Stress control of boilers is a major concern in the aged power plants. The studied forced circulation boiler suffers from a malfunction of the combustion control system. In order to reduce cyclic stress on boiler equipment and prevent undesirable shutdowns of power unit during fuel shortage events, an operating instruction is proposed. In order to predict dynamic behavior of the boiler, a nonlinear state space model is developed using mathematical modelling approach. A gray box identification procedure is introduced using only steady state measurements of plant. The dynamic model is verified compared to actual plant data and accuracy of model parameters is evaluated by sigma-normalized sensitivity analysis. Considering aim of steam pressure regulation, a three-step optimization approach is proposed based on golden section search, parabolic interpolation and interior-point methods to optimize arbitrary parameters of the proposed manual control scheme. Simulation results for different loads and various fuel limitation scenarios show that proposed instruction improves the cyclic stress in superheater tubes at least 84.5%. In addition, Monte Carlo experiments illustrate despite a 10% operators' error in implement of the instruction, the stress is still reduced by an average of 78.1% for a given case.

锅炉的压力控制是老旧发电厂的一个主要问题。所研究的强制循环锅炉存在燃烧控制系统故障。为了减少锅炉设备的循环应力并防止在燃料短缺事件期间动力装置的意外停机，提出了操作指南。为了预测锅炉的动态行为，使用数学建模方法开发了非线性状态空间模型。仅使用植物的稳态测量引入了灰盒识别程序。动态模型与实际工厂数据进行比较验证，模型参数的准确性通过 sigma 归一化敏感性分析进行评估。考虑到蒸汽压力调节的目的，提出了一种基于黄金分割搜索的三步优化方法，抛物线插值和内点方法来优化所提出的手动控制方案的任意参数。不同负载和各种燃料限制场景的仿真结果表明，所提出的指令将过热器管中的循环应力提高了至少 84.5%。此外，蒙特卡罗实验表明，尽管操作员在执行指令时有 10% 的错误，但对于给定情况，压力仍然平均降低了 78.1%。