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Optimizing utilization pathways for biomass to chemicals and energy by integrating emergy analysis and particle swarm optimization (PSO)

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  • Nimmanterdwong, Prathana
  • Chalermsinsuwan, Benjapon
  • Piumsomboon, Pornpote

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.

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  • Nimmanterdwong, Prathana & Chalermsinsuwan, Benjapon & Piumsomboon, Pornpote, 2023. "Optimizing utilization pathways for biomass to chemicals and energy by integrating emergy analysis and particle swarm optimization (PSO)," Renewable Energy, Elsevier, vol. 202(C), pages 1448-1459.
    • Handle: RePEc:eee:renene:v:202:y:2023:i:c:p:1448-1459
    DOI: 10.1016/j.renene.2022.12.036
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    Cited by:

    1. Haoyu Pan & Junhui Gong, 2023. "Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles," Energies, MDPI, vol. 16(14), pages 1-16, July.
    2. Daniel Sanin-Villa & Oscar Danilo Montoya & Walter Gil-González & Luis Fernando Grisales-Noreña & Alberto-Jesus Perea-Moreno, 2023. "Parameter Estimation of a Thermoelectric Generator by Using Salps Search Algorithm," Energies, MDPI, vol. 16(11), pages 1-16, May.

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