基于ESKF和MPC的CFBB燃烧系统的灵活最佳控制
Lei Han1, Lingmei Wang1, Enlong Meng2
1School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
本研究介绍了参与电网调度的燃煤发电机组的增强控制策略. 使用扩展状态卡尔曼波器 (ESKF) 的新模型预测控制 (MPC) 方法,在灵活运行时显著提高了控制性能和稳定性.
科学领域:
- 电力系统工程 电力系统工程
- 控制理论 控制理论
- 燃烧科学 燃烧科学
背景情况:
- 燃煤循环流化床 (CFB) 单元对于电网稳定性至关重要,特别是随着可再生能源集成的增加.
- CFB单元的灵活操作带来了诸如控制性能降低和信号干扰等挑战.
- 现有的控制策略与CFB燃烧系统固有的复杂动态和干扰作斗争.
研究的目的:
- 开发一个先进的控制方案,以提高燃煤CFB单元的灵活运行.
- 为了增强实时状态和干扰估计,以实现更准确的系统建模.
- 为了优化控制信号的生成,以更好地控制主蒸汽压力和床温度调节.
主要方法:
- 提出了一个与扩展状态卡尔曼波器 (ESKF) 集成的模型预测控制 (MPC) 框架.
- 使用ESKF进行实时选和系统状态和干扰的联合估计.
- 实现了协调的回退视界优化,以最大限度地减少输出偏差和控制信号增量.
主要成果:
- 与PI,LADRC和标准MPC相比,拟议的ESKF-MPC战略显示出优越的跟踪,防干扰和稳定性.
- 在±30%的参数干扰下,主要蒸汽压力和床温度的调整时间显著减少.
- 据ESKF-MPC方法显示,总绝对误差积分 (ITAE) 指标值较小且更加集中,表明强化了稳定性.
结论:
- 据了解,ESKF-MPC战略为燃煤CFB单元的灵活运行提供了强大而有效的解决方案.
- 这种先进的控制显著提高了系统稳定性,减少了超标,并提高了信号跟踪的准确性.
- 这些发现表明,整体燃烧系统控制性能得到了显著改善,促进了更深层次的新能源吸收.
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