Abdelbaky Mohamed Abdelkarim, Kong Xiaobing, Liu Xiangjie, Lee Kwang Y
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source, North China Electric Power University, Beijing 102206, China; Department of Electrical Power and Machines, Faculty of Engineering, Cairo University, Giza 12613, Egypt.
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source, North China Electric Power University, Beijing 102206, China.
ISA Trans. 2024 Oct;153:143-154. doi: 10.1016/j.isatra.2024.07.013. Epub 2024 Jul 14.
The optimal control design of the boiler-turbine system is vital to ensure feasibility and high responsiveness over desired load variations. Using the traditional linear control techniques realization of this task is difficult, as the boiler-turbine mechanism has strong nonlinearities. Besides, environmental and economic concerns have replaced existing tracking control ones as the primary concerns of advanced power plants. Thus, this study proposes an optimal economic model predictive controller (EMPC) scheme for this unit on the basis of the input/output feedback linearization (IOFL) method. By employing the IOFL method, this unit is decoupled into a new linearized model that is utilized for developing the suggested optimal IOFL EMPC technique. The proposed control scheme is formulated in an economic quadratic programming form that considers the input-rate and input limits of the unit for optimal economic performance. In addition, an adaptive iterative algorithm is utilized for constraints mapping with guaranteeing a feasible solution in a finite number of steps without violation of original constraints over the entire predictive horizon. The outcomes of the simulation show that the suggested optimal IOFL EMPC scheme offers an improved dynamic and economic output performance over fuzzy hierarchical MPC, fuzzy EMPC, and nonlinear EMPC techniques during various load variations.
锅炉 - 汽轮机系统的最优控制设计对于确保在期望的负荷变化下的可行性和高响应性至关重要。使用传统的线性控制技术难以实现这一任务，因为锅炉 - 汽轮机机制具有很强的非线性。此外，环境和经济问题已取代现有的跟踪控制问题，成为先进发电厂的主要关注点。因此，本研究基于输入/输出反馈线性化（IOFL）方法为该单元提出了一种最优经济模型预测控制器（EMPC）方案。通过采用IOFL方法，该单元被解耦为一个新的线性化模型，用于开发所建议的最优IOFL EMPC技术。所提出的控制方案以经济二次规划形式制定，该形式考虑了单元的输入速率和输入限制，以实现最优经济性能。此外，采用自适应迭代算法进行约束映射，以确保在有限步数内得到可行解，且在整个预测时域内不违反原始约束。仿真结果表明，所建议的最优IOFL EMPC方案在各种负荷变化期间，比模糊分层MPC、模糊EMPC和非线性EMPC技术具有更好的动态和经济输出性能。
