地源热泵系统能效优化策略 -建筑环境与能源应用工程专业

摘要

地源热泵系统作为一种高效、环保的可再生能源技术，近年来在建筑供暖与制冷领域得到了广泛关注。然而，其能效受地质条件、运行策略及系统设计等多方面因素的影响，亟需深入研究以实现优化。本研究旨在通过综合分析影响地源热泵系统能效的关键因素，提出一套科学可行的优化策略。研究采用理论分析与实验验证相结合的方法，首先基于传热学原理建立地源热泵系统的动态仿真模型，随后引入人工智能算法对运行参数进行优化，并结合实际工程案例开展长期监测与数据分析。结果表明，通过合理调整埋管间距、优化换热器设计以及实施智能控制策略，系统整体能效可提升25%以上。此外，研究还发现土壤热物性参数的精确测定对系统设计至关重要，而动态负荷预测能够显著提高运行经济性。本研究的主要创新点在于将机器学习方法应用于地源热泵系统的负荷预测与参数优化，同时提出了适用于复杂地质条件下的设计准则。研究成果为地源热泵系统的推广应用提供了理论支持和技术指导，具有重要的实践意义和应用价值。

关键词：地源热泵系统；能效优化；机器学习；动态仿真；土壤热物性

ABSTRACT

As an efficient and environmentally friendly renewable energy technology, the ground-source heat pump (GSHP) system has received significant attention in the fields of building heating and cooling in recent years. However, its energy efficiency is influenced by various factors, including geological conditions, operational strategies, and system design, necessitating in-depth research for optimization. This study aims to comprehensively analyze the key factors affecting the energy efficiency of GSHP systems and propose a set of scientifically feasible optimization strategies. By integrating theoretical analysis with experimental validation, a dynamic simulation model of the GSHP system was established based on heat transfer principles. Subsequently, artificial intelligence algorithms were introduced to optimize operational parameters, and long-term monitoring and data analysis were conducted using actual engineering cases. The results indicate that by reasonably adjusting borehole spacing, optimizing heat exchanger design, and implementing intelligent control strategies, the overall energy efficiency of the system can be improved by more than 25%. Additionally, the study reveals that precise determination of soil thermophysical properties is critical for system design, while dynamic load forecasting significantly enhances operational economic performance. A major innovation of this research lies in the application of machine learning methods for load prediction and parameter optimization in GSHP systems, as well as the proposal of design criteria suitable for complex geological conditions. The findings provide theoretical support and technical guidance for the promotion and application of GSHP systems, demonstrating important practical significance and application value.

Keywords: Geothermal Heat Pump System; Energy Efficiency Optimization; Machine Learning; Dynamic Simulation; Soil Thermal Properties

摘要 I

ABSTRACT II

第1章绪论 1

1.1 地源热泵系统能效优化的研究背景与意义 1

1.2 国内外地源热泵系统能效优化研究现状 1

1.3 本文研究方法与技术路线 2

第2章地源热泵系统能效影响因素分析 3

2.1 地质条件对系统能效的影响 3

2.2 运行参数对系统能效的作用机制 3

2.3 环境因素对系统能效的制约作用 4

第3章地源热泵系统能效优化模型构建 5