摘要在电力系统调度部门中，负荷预测是十分重要的工作。准确的负荷预测是举足轻重的，它不只关系到我们是否能够合理安排否发电、输电和电能分配，并且系统能否安全经济稳定的运行也和它有很大的关系。同时它对于国民经济的发展有着十分重要的作用。30980
本文主要研究了基于人工神经网络的电力系统短期负荷预测。介绍了短期负荷的特点和负荷预测的方法。方法主要包括传统方法和新方法。介绍了小波神经网络的结构和算法。并且通过实际的例子来进行仿真与对比，得出结论。选择了传统的回归分析方法对电力系统短期负荷进行预测。也选择了小波神经网络进行预测分析。建立了两个模型，一个只考虑历史负荷对预测结果的影响；一个不仅考虑历史负荷，还考虑天气因素，对其进行负荷预测。得到的结论是小波神经网络预测精度比较高，天气因素会对预测结果产生一定的影响。
关键词  电力系统  短期负荷预测  小波神经网络  仿真
毕业论文设计说明书外文摘要
Title  Power system short-term load prediction based on artificial    neural network                      
Abstract
In the dispatching department of power system, power system load forecasting is an important work. It is very important to accurately forecast the power load. It is not only related to the reasonable arrangement ,transmission and distribution of electrical energy, but also has important influence on the development of the safe and stable operation of power system and the national economy.
This paper mainly studies the  short-term load prediction based on artificial neural network. Through the analysis , understand the short-term load characteristics of power system, the understanding of traditional analysis methods and new methods of load forecasting.This paper mainly introduces the wavelet neural network. And through the actual example of simulation and comparison, I get the conclusion. First I choose of the traditional regression analysis method to carry on the short-term load forecasting of power system, and then select the wavelet neural network in artificial neural network prediction, finally set up two models. The first model only considers the historical load; the other one considers not only the historical load, but also considers the weather factors, forecasting the forecasts.The conclusion is that the wavelet neural network prediction accuracy is high, weather forecasts will have some impact on the results.
Keywords  Power system  Short term load forecasting  Simulation   Wavelet neural network
 目   次
1  绪论    1
1.1  电力系统短期负荷预测的研究背景及意义    1
1.2  国内外研究现状    1
1.3  论文主要内容    2
2  电力系统短期负荷预测综述    3
2.1  电力系统短期负荷预测    3
2.2  电力系统负荷预测方法介绍    4
2.3  电力系统短期负荷模型    6
2.4  电力系统短期负荷预测的数据处理    7
2.5  电力系统负荷预测的误差    9
2.6  本章小结    10
3  小波神经网络概述    11
3.1  小波分析理论简介    11
3.2  常用小波函数    11
3.3  小波神经网络概述    15
3.4  本章小结    18
4  实例分析    20
4.1  负荷周期性分析    20 基于人工神经网络的电力系统短期负荷预测:http://www.751com.cn/zidonghua/lunwen_26987.html