genetic algorithm for biofuel feedstock. (15th November 2016)

• Record Type: Journal Article
• Authors: Banerjee, Avik; Guria, Chandan; Maiti, Subodh K.
• Is Part Of: Energy. Volume 115(2016)Part 1
• Page Start: 1272
• Page End: 1290
• Publication Date: 2016-11-15
• Subjects: Microalgae-biomass -- Nannochloropsis sp. -- Fertilizer -- Response surface method -- Genetic algorithm -- Multi-objective optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.09.066
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Fertilizer based culture medium is formulated for the cultivation of Nannochloropsis sp. by selecting appropriate environmental parameters and nutrients. The influences of light intensity, temperature, NaCl, NaHCO3 and fertilizer are investigated on biomass, lipid and eicosapentaenoic acid productivity. Five-level-five-factor central composite design assisted response surface method is used for optimal cultivation of microalgae and results are compared with the genetic algorithm. A significant improvement in biomass, lipid and eicosapentaenoic acid productivity is obtained from the optimally formulated fertilizer medium using genetic algorithm over response surface method based fertilizer medium and standard culture medium. Using simple genetic algorithm, following optimal parameters, i.e., light intensity (μmol m −2 s −1 ), temperature (°C), NaCl (M), NaHCO3, (g L −1 ) and fertilizer (g L −1 ) are obtained for the maximum productivity of biomass (0.77 g L −1 ), lipid (47.91% of biomass) and eicosapentaenoic acid (26.67% of lipid): (125, 24.28, 0.55, 1.09, 1.07), (118, 21.79, 0.50, 1.13, 1.04) and (87.5, 17, 0.25, 1.09, 1.07), respectively. Two different multi-objective optimization problems are formulated and solved using elitist non-dominated sorting genetic algorithm to find the optimum operating variables resulting characteristic Pareto optimal solutions. Effects of the variables and their interactions on Nannochloropsis sp. cultivation, lipid and eicosapentaenoic acid productivity are successfully revealed. Highlights: Nannochloropsis sp. is cultivated using nitrogen-phosphorous-potassium fertilizer. Optimal cultivation medium is formulated using response surface method. Genetic algorithm is used to maximize algal productivity. Multi-objective optimization is carried out to maximize biofuel feedstock. Enhancement of biomass, lipid and ω-3 fatty acid productivity is achieved.