The accuracy and efficiency of GA and PSO optimization schemes on estimating reaction kinetic parameters of biomass pyrolysis

Reaction kinetic parameters estimation of biomass pyrolysis is a relatively difficult optimization problem due to the complexity of pyrolysis model. Two common heuristic algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), are applied to estimate the kinetic parameters of three-...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Energy (Oxford) Ročník 176; s. 582 - 588
Hlavní autori: Ding, Yanming, Zhang, Wenlong, Yu, Lei, Lu, Kaihua
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Elsevier Ltd 01.06.2019
Elsevier BV
Predmet:
Algorithms
Biomass
Biomass pyrolysis
Cellulose
Convergence
Genetic algorithms
Hemicellulose
Kinetic parameters
Lignin
Optimization scheme
Parameter estimation
Particle swarm optimization
PSO
Pyrolysis
Reaction mechanisms
system optimization
thermogravimetry
GA
Kinetic parameters
PSO
Optimization scheme
Biomass pyrolysis
ISSN:0360-5442, 1873-6785
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Reaction kinetic parameters estimation of biomass pyrolysis is a relatively difficult optimization problem due to the complexity of pyrolysis model. Two common heuristic algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), are applied to estimate the kinetic parameters of three-component parallel reaction mechanism based on the thermogravimetric experiment in wide heating rates. The accuracy and efficiency of GA and PSO algorithms are compared with each other under the identical optimization conditions. The results indicate the better optimization abilities of PSO with the closer convergence solution to the global optimum and quicker convergence to the solution than GA based on the three-component parallel reaction mechanism of biomass pyrolysis. Especially, the improvement of best fitting value of PSO reaches up to 30% compared with that of GA. Furthermore, 14 estimated kinetic parameters of best fitting value are obtained and the mass loss rate predicted results including three separate components (hemicellulose, cellulose and lignin) are compared with experimental data. •PSO and GA are compared in the application of biomass pyrolysis.•PSO represents better optimization abilities with the improvement of 30% than GA.•The estimated kinetic parameters of best fitting value are obtained.•Predicted mass loss rates of GA fail in the accuracy of shoulder region.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2019.04.030