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; 孙力; 贺高红; 盖丽梅

doi:10.3969/j.issn.0438-1157.2014.09.028

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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

过程系统工程 | 更新时间：2025-12-10

- 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
- 化工学报 2014年第9期页码：3512-3518
- 作者机构：
  
  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 M12.9PL
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0438-1157.2014.09.028
  中图分类号： Q021.8
- 网络首发：2014-09-05，
  
  纸质出版：2014-09-05
- 稿件说明：
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刘畅, 孙力, 贺高红, 等. 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,(9):3512-3518.

LIU Chang, SUN Li, HE Gaohong, et al. Boiler system design based on stochastic programming under uncertain steam demand and equipment failure[J]. CIESC Journal, 2014, (9): 3512-3518.
刘畅, 孙力, 贺高红, 等. 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,(9):3512-3518. DOI： 10.3969/j.issn.0438-1157.2014.09.028.

LIU Chang, SUN Li, HE Gaohong, et al. Boiler system design based on stochastic programming under uncertain steam demand and equipment failure[J]. CIESC Journal, 2014, (9): 3512-3518. DOI： 10.3969/j.issn.0438-1157.2014.09.028.

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。

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.

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