Optimizing utilization pathways for biomass to chemicals and energy by integrating emergy analysis and particle swarm optimization (PSO). (January 2023)
- Record Type:
- Journal Article
- Title:
- Optimizing utilization pathways for biomass to chemicals and energy by integrating emergy analysis and particle swarm optimization (PSO). (January 2023)
- Main Title:
- Optimizing utilization pathways for biomass to chemicals and energy by integrating emergy analysis and particle swarm optimization (PSO)
- Authors:
- Nimmanterdwong, Prathana
Chalermsinsuwan, Benjapon
Piumsomboon, Pornpote - Abstract:
- Abstract: In this study, emergy analysis has been applied to evaluate and quantify the system performance in terms of natural resource utilization. The Emergy to Money Ratio (EMR) is the performance parameter to be optimized using the Particle Swarm Optimization (PSO) to obtain the optimal use of available resources. A framework, so-called EMR-PSO, has been proposed to determine the minimum EMR, reflecting the low emergy investment with high system net profit. The system boundary consisted of four selected biomass and six alternative conversion processes. The framework was implemented in three scenarios covering feedstocks and product constraints. The optimization result indicated that, in the supply aspect, liquid fuel production from eucalyptus is the optimum solution in the case of normal operation. While eucalyptus availability was limited, Napier grass and PEFB were suggested as alternative substitutes. The minimum EMR from the production system in case of normal operation and high product demand with limited biomass availability were 2.04E+09 sej/$ and 6.77E+09 sej/$, v. Furthermore, the performance of the EMR-PSO was compared with other optimization techniques such as genetic algorithm (EMR-GA) and gradient-based method (EMR-GBM). The EMR-PSO was found to be superior to the others. Graphical abstract: Image 1 Highlights: An EMR-PSO framework based on economic and emergy aspects was proposed. Minimum EMR from emergy analysis was the objective function of processAbstract: In this study, emergy analysis has been applied to evaluate and quantify the system performance in terms of natural resource utilization. The Emergy to Money Ratio (EMR) is the performance parameter to be optimized using the Particle Swarm Optimization (PSO) to obtain the optimal use of available resources. A framework, so-called EMR-PSO, has been proposed to determine the minimum EMR, reflecting the low emergy investment with high system net profit. The system boundary consisted of four selected biomass and six alternative conversion processes. The framework was implemented in three scenarios covering feedstocks and product constraints. The optimization result indicated that, in the supply aspect, liquid fuel production from eucalyptus is the optimum solution in the case of normal operation. While eucalyptus availability was limited, Napier grass and PEFB were suggested as alternative substitutes. The minimum EMR from the production system in case of normal operation and high product demand with limited biomass availability were 2.04E+09 sej/$ and 6.77E+09 sej/$, v. Furthermore, the performance of the EMR-PSO was compared with other optimization techniques such as genetic algorithm (EMR-GA) and gradient-based method (EMR-GBM). The EMR-PSO was found to be superior to the others. Graphical abstract: Image 1 Highlights: An EMR-PSO framework based on economic and emergy aspects was proposed. Minimum EMR from emergy analysis was the objective function of process evaluation. PSO was selected as an optimization method for EMR-PSO framework. Framework implementation could optimize seasonal feedstocks for high productivity. … (more)
- Is Part Of:
- Renewable energy. Volume 202(2023)
- Journal:
- Renewable energy
- Issue:
- Volume 202(2023)
- Issue Display:
- Volume 202, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 202
- Issue:
- 2023
- Issue Sort Value:
- 2023-0202-2023-0000
- Page Start:
- 1448
- Page End:
- 1459
- Publication Date:
- 2023-01
- Subjects:
- Biomass utilization -- Optimization -- Emergy analysis
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2022.12.036 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25223.xml