连接开放水域系统的经济区数据支持的预测控制
Xiaoqiao Chen1, Xuewen Zhang2, Minghao Han3
1Nanyang Environment and Water Research Institute, Nanyang Technological University, 1 CleanTech Loop, 637141, Singapore; Interdisciplinary Graduate Programme, Nanyang Technological University, 61 Nanyang Drive, 637460, Singapore; School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 62 Nanyang Drive, 637459, Singapore.
Water research
|December 19, 2025
概括
本研究介绍了安全和节能开放水系统的数据驱动控制框架. 与现有策略相比,新方法显著减少了区域违规和能源使用.
科学领域:
- 水资源管理 水资源管理
- 控制工程 控制工程 控制工程
- 人工智能的人工智能
背景情况:
- 开放水系统的实时运行对于安全,效率和能源优化至关重要.
- 现有的控制方法 (基于规则,基于模型) 在复杂,动态和不确定的环境中存在局限性.
- 需要采用数据驱动的方法来克服传统控制策略的挑战.
研究的目的:
- 为连接的开放水系统开发一个完全数据驱动的,基于区域的控制框架.
- 通过适应性控制目标区域选择,实现安全和节能运行.
- 为了最大限度地降低运营能耗,同时保持所需的水位.
主要方法:
- 提出了一种混合整数经济区数据支持预测控制 (DeePC) 方法.
- 利用词汇优化来处理多个控制目标 (区域跟踪,能源最小化).
- 采用贝叶斯优化来适应性控制目标区域选择,以平衡竞争目标.
主要成果:
- 拟议的方法在97.04%的运行时间内保持了所需区域内的水位.
- 平均每0.5小时能耗达到33.5千瓦时.
- 与基线和基于规则的方法相比,明显减少了区域违规和能源消耗 (例如,违规和基于规则的控制相比违规减少了74.96%).
结论:
- 数据驱动的DeePC框架与适应性区域选择有效地管理开放水系统.
- 该方法为安全,节能运行提供了强大的解决方案,优于传统方法.
- 这种方法消除了对显式动态建模的需求,简化了复杂水系统的实施.
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