摘 要
随着全球气候变化和能源结构转型，电力系统负荷预测面临新的挑战。气象因素作为影响电力负荷的重要外部变量，其与电力负荷之间的关系日益复杂。为提高电力系统运行效率和稳定性，本研究旨在深入分析气象因素对电力系统负荷预测的影响机制。通过收集某地区多年逐时气象数据和对应电力负荷数据，采用多元线性回归、神经网络和支持向量机等方法建立预测模型，并引入气象敏感度分析以量化不同气象因子对负荷变化的贡献率。研究发现温度、湿度、风速等气象要素与电力负荷存在显著相关性，其中温度对负荷影响最为突出。创新性地提出基于气象聚类的分区预测方法，有效提高了短期负荷预测精度，特别是在极端天气条件下预测性能提升明显。该研究成果不仅为电力调度部门提供了科学依据，也为应对气候变化背景下的电力系统规划与运行优化提供了重要参考，具有重要的理论意义和实际应用价值。
关键词：电力负荷预测 气象因素影响 温度敏感性
Abstract
With the global climate change and energy structure transformation, power system load forecasting faces new challenges. Meteorological factors, as significant external variables influencing power load, have developed increasingly complex relationships with power load. To enhance the efficiency and stability of power system operations, this study aims to thoroughly analyze the impact mechanisms of meteorological factors on power system load forecasting. By collecting multi-year hourly meteorological data and corresponding power load data from a specific region, prediction models were established using multiple linear regression, neural networks, and support vector machines, while introducing meteorological sensitivity analysis to quantify the contribution rates of different meteorological factors to load variations. The study found that meteorological elements such as temperature, humidity, and wind speed exhibit significant correlations with power load, with temperature having the most pronounced effect. Innovatively, a zoning forecasting method based on meteorological clustering was proposed, which effectively improved short-term load forecasting accuracy, particularly under extreme weather conditions. This research not only provides scientific evidence for power dispatching departments but also offers important references for power system planning and operational optimization in the context of climate change, demonstrating significant theoretical implications and practical application value.
Keyword:Electric Load Forecasting Meteorological Factors Impact Temperature Sensitivity
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法与技术路线 2
2气象因素与电力负荷关系 2
2.1气温对电力负荷的影响 2
2.2降水对电力负荷的影响 3
2.3风速对电力负荷的影响 3
3气象数据处理与特征分析 4
3.1气象数据获取与预处理 4
3.2气象数据特征提取 4
3.3气象数据质量评估 5
4气象因素在负荷预测中的应用 5
4.1负荷预测模型构建 6
4.2气象因素的模型融合 6
4.3模型验证与结果分析 7
结论 8
参考文献 9
致谢 10
