Modeling and Simulation of Superheated Steam Temperature Based on Multi-objective Genetic Algorithm

doi:10.16182/j.issn1004731x.joss.201709027

Journal of System Simulation ›› 2017, Vol. 29 ›› Issue (9): 2081-2086.doi: 10.16182/j.issn1004731x.joss.201709027

Previous Articles Next Articles

Modeling and Simulation of Superheated Steam Temperature Based on Multi-objective Genetic Algorithm

Wu Zhenlong¹, He Ting¹, Wang Lingmei², Jia Fengsheng³, Yang Yunkai⁴, Wu Haishu⁴, Li Donghai^1*, Han Lei²

1. State Key Laboratory of Thermal Power System, Tsinghua University, Beijing 100084, China;
2. School of Engineering, Shanxi University, Taiyuan 030013, China;
3. State Grid Shanxi Electric Power Research Institute, Taiyuan 030001, China;
4. Datong Coal Mine Group Tongda Thermal Power Co., Ltd., Datong 037001, China

Received:2017-05-20 Published:2020-06-02

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.

Key words: superheated steam temperature model, cascade system, multi-objective genetic algorithm, Pareto optimal solution set

CLC Number:

TP27

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.

References

[1] 刘吉臻, 曾德良, 田亮, 等. 新能源电力消纳与燃煤电厂弹性运行控制策略[J]. 中国电机工程学报, 2015, 35(21): 5385-5394.
(Liu Jizhen, Zeng Deliang, Tian Liang, et al.Control strategy for operating flexibility of coal-fired power plants in alternate electrical power systems[J]. Proceedings of the CSEE, 2015, 35(21): 5385-5394.)
[2] 王传峰, 李东海, 姜学智, 等. 基于概率鲁棒性的锅炉过热汽温串级PID控制器[J]. 清华大学学报(自然科学版), 2009, 49(2): 249-252.
(Wang Chuanfeng, Li Donghai, Jiang Xuezhi, et al.Cascade PID controllers for superheated steam boiler temperatures based on probabilistic robustness[J]. Journal of Tsinghua University (Science and Technology), 2009, 49(2): 249-252.
[3] Wu Z, Li D, Wang L.Control of the Superheated Steam Temperature: A Comparison Study Between PID and Fractional Order PID Controller[C]// Control Conference (CCC), 2016 35th Chinese. USA: IEEE, 2016: 10521-10526.
[4] 范永胜, 徐治皋. 基于动态特性机理分析的锅炉过热汽温自适应模糊控制系统研究[J]. 中国电机工程学报, 1997, 17(1): 23-28.
(Fan Yongsheng, Xu Zhigao.Study of Adaptive Fuzzy Control of Boiler Superheated Steam Temperature Based on Dynamic Mechanism Analysis[J]. Proceedings of the CSEE, 1997, 17(1): 23-28.)
[5] Wen X, Jian S.Modeling of Main Steam Parameters in Large Thermal Power Plant [C]// MATEC Web of Conferences. EDP Sciences. Paris, France: Atlantis Press, 2016, 77: 02011.
[6] Wang D, Yuan S.Identification of LPV Model for Superheated Steam Temperature System Using A-QPSO[J]. Simulation Modelling Practice and Theory (S1569-190X), 2016, 69(1): 1-13.
[7] Jiao S, He L, Wang Z, et al.Main Steam Temperature System Modeling Based on PCA and Neural Networks[C]// Computational Intelligence and Design, 2008. ISCID'08, International Symposium on. USA: IEEE, 2008, 1: 303-308.
[8] Deb K, Pratap A, Agarwal S, et al.A Fast and Elitist Multi-objective Genetic Algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation (S1089-778X), 2002, 6(2): 182-197.
[9] Liu X, Li D, Jiang X, et al.Simulation Study of Auto-disturbance-rejection Controller for High-order Systems[J]. Journal-Tsinghua University (S1007-0214), 2001, 41(6): 95-99.
[10] Blasco X, Herrero J, Sanchis J, et al.A New Graphical Visualization of N-dimensional Pareto Front for Decision-making in Multi-objective Optimization[J]. Information Science (S0020-0255), 2008, 178(20): 3908-3924.

Modeling and Simulation of Superheated Steam Temperature Based on Multi-objective Genetic Algorithm

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 3

Recommended Articles

Metrics

Comments

[1]	Liu Yanbin, Wang Yawei, Han Jianhai. Analysis and Optimization of MR Damper Based on Parallel of Positive and Negative Stiffness [J]. Journal of System Simulation, 2018, 30(10): 3965-3975.
[2]	Li Suike, Xiang Jianhua, Wang Haijun, Zhang Mingzhi, Li Yi. Target Combination Selection Optimization Method of Joint Operations based on Fuzzy Genetic algorithm [J]. Journal of System Simulation, 2017, 29(10): 2254-2261.
[3]	Yang Yunfei, Gu Yan, Fan Xiumin, He Qichang, Qiu Shiguang. A Research of Virtual Human Assembly Intelligent Simulation Technology [J]. Journal of System Simulation, 2015, 27(10): 2320-2327.