基于AI的暖通空调智能调控 -建筑环境与能源应用工程专业

摘要

随着全球能源消耗的持续增长和环境问题的日益严峻，暖通空调（HVAC）系统作为建筑能耗的主要组成部分，其智能化调控成为研究热点。本研究旨在通过引入人工智能技术，构建一种基于AI的暖通空调智能调控方法，以实现能源效率的提升和运行成本的降低。研究采用深度学习算法与强化学习框架相结合的方式，通过对历史运行数据的分析和实时环境参数的感知，建立精确的预测模型，并优化控制策略。实验结果表明，该方法能够显著提高系统的响应速度和调节精度，同时在多种工况下实现能耗的有效降低。与传统调控方式相比，本研究提出的AI驱动方案平均节能率达到15%以上，且具有较强的适应性和可扩展性。此外，研究还创新性地引入了多目标优化机制，平衡了舒适性与经济性的矛盾，为实际工程应用提供了重要参考。总体而言，本研究不仅为暖通空调系统的智能化升级提供了新思路，也为建筑领域的可持续发展做出了积极贡献。

关键词：暖通空调系统；人工智能调控；深度学习；多目标优化；能耗降低

ABSTRACT

With the continuous growth of global energy consumption and the increasing severity of environmental issues, heating, ventilation, and air conditioning (HVAC) systems, as a major component of building energy consumption, have become a research hotspot for intelligent regulation. This study aims to introduce artificial intelligence technology to construct an AI-based intelligent control method for HVAC systems, thereby enhancing energy efficiency and reducing operational costs. By integrating deep learning algorithms with reinforcement learning fr ameworks, this research establishes an accurate predictive model through the analysis of historical operational data and real-time perception of environmental parameters, while optimizing control strategies. Experimental results indicate that this approach significantly improves system response speed and regulation accuracy, achieving effective energy reduction under various operating conditions. Compared with traditional control methods, the AI-driven solution proposed in this study achieves an average energy-saving rate of over 15%, demonstrating strong adaptability and scalability. Additionally, this study innovatively incorporates a multi-ob jective optimization mechanism to balance the trade-off between comfort and economy, providing significant reference for practical engineering applications. Overall, this research not only offers new insights into the intelligent upgrading of HVAC systems but also makes a positive contribution to sustainable development in the building sector.

Keywords: Hvac System; Artificial Intelligence Control; Deep Learning; Multi-ob jective Optimization; Energy Consumption Reduction

摘要 I

ABSTRACT II

第1章绪论 1

1.1 暖通空调智能调控的研究背景 1

1.2 AI技术在暖通空调领域的意义 1

1.3 国内外研究现状分析 1

1.4 本文研究方法与结构安排 2

第2章 AI驱动的暖通空调系统建模 3

2.1 暖通空调系统的数据采集与处理 3

2.2 基于AI的系统建模方法 3

2.3 模型验证与优化策略 4