Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4764179 | Chinese Journal of Chemical Engineering | 2017 | 39 Pages |
Abstract
A microbial fuel cell (MFC) is a novel promising technology for simultaneous renewable electricity generation and wastewater treatment. Three non-comparable objectives, i.e. power density, attainable current density and waste removal ratio, are often conflicting. A thorough understanding of the relationship among these three conflicting objectives can be greatly helpful to assist in optimal operation of MFC system. In this study, a multi-objective genetic algorithm is used to simultaneously maximizing power density, attainable current density and waste removal ratio based on a mathematical model for an acetate two-chamber MFC. Moreover, the level diagrams method is utilized to aid in graphical visualization of Pareto front and decision making. Three bi-objective optimization problems and one three-objective optimization problem are thoroughly investigated. The obtained Pareto fronts illustrate the complex relationships among these three objectives, which is helpful for final decision support. Therefore, the integrated methodology of a multi-objective genetic algorithm and a graphical visualization technique provides a promising tool for the optimal operation of MFCs by simultaneously considering multiple conflicting objectives.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Ke Yang, Yijun He, Zifeng Ma,