Ensembles‐based and GA‐based optimization for landfill gas production |
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| Authors: | Hu Li Theodore T. Tsotsis Muhammad Sahimi S. Joe Qin |
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| Affiliation: | Mork Family Dept. of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA |
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| Abstract: | The efficient and economic production of landfill gases (LFG) by optimally adjusting LFG production settings is of high interest as a promising source of biomass energy. A key obstacle in LFG production optimization is the large‐scale and complex system with overwhelming uncertainty and heterogeneity. We propose a simplified ensemble‐based optimization (EnOpt) method to solve the LFG production optimization problem when constraints are not a concern, where the gradient information is obtained from an ensemble of realizations of the system. For constrained optimization, a novel parameterless genetic algorithm is proposed and successfully applied to the simulated LFG process. The effectiveness of the proposed (EnOpt) method and the parameterless genetic algorithm is demonstrated with the simulation of a landfill and gas generation and transport therein, using a parallel computation strategy. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2063–2071, 2014 |
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| Keywords: | landfill gas system production optimization ensemble‐based optimization parallel computation |
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