【作者】 陈昊；

【导师】 吴杰；

【作者基本信息】 东南大学 ， 电力系统及其自动化， 2005， 硕士

【摘要】 电力负荷预测对电力系统的经济、安全运行有着重要的意义。随着电力行业逐渐走向市场,人们对负荷预测的精度越来越关注。负荷预测领域涌现出了一大批很有效的预测模型,但同时也存在着诸如实际应用中不能满足经典模型的前提假设,模型参数物理意义不明确等一些问题。本文使用了非经典计量经济学的一些思路方法,试图为建立具有更实际的假设前提和更强的解释能力的负荷预测模型做一些探索。本文主要工作如下:1.分析了负荷预测研究的现状和存在的问题。2.对非经典计量经济学中的条件异方差模型和协整理论作了较为完整的综述。3.为用电量,GDP两变量系统建立了动态经济学模型,并运用协整理论研究了季度用电量与季度GDP之间的协整关系。4.为用电量,GDP两变量系统建立了向量误差纠正模型,并分析了模型长期均衡,短期波动的误差纠正机制。5.用负荷分解的方法建立了日用电量序列的时间序列模型,分析了日用电量序列的波动集群效应,建立了广义条件异方差模型。6.利用ARCH族模型的扩展形式,对电力负荷时间序列的二阶矩进行了多角度(二阶矩对一阶矩的影响,逆杠杆效应,长期短期波动联合建模)的实证研究。7.研究了不同时间尺度下的用电量时间序列波动集群效应,并作了条件异方差效应的强弱程度比较。更多还原

【Abstract】 Load forecasting is of great importance for economic and secure operation of power system.With the development of electricity market, more and more attention is paid to the precision of load forecasting. There have been a good many efficient forecasting models in the field of load forecasting.But,unfortunately,some puzzles also exist.The preconditions of some classical models are hardly met in applications.And sometimes the parameters of some models have few definite physical meanings.This paper tries to model load time series with non-classical econometrics models, which have more practical preconditions, and have more powerful realistic meanings. The main achievements involve the following aspects:1. The actuality and challenges of load forecasting are analyzed.2. The autoregressive conditional heteroscedasticity (ARCH) model and cointegration theory of the non-classical econometrics are reviewed.3. The two-variable system, including seasonally adjusted power consumption and GDP, is modeled with dynamic economics model. With the help of cointegration theory, the relationship of cointegration between this two series is studied.4. The model of two variable system based on VECM is built.The long term equilibrium in this model is analyzed. The mechanism of error correction in short term is also discussed.5. The daily power consumption series is modeled with load-decompoing.The ARCH effect is analyzed. Finally, a generalized ARCH model is built.6. With the help of extended ARCH class model, a positive research on the second-order moment of load time series proceeds from different viewpoints, such as the influence of second-order moment upon the first-order moment, reverse leverage effect and modeling the long term volatility and the short term volatility together.7. Volatility clusrering effects of load time series in different terms are studied, and the intensity of ARCH effect in different series is compared.更多还原