城市固废焚烧过程的回路控制半实物仿真平台

doi:10.16182/j.issn1004731x.joss.21-1184

摘要/Abstract

摘要：

为精确模拟和实现城市固废焚烧(municipal solid waste incineration，MSWI)过程的多入多出(multiple input multiple output，MIMO)回路控制，面向实际工业过程开发了由真实设备层和虚拟对象层组成的分布式半实物仿真实验平台。结合对MSWI工艺流程机理模型的定性描述，建立了数据驱动的面向回路控制的虚拟过程对象模型，依据回路控制需求设计了该平台的各软件子系统，以及相互间的协同运行模式，搭建了平台硬件和开发了平台软件，并采用工业实际数据进行实验验证。结果表明：该平台为MSWI过程的智能建模与控制算法的进一步研究提供了可靠的工程化验证环境。

关键词: 城市固废焚烧, 半实物仿真平台, 多入多出模型, 回路控制

Abstract:

To accurately simulate and realize the multiple input multiple output (MIMO) loop control of municipal solid waste incineration (MSWI) process, a distributed hardware-in-the-loop simulation platform consisting of a real device layer and a virtual object layer is developed based on the actual industrial process. The mechanism model is qualitatively described, and a data-driven virtual process object model in terms of loop control is established. The software subsystems of the platform and their cooperative operation mode are designed based on the control requirement. The hardware and software of the proposed platform are built and experimentally verified based on actual industrial data. The results show that the platform provides a reliable engineering verification environment for the intelligent modeling and the control algorithm of MSWI process.

Key words: municipal solid waste incineration(MSWI), hardware-in-the-loop simulation platform, multiple input multiple output(MIMO) model, loop control

中图分类号:

TP391.9

王天峥,汤健,夏恒等 . 城市固废焚烧过程的回路控制半实物仿真平台[J]. 系统仿真学报, 2023, 35(2): 241-253.

Tianzheng Wang,Jian Tang,Heng Xia,et al . Hardware-in-the-loop Simulation Platform of Loop Control for Municipal Solid Waste Incineration Process[J]. Journal of System Simulation, 2023, 35(2): 241-253.

图/表 9

图1

图2

图3

图4

图5

图6

表1

表2

图7

参考文献 28

1	Silpa K, Lisa Y, Perinaz B, et al. What a Waste 2.0: a Global Snapshot of Solid Waste Management to 2050[M]. Washington, DC: World Bank, 2018.
2	Kolekar K A, Hazra T, Chakrabarty S N, et al. A Review on Prediction of Municipal Solid Waste Generation Models[J]. Procedia Environmental Sciences(S1878-0296), 2016, 35: 238-244.
3	Harshit K, Hiya D, Arun K T, et al. Application of Life Cycle Assessment in Municipal Solid Waste Management: A Worldwide Critical Review[J]. Journal of Cleaner Production(S0959-6526), 2019, 209: 630-654.
4	Zhou X, Zhou P, Zhao X Q, et al. Applicability of Municipal Solid Waste Incineration(MSWI) System Integrated with Pre-drying or Torrefaction for Flue Gas Waste Heat Recovery[J]. Energy(S0360-5442), 2021, 224: 120157.
5	Audrius V, Judita G, Ovidijus Š, et al. An Algorithm for the Use of MSWI Bottom Ash as a Building Material in Road Pavement Structural Layers[J]. Construction and Building Materials(S0950-0618), 2019, 212(10): 456-466.
6	乔俊飞, 郭子豪, 汤健. 面向城市固废焚烧过程的二噁英排放浓度检测方法综述[J]. 自动化学报, 2020, 46(6): 1063-1089.
	Qiao Junfei, Guo Zihao, Tang Jian. Dioxin Emission Concentration Measurement Approaches for Municipal Solid Wastes Incineration Process: A Survey[J]. Acta Automatica Sinica, 2020, 46(6): 1063-1089.
7	Liu Y L, Xing P X, Liu J G, et al. Environmental Performance Evaluation of Different Municipal Solid Waste Management Scenarios in China[J]. Resources, Conservation and Recycling(S0921-3449), 2017, 125: 98-106.
8	Zhang D Q, Soon K T, Richard M. G. Municipal Solid Waste Management in China: Status, Problems and Challenges[J]. Journal of Environmental Management(S0301-4797), 2010, 91(8): 1623-1633.
9	秦宇飞. 大型城市生活垃圾焚烧炉焚烧过程仿真及控制[D]. 北京: 华北电力大学, 2011.
	Qin Yufei. Modeling and Control of Municipal Solid Waste Incineration Process in Large Scale Mechanical Grate-fired Boiler[D]. Beijing: North China Electric Power University, 2011.
10	Hu Y A, Cheng H F, Tao S. The Growing Importance of Waste-to-Energy(WTE) Incineration in China's Anthropogenic Mercury Emissions: Emission Inventories and Reduction Strategies[J]. Renewable and Sustainable Energy Reviews(S1364-0321), 2018, 97: 119-137.
11	Huang Tao, Zhou Lulu, Liu Longfei, et al. Ultrasound-enhanced Electrokinetic Remediation for Removal of Zn, Pb, Cu and Cd in Municipal Solid Waste Incineration Fly Ashes[J]. Waste Management(S0956-053X), 2018, 75: 226-235.
12	Lu J W, Zhang S K, Hai J, et al. Status and Perspectives of Municipal Solid Waste Incineration in China: A Comparison with Developed Regions[J]. Waste Management(S0956-053X), 2017, 69: 170-186.
13	汤健, 夏恒, 乔俊飞, 等. 深度集成森林回归建模方法及应用[J]. 北京工业大学学报, 2021, 47(11): 1219-1229.
	Tang Jian, Xia Heng, Qiao Junfei, et al. Modeling Method of Deep Ensemble Forest Regression with Its Application[J]. Journal of Beijing University of Technology, 2021, 47(11): 1219-1229.
14	Zheng L J, Song J C, Li C Y, et al. Preferential Policies Promote Municipal Solid Waste (MSW) to Energy in China: Current Status and Prospects[J]. Renewable & Sustainable Energy Reviews(S1364-0321), 2014, 36(C): 135-148.
15	王克, 张世红, 付哲, 等. 垃圾炉排焚烧炉的富氧燃烧改造数值模拟研究[J]. 太阳能学报, 2016, 37(9): 2257-2264.
	Wang Ke, Zhang Shihong, Fu Zhe, et al. Numerical Simulation Research for the Oxyfuel Combustion Renovation of a MSW Grate Incinerator[J]. Acta Energiae Solaris Sinica, 2016, 37(9): 2257-2264.
16	Wang J F, Xue Y Q, Zhang X X, et al. Numerical Study of Radiation Effect on the Municipal Solid Waste Combustion Characteristics Inside an Incinerator[J]. Waste Management(S0956-053X), 2015, 44: 116-124.
17	Elisa M, Olaf L T, Per C, et al. Dynamic Modeling of Municipal Solid Waste Incineration[J]. Energy(S0360-5442,), 2020, 209: 118426.
18	Mahlia T M I, Abdulmuin M Z, Alamsyah T M I, et al. Dynamic Modeling and Simulation of a Palm Wastes Boiler[J]. Renew Energy(S0960-1481), 2003, 28(8): 1235-1256.
19	Falah A, Wisam A K, Thomas L, et al. Dynamic Simulation of A Municipal Solid Waste Incinerator[J]. Energy(S0360-5442), 2018, 149: 230-249.
20	秦宇飞, 白焰, 张菊军, 等. 垃圾焚烧发电厂环境监测系统的设计与实现[J]. 热力发电, 2010, 39(10): 89-91.
	Qin Yufei, Bai Yan, Zhang Jujun, et al. Design and Realization of Environment Monitoring System for MSW Incineration Power Plant[J]. Thermal Power Generation, 2010, 39(10): 89-91.
21	严爱军, 夏恒, 刘溪芷. 城市生活垃圾焚烧过程监控半实物仿真平台研发[J]. 系统仿真学报, 2021, 33(6): 1427-1435.
	Yan Aijun, Xia Heng, Liu Xizhi. Development of Semi-physical Simulation Platform for Monitoring Municipal Solid Waste Incineration Process[J]. Journal of System Simulation, 2021, 33(6): 1427-1435.
22	马平, 王凯宸, 李紫君. 基于半实物仿真平台的温度控制系统设计[J]. 实验科学与技术, 2017, 15(5): 10-14.
	Ma Ping, Wang Kaichen, Li Zijun. Design of Temperature Control System Using Semi-physical Simulation Platform[J]. Experiment Science and Technology, 2017, 15(5): 10-14.
23	赵珊珊, 白焰, 黄从智. 化学水处理系统的半物理仿真[J]. 化工自动化及仪表, 2010, 37(1): 79-84.
	Zhao Shanshan, Bai Yan, Huang Congzhi. Semi-physical Simulation of Chemical Water Treatment System[J]. Control and Instruments in Chemical Industry, 2010, 37(1): 79-84.
24	汤健, 柴天佑, 片锦香, 等. 工业过程智能优化控制半实物仿真实验平台[J]. 东北大学学报(自然科学版), 2009, 30(11): 1530-1533.
	Tang Jian, Chai Tianyou, Jinxiang Pian, et al. A Hardware-in-the-loop Simulation Platform for Optimized Intelligent Control of Industrial Process[J]. Journal of Northeastern University (Natural Science), 2009, 30(11): 1530-1533.
25	杜胜, 吴敏, 陈略峰, 等. 基于粒度聚类的铁矿石烧结过程运行性能评价[J/OL]. 自动化学报, (2020-09-18) [2021-12-03]. .
	Du Sheng, Wu Min, Chen Luefeng, et al. Operating Performance Assessment Based on Granular Clustering for Iron Ore Sintering Process[J/OL]. Acta Automatica Sinic, (2020-09-18) [2021-12-03]. .
26	常玉清, 孙雪婷, 钟林生, 等. 基于改进随机森林算法的工业过程运行状态评价[J]. 自动化学报, 2021, 47(9): 2214-2225.
	Chang Yuqing, Sun Xueting, Zhong Linsheng, et al. Industrial Operation Performance Evaluation of Industrial Processes Based on Modified Random Forest[J]. Acta Automatica Sinica, 2021, 47(9): 2214-2225.
27	程泽凯, 闫小利, 程旺生, 等. 基于梯度提升决策树的焦炭质量预测模型研究[J]. 重庆工商大学学报(自然科学版), 2021, 38(5): 55-60.
	Cheng Zekai, Yan Xiaoli, Cheng Wangsheng, et al. Research on Coke Quality Prediction Model Based on Gradient Boosting Decision Tree[J]. Journal of Chongqing Technology and Business University(Natural Science Edition), 2021, 38(5): 55-60.
28	谢少捷, 王伟, 何福善. 基于梯度提升决策树的特征筛选与钢卷力学性能预测[J]. 机械工程材料, 2021, 45(10): 104-110.
	Xie Shaojie, Wang Wei, He Fushan. Feature Selection and Prediction of Mechanical Properties of Steel Coils Based on Gradient Boosting Decision Tree[J]. Materials for Mechanical Engineering, 2021, 45(10): 104-110.

序号	标签名	取值	序号	标签名	取值
1	进料器左内侧速度	30%	18	燃烬炉排右侧速度	20%
2	进料器左外侧速度	100%	19	干燥炉排左1段挡板开度	100%
3	进料器右内侧速度	30%	20	燃烧炉排左1-2段挡板开度	58.2%
4	进料器右外侧速度	30%	21	燃烧炉排左2-1段挡板开度	31.7%
5	干燥炉排左内侧速度	20%	22	燃烧炉排左2-2段挡板开度	26.1%
6	干燥炉排左外侧速度	20%	23	燃烬炉排左段挡板开度	18.8%
7	干燥炉排右内侧速度	30%	24	干燥炉排右1段挡板开度	100%
8	干燥炉排右外侧速度	30%	25	燃烧炉排右1-1段挡板开度	100%
9	燃烧炉排1段左内侧速度	90%	26	燃烧炉排右1-2段挡板开度	55%
10	燃烧炉排1段左外侧速度	90%	27	燃烧炉排右2-1段挡板开度	30.1%
11	燃烧炉排1段右内侧速度	90%	28	燃烧炉排右2-2段挡板开度	24.4%
12	燃烧炉排1段右外侧速度	90%	29	燃烬炉排右段挡板开度	23.6%
13	燃烧炉排2段左内侧速度	100%	30	二次风流量/(km³N/h)	5.3
14	燃烧炉排2段左外侧速度	100%	31	一次空气加热器出口空气温度/℃	143
15	燃烧炉排2段右内侧速度	100%	32	燃烧段炉排进口空气温度/℃	201
16	燃烧炉排2段右外侧速度	100%	33	干燥段炉排进口空气温度/℃	189
17	燃烬炉排左侧速度	20%	34	二次空气加热器出口空气温度/℃	13

回路	SV	KP	KI
FT	970.0	10.0	0
OC	7.8	10.0	0
BSF	74.0	8.5	0.2

[1]	黄涛, 张智, 丁玉杰, 陈艳波, 王晶, 张文倩. 考虑动态频率安全与N-k故障的鲁棒应急调度方法[J]. 系统仿真学报, 2025, 37(12): 2981-2993.
[2]	张润昭, 陈艳波, 黄涛, 田昊欣, 强涂奔, 张智. 基于异构负荷特征解析预测的虚拟电厂调度方法[J]. 系统仿真学报, 2025, 37(12): 2994-3006.
[3]	于祥星, 赵艳东, 张宝琳. 基于电涡流NES的海上风机塔架振动控制[J]. 系统仿真学报, 2025, 37(12): 3007-3017.
[4]	李斌, 王于绰. 基于多策略融合的光伏系统故障诊断方法[J]. 系统仿真学报, 2025, 37(12): 3018-3032.
[5]	李孝斌, 胡冰, 尹超, 李波, 马军. 基于时空图卷积的汽车配件供应链需求预测与仿真分析[J]. 系统仿真学报, 2025, 37(12): 3060-3074.
[6]	彭艺, 雷云揆, 杨青青, 李辉, 王健明. 改进PID搜索算法的山地环境无人机路径规划[J]. 系统仿真学报, 2025, 37(12): 3075-3086.
[7]	陈逸, 邱思航, 朱正秋, 季雅泰, 赵勇, 鞠儒生. 基于启发式的人-大模型协作寻源方法[J]. 系统仿真学报, 2025, 37(12): 3112-3127.
[8]	索婧怡, 卢柏宏, 屈澈. 影视LED光源光强分布测定及其在游戏引擎中的仿真研究[J]. 系统仿真学报, 2025, 37(12): 3140-3151.
[9]	龚建兴, 胡海, 任海慧, 吴瑞祥. 面向虚实结合的军事训练系统互操作模型与运用[J]. 系统仿真学报, 2025, 37(12): 3161-3175.
[10]	徐智霞, 王蕊, 孙楠, 何兵, 沈晓卫, 朱晓菲. 基于改进遗传算法的协同干扰资源分配问题研究[J]. 系统仿真学报, 2025, 37(12): 3176-3189.
[11]	刘翔, 金乾坤. 基于PAC-Bayes的多目标强化学习A2C算法研究[J]. 系统仿真学报, 2025, 37(12): 3212-3223.
[12]	杨兰英, 李超, 邹海锋, 万江涛, 张仁强, 刘惠, 卢宏. 基于改进蚁群算法与A*算法相融合的机器人路径规划优化[J]. 系统仿真学报, 2025, 37(11): 2956-2965.
[13]	苏筱婷, 张小威, 田义, 李奇, 王帅豪. 星光导航动态仿真场景时序设计方法研究[J]. 系统仿真学报, 2025, 37(11): 2946-2955.
[14]	张志利, 刘瑾, 周召发, 梁哲, 张云昊. 基于ISCSO-BP神经网络模型的光纤陀螺温度补偿技术研究[J]. 系统仿真学报, 2025, 37(11): 2904-2917.
[15]	陈际同, 周佳加, 吴迪, 江海龙. 基于TD3-RRT的特殊环境下USV路径规划算法研究[J]. 系统仿真学报, 2025, 37(11): 2888-2903.