集成模拟和校准框架用于加热系统优化
Kirill Djebko1, Daniel Weidner1, Marcel Waleska1
1Chair of Computer Science VI: Artificial Intelligence and Knowledge Systems, Julius-Maximilians-Universität Würzburg, Am Hubland, 97074 Würzburg, Germany.
Sensors (Basel, Switzerland)
|February 10, 2024
概括
本研究提出了利用粗的数字双胞胎模型优化供暖系统效率的框架. 它通过使用预处理和校准来解决数据缺口,从而减少炉气体消耗和提高可持续性.
科学领域:
- 建筑能源系统 建筑能源系统
- 控制工程 控制工程 控制工程
- 可持续的能源 可持续的能源
背景情况:
- 由于控制器参数不足于最佳值,供热系统面临效率低下的问题.
- 现有的监测系统缺乏可行的改进建议.
- 精确的数字双胞胎受到不可用的关键数据 (如水消耗) 的阻碍.
研究的目的:
- 开发用于加热系统的模拟和校准框架.
- 为了实现控制器参数的优化,以提高能源效率.
- 为了解决建筑物数字双胞胎建模中的数据限制.
主要方法:
- 利用粗略模型进行定量预测和定性评估.
- 开发了一个用于数据增强的预处理模块.
- 使用测量数据实现自动模型校准.
- 评估控制器参数优化以减少燃气消耗.
主要成果:
- 使用粗模型和预处理,与部分不完整的测量数据实现了可接受的匹配.
- 证明了加热系统模型的成功校准.
- 成功优化了控制器参数,以减少模拟炉燃气消耗.
结论:
- 粗的数字双胞胎模型,加上预处理,可以有效地建模不完整的数据.
- 该框架可以准确校准和优化供暖系统控制器.
- 这种方法提高了建筑加热系统的可持续性和二氧化碳效率.
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