Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system
College
Gokongwei College of Engineering
Department/Unit
Chemical Engineering
Document Type
Article
Source Title
Chemical Engineering Transactions
Volume
45
First Page
1627
Last Page
1632
Publication Date
1-1-2015
Abstract
Copyright © 2015, AIDIC Servizi S.r.l.,. Process systems engineering (PSE) approaches are useful for facilitating the optimal design and operation of industrial plants. This study develops a modified Luus-Jaakola adaptive random search (LJ-ARS) procedure by incorporating some features from the line-up competition algorithm (LCA). The search procedure is conducted using multiple points, and cooperation is exhibited as each point moves toward the next-best point to improve its position. The search space of each point is influenced by its rank, but a lower limit for the space reduction factor is specified to prevent premature convergence. A probabilistic roundingoff procedure is used for integer variables, while the penalty function approach is used for constraint resolution. This modified algorithm is encoded in Microsoft Excel and Visual Basic for Applications and is used to optimize a mixed-integer nonlinear programming model of an integrated algal bioenergy system, while the original LJ-ARS is unable to locate a feasible solution. The model considers six processes: cultivation of the microalgae Chlorella vulgaris, dewatering, cell disruption, pretreatment, oil extraction, and transesterification. The optimal solution, which has been verified using LINGO 14.0, involves microfiltration (for dewatering) and oven drying, but does not utilize any cell disruption process due to high capital cost and energy requirement. This implies that if residual biomass can be sold, it may be more economical to cultivate more algae than to increase the oil yield by means of cell disruption. Furthermore, it is essential to utilize the residual biomass to ensure that the system produces more energy than it consumes. Finally, it is more economical to use residual biomass to supply energy rather than to sell the residual biomass while purchasing electricity.
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Digitial Object Identifier (DOI)
10.3303/CET1545272
Recommended Citation
Holaysan, S. A., Razon, L. F., & Tan, R. R. (2015). Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system. Chemical Engineering Transactions, 45, 1627-1632. https://doi.org/10.3303/CET1545272
Disciplines
Civil and Environmental Engineering | Energy Systems
Keywords
Power-plants--Design and construction; Biomass energy industries; Algal biofuels
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