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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