毕业论文《电力市场下基于BP神经网络的短期负荷预测建模及其仿真研究》.doc

PAGE 摘要 本文主要介绍我们在人工神经网络（Artificial Neural Network）ANN在电力系统短期负荷预测中进行的研究工作。 电力系统短期负荷预测的电力调度中十分重要的一个环节，其结果将对发电机生产计划的制定、水火发电的合理配置、燃料配置和安全分析设备的短期维修及电网能量的传播等产生很大的影响。在信息化建设蓬勃发展的今天，传统的人工预测已经越来越不能满足电力工业发展的需要，而以ANN为代表的预测方法则越来越显示出其巨大的优越性。准确的负荷预测有助于提高系统的安全性和经济性，能够减少发电成本。因此，寻求合适的负荷预测方法以最大限度的提高预测精度具有重要的应用价值。 本文在进行短期负荷预测的过程中，主要进行以下的工作：介绍和分析国内外现有的负荷预测技术现状；简要说明ANN；几种流行BP网络算法的理论介绍和算法的选取；根据负荷组成成分的分析及主要成分的变化规律，决定神经网络的输入以及训练样本数量的选取和处理；比较不同隐含层神经元数量对预测结果的影响，然后选取最优值；检验新的预测模型在实际的使用效果；根据实际应用情况提出存在的问题和后续的研究的见解。 关键词：短期负荷预测，人工神经网络，BP算法 Abstract This paper mainly presents our work on the research of short term load forecasting by using Artificial Neural Network(ANN). The short-term electric load forecasting is a very important link in the electric power dispatch ,resulted in a great improvement in the establishment of the production plan of generators,the reasonable deployment of fire and water generate electricity and fuel ,the short-term maintenance of safe analysis equipments and the spread of the energy of electrical network.Nowadays informatization construction is developing so vigorously that traditional artificial forecast can not yet satisfy the needs of electric power industrial development more and more.However,the forecast method for representative ,which is ANN,shows its huge superiority.Accurate load forecasting is advantageous to improveing the security and economic effect of power system and can reduce the cost of generating electricity.Finding an appropriate load forecasting method to improve the accuracy of precision has important applicationg value. This paper mainly introduced the topic as the following in the short-term load forecasting:The introduciong of and analysis of existing short-term load forecast technology both domestic and overseas.The brief introduction on ANN.The main popular BP(Error Back Propagation Network)training function and the choice in this function.According to the annlysis of composition of the load and the change rule of the main factor,decide the