Research on power load forecasting and management methods in power distribution projects
输配电工程中的电力负荷预测与管理方法研究

摘要

随着智能电网建设的深入推进，输配电工程中电力负荷的精准预测与高效管理已成为保障电力系统安全、经济运行的关键环节。本文围绕输配电工程中的电力负荷预测与管理展开研究，系统分析了常用负荷预测方法的原理与应用场景，结合智能算法与传统模型提出改进预测方案，并构建了基于大数据的负荷管理体系。通过引入时间序列模型与机器学习算法，建立了负荷预测的数学模型，以某地区电网为例进行实证分析，验证了方法的有效性。研究结果表明，融合多源数据的预测模型可将负荷预测误差控制在5%以内，基于需求侧响应的管理策略能显著提升电网运行效率。本文研究为输配电工程的负荷管理提供了理论参考与实践指导。

Abstract

With the deepening of smart grid construction, the accurate prediction and efficient management of power load in power transmission and distribution projects have become the key link to ensure the safe and economical operation of the power system. This paper focuses on the research on power load forecasting and management in power transmission and distribution engineering, systematically analyzes the principles and application scenarios of common load forecasting methods, proposes improved prediction schemes based on intelligent algorithms and traditional models, and constructs a load management system based on big data. By introducing the time series model and machine learning algorithm, a mathematical model of load forecasting is established, and the empirical analysis is carried out by taking a regional power grid as an example to verify the effectiveness of the method. The results show that the prediction model fusing multi-source data can control the load prediction error within 5%, and the management strategy based on demand-side response can significantly improve the operation efficiency of the power grid. This paper provides a theoretical reference and practical guidance for the load management of power transmission and distribution engineering.