Literature DB >> 25305644

Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming.

Santiago García-Gen1, Jorge Rodríguez2, Juan M Lema1.   

Abstract

Anaerobic co-digestion of multiple substrates has the potential to enhance biogas productivity by making use of the complementary characteristics of different substrates. A blending strategy based on a linear programming optimisation method is proposed aiming at maximising COD conversion into methane, but simultaneously maintaining a digestate and biogas quality. The method incorporates experimental and heuristic information to define the objective function and the linear restrictions. The active constraints are continuously adapted (by relaxing the restriction boundaries) such that further optimisations in terms of methane productivity can be achieved. The feasibility of the blends calculated with this methodology was previously tested and accurately predicted with an ADM1-based co-digestion model. This was validated in a continuously operated pilot plant, treating for several months different mixtures of glycerine, gelatine and pig manure at organic loading rates from 1.50 to 4.93 gCOD/Ld and hydraulic retention times between 32 and 40 days at mesophilic conditions.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  ADM1; Anaerobic co-digestion; Biogas; Linear programming; Optimisation

Mesh:

Year:  2014        PMID: 25305644     DOI: 10.1016/j.biortech.2014.09.089

Source DB:  PubMed          Journal:  Bioresour Technol        ISSN: 0960-8524            Impact factor:   9.642


  2 in total

1.  Effects of waste sources on performance of anaerobic co-digestion of complex organic wastes: taking food waste as an example.

Authors:  Xingang Lu; Wengang Jin; Shengrong Xue; Xiaojiao Wang
Journal:  Sci Rep       Date:  2017-11-16       Impact factor: 4.379

2.  Comparison of Optimisation Algorithms for Centralised Anaerobic Co-Digestion in a Real River Basin Case Study in Catalonia.

Authors:  David Palma-Heredia; Marta Verdaguer; Vicenç Puig; Manuel Poch; Miquel Àngel Cugueró-Escofet
Journal:  Sensors (Basel)       Date:  2022-02-26       Impact factor: 3.576

  2 in total

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