Comparison of Real-Time Methods for Maximizing Power Output in Microbial Fuel Cells

Comparison of Real-Time Methods for Maximizing Power Output in Microbial Fuel Cells

Comparison of Real-Time Methods for Maximizing Power Output in Microbial Fuel Cells

Microbial 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.
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