Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system

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-...

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Main Authors: Holaysan, Sed A.K., Razon, Luis F., Tan, Raymond Girard R.
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Published: Animo Repository 2015
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/3330
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-43262021-05-05T07:27:16Z Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system Holaysan, Sed A.K. Razon, Luis F. Tan, Raymond Girard R. 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. 2015-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/3330 info:doi/10.3303/CET1545272 Faculty Research Work Animo Repository Power-plants--Design and construction Biomass energy industries Algal biofuels Civil and Environmental Engineering Energy Systems
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Power-plants--Design and construction
Biomass energy industries
Algal biofuels
Civil and Environmental Engineering
Energy Systems
spellingShingle Power-plants--Design and construction
Biomass energy industries
Algal biofuels
Civil and Environmental Engineering
Energy Systems
Holaysan, Sed A.K.
Razon, Luis F.
Tan, Raymond Girard R.
Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system
description 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.
format text
author Holaysan, Sed A.K.
Razon, Luis F.
Tan, Raymond Girard R.
author_facet Holaysan, Sed A.K.
Razon, Luis F.
Tan, Raymond Girard R.
author_sort Holaysan, Sed A.K.
title Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system
title_short Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system
title_full Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system
title_fullStr Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system
title_full_unstemmed Development of a modified Luus-Jaakola adaptive random search algorithm for design of integrated algal bioenergy system
title_sort development of a modified luus-jaakola adaptive random search algorithm for design of integrated algal bioenergy system
publisher Animo Repository
publishDate 2015
url https://animorepository.dlsu.edu.ph/faculty_research/3330
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