基于不确定蒸汽需求和设备故障的锅炉系统随机规划设计

doi:10.3969/j.issn.0438-1157.2014.09.028

化工学报 ›› 2014, Vol. 65 ›› Issue (9): 3512-3518.DOI: 10.3969/j.issn.0438-1157.2014.09.028

基于不确定蒸汽需求和设备故障的锅炉系统随机规划设计

刘畅¹, 孙力^1,2, 贺高红¹, 盖丽梅¹

1 大连理工大学精细化工国家重点实验室, 膜科学与技术研究开发中心, 辽宁大连 116024;
2 曼彻斯特大学过程集成中心, 英国曼彻斯特 M13 9PL

收稿日期:2013-12-13 修回日期:2014-03-06 出版日期:2014-09-05 发布日期:2014-09-05
通讯作者: 孙力
基金资助:
国家杰出青年科学基金项目（21125628）；辽宁省科学技术计划项目（2011224005）；中国石油科技创新基金资助项目（2011D-5006-0401）。

Boiler system design based on stochastic programming under uncertain steam demand and equipment failure

LIU Chang¹, SUN Li^1,2, HE Gaohong¹, GAI Limei¹

1 State Key Laboratory of Fine Chemicals, Research and Development Center of Membrane Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China;
2 Centre for Process Integration, School of Chemical Engineering and Analytical Science, University of Manchester, Manchester M13 9 PL, UK

Received:2013-12-13 Revised:2014-03-06 Online:2014-09-05 Published:2014-09-05
Supported by:
supported by the National Science Fund for Distinguished Young Scholars of China (21125628), the Science and Technology Plan Projects of Liaoning Province(2011224005) and China Petroleum Science and Technology Innovation Fund(2011D-5006-0401).

摘要/Abstract

摘要： 公用工程系统中锅炉系统设计不仅要考虑锅炉应对发生的故障的可靠性，还要保证系统具有一定应对蒸汽需求的波动的可操作性。本研究针对满足不确定蒸汽需求和考虑设备故障的锅炉系统设计，提出基于数学规划法的设计模型：对生产过程波动引起的不确定蒸汽需求以概率表达，采用Markov模型分析锅炉故障，表达为以一定概率发生的不确定参数。优化模型采用二阶段随机规划策略对蒸汽需求不确定波动和锅炉故障实现引起的约束违背进行补偿，以降低不确定变量对目标函数和约束条件的影响。以年总费用最小为目标，建立混合整数线性模型（MILP），实现锅炉系统配置，设备模式确定以及应对蒸汽需求波动和设备故障发生的补偿操作的优化设计。

关键词: 不确定性, 两阶段随机规划, 系统工程, 模拟, 优化设计

Abstract: The utility system design would consider the reliability to respond to boiler failure even shut down. The design would ensure system flexibility for the fluctuation of process steam demand as well. In this work, boiler system design was studied considering both the uncertainty of process steam demand and equipment failure based on mathematical programming. Probability distribution was used for fluctuation of process steam demand and the Markov model was used to deal with boiler failure to express uncertain parameter with probability. The approach of two-stage stochastic programming was to compensate the constraint violations caused by uncertain steam demand and boiler failure to reduce the effect on optimization and constraints. A mixed integer linear programming model (MILP) was formulated with the objective of minimum annual cost to design system configuration, equipment modes and operation of compensating flexible steam demand and equipment failure.

Key words: uncertainty, two-stage stochastic programming, systems engineering, simulation, optimal design

中图分类号:

TQ021.8

刘畅, 孙力, 贺高红, 盖丽梅. 基于不确定蒸汽需求和设备故障的锅炉系统随机规划设计[J]. 化工学报, 2014, 65(9): 3512-3518.

LIU Chang, SUN Li, HE Gaohong, GAI Limei. Boiler system design based on stochastic programming under uncertain steam demand and equipment failure[J]. CIESC Journal, 2014, 65(9): 3512-3518.

参考文献 19

[1]	Frangopoulos Christos A, George G Dimopoulos. Effect of reliability considerations on the optimal synthesis, design and operation of a cogeneration system [J]. Energy, 2004, 29 (3): 309-329
[2]	Frank L Del Nogal, Jin-Kuk Kim, Simon Perry, Robin Smith. Synthesis of mechanical driver and power generation configurations (Ⅰ): Optimization framework [J]. AIChE Journal, 2010, 56 (9): 2356-2376
[3]	Smith R, Yin Q, Lin Z, Zheng X. Reliability issues in the design and operation of process utility systems [J]. Chemical Engineering Transactions, 2011, 22:75-80
[4]	Aguilar O. Design and optimisation of flexible utility systems [D]. Manchester: University of Manchester, 2005
[5]	Aguilar O, Kim J K, Perry S, Smith R. Availability and reliability considerations in the design and optimization of flexible utility systems [J]. Chemical Engineering Science, 2008, 63 (14): 3569-3584
[6]	Luo X, Zhang B, Chen Y, Mo S. Operational planning optimization of steam power plants considering equipment failure in petrochemical complex [J]. Applied Energy, 2013, 112:1247-1264
[7]	Yin Q Y. Incorporating reliability, availability and maintainability (RAM) into process synthesis [D]. Manchester: University of Manchester, 2006
[8]	Nabena E. Reliability modeling of utility systems [D]. Manchester: University of Manchester, 2010
[9]	Lin Z. Process reliability, availability and maintainability (RAM) analysis [D]. Manchester: University of Manchester, 2010
[10]	Lin Z, Zheng Z, Smith R, Yin Q. Reliability issues in the design and optimization of process utility systems [J]. Theoretical Foundations of Chemical Engineering, 2012, 46 (6): 747-754
[11]	Madansky A. Inequalities for stochastic linear programming problems [J]. Management Science, 1960, 6 (2): 197-204
[12]	Luo Xianglong (罗向龙), Hua Ben (华贲). Synthesis and design of flexible steam power system [J]. CIESC Journal (化工学报), 2009, 60 (4): 936-944
[13]	Li Hui (李晖), Sun Li (孙力), He Gaohong (贺高红). Design and operation of steam and power system with uncertain steam and power demands [J]. CIESC Journal (化工学报), 2013, 64 (1): 318-325
[14]	Clay R L, Grossmann I E. A disaggregation algorithm for the optimization of stochastic planning models [J]. Computers & Chemical Engineering, 1997, 21 (7): 751-774
[15]	Soroush M, Chmielewski D J. Process systems opportunities in power generation, storage and distribution [J]. Computers & Chemical Engineering, 2013, 51: 86-95
[16]	Huang G H, Loucks D P. An inexact two-stage stochastic programming model for water resources management under uncertainty [J]. Civil Engineering Systems, 2000, 17 (2): 95-118
[17]	Wang J, Shahidehpour M, Li Z. Security-constrained unit commitment with volatile wind power generation [J]. IEEE Transactions on Power Systems, 2008, 23 (3): 1319-1327
[18]	Adarijo-Akindele O, Yang A, Cecelja F, Kokossis A C. A Systems Approach for the Optimal Retrofitting of Utility Networks Under Demand and Market Uncertainties//Handbook of Power Systems I [M]. Springer Berlin Heidelberg, 2010: 293-306
[19]	Shang Z, Kokossis A. A transhipment model for the optimisation of steam levels of total site utility system for multiperiod operation [J]. Computers & Chemical Engineering, 2004, 28 (9): 1673-1688

基于不确定蒸汽需求和设备故障的锅炉系统随机规划设计

Boiler system design based on stochastic programming under uncertain steam demand and equipment failure

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