Comparison of real-time methods for maximizing power output in microbial fuel cells

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DOIResolve DOI: http://doi.org/10.1002/aic.12157
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TypeArticle
Journal titleAIChE Journal
Volume56
Issue10
Pages27422750; # of pages: 9
Subjectenv; Maximum power point tracking; Real-time optimization; Perturbation and observation method; Microbial fuel cell; Multiunit optimization
AbstractMicrobial fuel cells (MFCs) constitute a novel power generation technology that converts organic waste to electrical energy using microbially catalyzed electrochemical reactions. Since the power output of MFCs changes considerably with varying operating conditions, the online optimization of electrical load (i.e., external resistance) is extremely important for maintaining a stable MFC performance. The application of several real-time optimization methods is presented, such as the perturbation and observation method, the gradient method, and the recently proposed multiunit method, for maximizing power output of MFCs by varying the external resistance. Experiments were carried out in two similar MFCs fed with acetate. Variations in substrate concentration and temperature were introduced to study the performance of each optimization method in the face of disturbances unknown to the algorithms. Experimental results were used to discuss advantages and limitations of each optimization method.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); NRC Biotechnology Research Institute
Peer reviewedYes
NRC number50003
NPARC number16152645
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Record identifiera59982ab-ac0a-4cdd-a652-96bfa8731a6d
Record created2010-11-05
Record modified2016-05-09
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