Lignin valorization process control under feedstock uncertainty through a dynamic stochastic programming approach

Literature Information

Publication Date 2019-07-17
DOI 10.1039/C9RE00176J
Impact Factor 4.239
Authors

Hanxi Bao, Zhiqiang Zhou, Georgios Kotsalis, Guanghui Lan, Zhaohui Tong


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Abstract

The randomness introduced by reactants is an issue when processing renewable bioresources. In this paper, we apply tools from dynamic stochastic programming theory to the biochemical process. Instead of introducing extra preprocessing units, we consider the inherent randomness of the process and optimize in expectation the performance of the system. In a general setting, this is a multistage stochastic optimization problem and we investigate its approximate solution via two approaches, namely stochastic dual dynamic programming (SDDP) and the finite state, finite action Markov decision process (MDP) framework. These two methods are implemented to a case study of lignin valorization that is crucial to a cost-effective biorefinery process using biomass as the feedstock.

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Back matter

Front/Back Matter

DOI: 10.1039/C3CP90004E

Front cover

Cover

DOI: 10.1039/C3CP90018E

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Source Journal

Reaction Chemistry & Engineering

Reaction Chemistry & Engineering
CiteScore: 0
Self-citation Rate: 8.8%
Articles per Year: 284

Reaction Chemistry & Engineering is an interdisciplinary journal reporting cutting-edge research focused on enhancing the understanding and efficiency of reactions. Reaction engineering leverages the interface where fundamental molecular chemistry meets chemical engineering and technology. Challenges in chemistry can be overcome by the application of new technologies, while engineers may find improved solutions for process development from the latest developments in reaction chemistry. Reaction Chemistry & Engineering is a unique forum for researchers whose interests span the broad areas of chemical engineering and chemical sciences to come together in solving problems of importance to wider society. All papers should be written to be approachable by readers across the engineering and chemical sciences. Papers that consider multiple scales, from the laboratory up to and including plant scale, are particularly encouraged.

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