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

Anaerobic digestion (AnD) is a process that allows the conversion of organic waste into a source of energy such as biogas, introducing sustainability and circular economy in waste treatment. AnD is an intricate process because of multiple parameters involved, and its complexity increases when the wa...

Full description

Saved in:
Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-02, Vol.22 (5), p.1857
Main Authors: Palma-Heredia, David, Verdaguer, Marta, Puig, Vicenç, Poch, Manuel, Cugueró-Escofet, Miquel Àngel
Format: Article
Language:English
Subjects:
Algorithms
anaerobic co-digestion
Anaerobic digestion
Anaerobic processes
Anaerobiosis
ant colony optimisation
Biogas
Biomass energy
Case studies
circular economy
Climate change
Combinatorial analysis
Comparative analysis
Digestion
Energy sources
Environmental sustainability
Evolutionary algorithms
Genetic algorithms
Geographic information systems
Logistics
particle swarm optimisation
Process parameters
Refuse and refuse disposal
River basins
Rivers
Spain
waste management
Waste treatment
Water treatment
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Anaerobic digestion (AnD) is a process that allows the conversion of organic waste into a source of energy such as biogas, introducing sustainability and circular economy in waste treatment. AnD is an intricate process because of multiple parameters involved, and its complexity increases when the wastes are from different types of generators. In this case, a key point to achieve good performance is optimisation methods. Currently, many tools have been developed to optimise a single AnD plant. However, the study of a network of AnD plants and multiple waste generators, all in different locations, remains unexplored. This novel approach requires the use of optimisation methodologies with the capacity to deal with a highly complex combinatorial problem. This paper proposes and compares the use of three evolutionary algorithms: ant colony optimisation (ACO), genetic algorithm (GA) and particle swarm optimisation (PSO), which are especially suited for this type of application. The algorithms successfully solve the problem, using an objective function that includes terms related to quality and logistics. Their application to a real case study in Catalonia (Spain) shows their usefulness (ACO and GA to achieve maximum biogas production and PSO for safer operation conditions) for AnD facilities.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22051857