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炉-轮机系统的最佳IOFL经济模型预测控制技术
Mohamed Abdelkarim Abdelbaky1, Xiaobing Kong2, Xiangjie Liu2
1State 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.
ISA transactions
|July 28, 2024
概括
本研究介绍了一种使用输入/输出反线性化 (IOFL) 的最佳经济模型预测控制器 (EMPC),用于炉-轮机系统. 与现有技术相比,新方法在负载变化期间提高了动态和经济性能.
科学领域:
- 工程 工程师 工程师 工程师
- 控制系统 控制系统
- 电厂运营 电厂运营 电厂运营
背景情况:
- 炉轮机系统在负载变化期间需要精确控制响应能力和可行性.
- 传统的线性控制方法与这些系统固有的非线性作斗争.
- 现代发电厂优先考虑经济和环境性能,而不是简单的跟踪控制.
研究的目的:
- 为炉-轮机系统开发一个最佳的经济模型预测控制器 (EMPC).
- 应对系统非线性所带来的挑战,并纳入经济目标.
- 在负载变化期间增强动态和经济性能.
主要方法:
- 输入/输出反线性化 (IOFL) 来创建一个线性化的模型.
- 最佳经济模型预测控制 (EMPC) 公式作为一个二次编程问题.
- 适应性代算法用于约束映射,以确保可行的解决方案.
主要成果:
- 拟议的最佳IOFL EMPC方案有效地将非线性系统解为线性化模型.
- 控制器考虑了输入率和输入限制,以优化经济绩效.
- 与模糊和非线性EMPC技术相比,模拟显示出优越的动态和经济性能.
结论:
- 最优的IOFL EMPC是炉轮机系统的高效控制策略.
- 这种方法显著提高了动态响应能力和经济效率.
- 该方法提供了一个强大的解决方案,用于管理发电厂的负载变化.
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