毕业设计论文-基于天气敏感模型的短期电力负荷预测.doc

基于天气敏感模型的短期电力负荷预测
摘要
电力系统短期负荷预测是电力部门的一项重要工作,对其预测方法的研究一直为人们所重视。短期负荷预测的准确与否将直接关系到电力系统的安全运行和经济调度,便于更合理地安排电网设备调度及检修计划;还能提高电力系统运行的稳定性,减少电网的发电成本。随着我国区域性电力市场的逐步建立和完善,短期负荷预测工作将在电力市场运营中占据十分重要的地位。
本文首先介绍了短期电力负荷预测研究的目的和意义,分析了电力系统负荷的组成,介绍了电力负荷预测的内容和基本算法。着重阐述了人工神经网络(ANN)进行负荷预测的基本原理,并针对一个实际地区电力负荷的具体情况,提出用人工神经网络建立模型来预测其负荷的变化。其次,该模型将电力负荷的变化考虑成:系统的基本负荷、温度的差异、天气的改变和同期的类型(工作日与节假日),这些主要因素共同决定的。因此,本文采用改进的三层BP型人工神经网络来建立负荷预测模型,以上述影响负荷的主要因素作为数据样本,进行神经网络的自我训练和学习,并且在不断地训练和学习的过程中引入误差反方向传播算法(即BP算法)来修正神经网络的连接权重,从而达到对负荷预测模型的改良和完善,进一步贴近实际的负荷变化。同时,在负荷预测模块运行结束后,本文还将因电力线路或设备检修损失的负荷量也作为影响因素进行了考虑,从而得出更精确的预测负荷值。
在实际的负荷预测算例结果与分析中,上述的预测思路得到了较好的印证,其预测的精度也较高,完全满足了电力部门运行和经济调度的实际要求,减少了购电成本,提高了电力部门的经济效益和电网调度技术人员的工作效率,保障了电网运行的安全。
关键字: 短期负荷预测人工神经网络 BP算法
Research For Power System
Short-Term Load Forecasting
Abstract
Power system short—term load forecasting(STLF) is all important task of power utilities,So great attention has always been paid on methods of forecasting is related to operation security and economical dispatching of power system,which is used to arrange the equipments dispatching and it can advance the stability of power system and save generation the development of area power market in China,STLF will play an important role in the operation of power market.
This article first describes the purpose and significance of short-term power load forecasting, analysis of power system load, and describes the contents and basic algorithm for power load on the artificial work (ANN) for load forecasting principle and for a real load in specific situations, made using artificial work model to predict changes of its load .In the second model devises the load into a few main pans:basic load,difference of temperature and weather,different day type(working day and holidays).So improved work of three layers are used to set up the factors which effect the load are the samples,and through self-training and study to finish the