长期电力负荷预测中的经济因素分析 -电气工程及其自动化专业

摘要

随着全球经济一体化进程加快和能源结构转型，电力负荷预测成为保障电力系统稳定运行的关键环节。本文聚焦长期电力负荷预测中的经济因素分析，旨在揭示经济发展与电力需求之间的内在联系，为电力规划提供科学依据。研究基于1990 - 2020年期间中国31个省份的面板数据，采用向量自回归模型（VAR）和格兰杰因果检验等计量经济学方法，深入剖析国内生产总值、产业结构、居民收入水平、固定资产投资等主要经济变量对电力负荷的影响机制。研究发现，GDP增长率与电力负荷呈显著正相关关系，第三产业占比上升会抑制电力需求增长，而居民收入水平提高则促进电力消费。此外，固定资产投资规模扩大对电力负荷具有滞后效应。本文创新性地引入了区域异质性分析框架，通过构建空间杜宾模型，探讨了不同地区间经济因素影响的差异性。研究表明，东部沿海地区更注重高附加值产业发展，电力弹性系数相对较低；中西部地区仍以重工业为主导，电力需求对经济增长更为敏感。本研究为制定精准化、差异化的电力发展规划提供了理论支持，有助于提升电力资源配置效率，推动能源可持续发展。

关键词：电力负荷预测经济因素分析向量自回归模型

Abstract

With the acceleration of global economic integration and energy structure transformation, electricity load forecasting has become a critical component in ensuring the stable operation of power systems. This study focuses on the analysis of economic factors in long-term electricity load forecasting, aiming to uncover the intrinsic relationship between economic development and electricity demand, thereby providing a scientific basis for power planning. Based on panel data from 31 provinces in China spanning from 1990 to 2020, this research employs econometric methods such as Vector Autoregression (VAR) models and Granger causality tests to thoroughly examine the impact mechanisms of key economic variables including Gross Domestic Product (GDP), industrial structure, household income levels, and fixed asset investment on electricity load. The findings indicate a significant positive correlation between GDP growth rate and electricity load, while an increase in the proportion of the tertiary sector tends to suppress the growth of electricity demand. Higher household income levels, however, promote electricity consumption. Additionally, the expansion of fixed asset investment exhibits a lagged effect on electricity load. Innovatively, this study introduces a fr amework for regional heterogeneity analysis by constructing a Spatial Durbin Model to explore the differences in the influence of economic factors across regions. The results show that the eastern coastal areas focus more on high-value-added industries, resulting in relatively lower electricity elasticity coefficients; whereas the central and western regions remain dominated by heavy industries, making electricity demand more sensitive to economic growth. This research provides theoretical support for formulating precise and differentiated power development plans, contributing to improved efficiency in power resource allocation and promoting sustainable energy development.

Keyword:Electric Load Forecasting Economic Factors Analysis Vector Autoregression Model

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研究方法概述 2

2经济增长对电力负荷的影响 2

2.1宏观经济指标分析 2

2.2产业结构调整效应 3

2.3城镇化进程影响 3

3政策因素对电力需求的调控 4

3.1能源政策导向作用 4

3.2环保政策约束机制 5