模拟和非线性预测控制太阳能热系统的区域供暖
Jan Lorenz Svensen1, Hjörleifur G Bergsteinsson1, Henrik Madsen1
1Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads 324, 2800 Kongens Lyngby, Denmark.
Heliyon
|December 13, 2024
概括
这项研究优化了太阳能热电厂在区域供暖中的运行,使用数据驱动模型和先进的控制. 开发的非线性模型预测控制器提高了高达28%的能源效率.
科学领域:
- 可再生能源系统可再生能源系统
- 控制工程 控制工程 控制工程
- 数学建模的数学建模
背景情况:
- 区域供暖系统越来越多地集成太阳能热能.
- 太阳能热电厂的高效运行对于最大限度地利用可再生能源至关重要.
- 现有的控制策略可能无法完全捕捉太阳能热电厂的动态复杂性.
研究的目的:
- 开发和实施数据驱动的非线性模型预测控制 (NMPC) 战略,以优化太阳能热电站运行.
- 提高区域供暖网络中太阳能热发电厂的能源效率和性能.
- 通过模拟和现实数据分析拟议的NMPC的有效性.
主要方法:
- 使用随机微分方程和现实世界植物数据来创建一个动态模型的灰盒建模.
- 非线性模型预测控制器 (NMPC) 设计基于重复的轨迹线性化.
- 模拟分析用于评估模型准确性和控制器性能在各种目标下 (例如,最大化能量或温度).
主要成果:
- 开发的动态模型准确地代表了太阳能热电厂的白天运行.
- 通过NMPC战略,可显著提高运营效率.
- 模拟显示,运输能量的增加高达28%.
结论:
- 数据驱动的建模和NMPC对于优化太阳能热电厂在区域供暖中的运作是有效的.
- 拟议的控制方法可大幅改善能源供应和系统效率.
- 这种方法提供了一个有价值的工具,以提高可再生能源在供暖系统的整合性能.
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