Journal of System Simulation
Abstract
Abstract: The high order inertial transfer functions were used to approximate the distribution parameter model. In order to compare the influence of the order of the leading region and the inertia object model on the accuracy and get the dynamic parameters, the multi-objective genetic algorithm was used to optimize the model parameters according to the actual operation data of the power plant. The higher the order, the Pareto front moves forward and recognizes the higher accuracy by the simulation when the orders are in a reasonable range. The reasonable superheated steam temperature system model was established considering the engineering and accuracy requirements.
Recommended Citation
Wu, Zhenlong; He, Ting; Wang, Lingmei; Jia, Fengsheng; Yang, Yunkai; Wu, Haishu; Li, Donghai; and Lei, Han
(2020)
"Modeling and Simulation of Superheated Steam Temperature Based on Multi-objective Genetic Algorithm,"
Journal of System Simulation: Vol. 29:
Iss.
9, Article 27.
DOI: 10.16182/j.issn1004731x.joss.201709027
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol29/iss9/27
First Page
2081
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201709027
Last Page
2086
CLC
TP27
Recommended Citation
Wu Zhenlong, He Ting, Wang Lingmei, Jia Fengsheng, Yang Yunkai, Wu Haishu, Li Donghai, Han Lei. Modeling and Simulation of Superheated Steam Temperature Based on Multi-objective Genetic Algorithm[J]. Journal of System Simulation, 2017, 29(9): 2081-2086.
DOI
10.16182/j.issn1004731x.joss.201709027
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