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基于模糊神经网络的短期负荷预测系统的研究及实现

Research and Realization of Short-term Load Forecasting Based on Fuzzy Neural Networks

【作者】 赵敏

【导师】 朱永利; 栗然;

【作者基本信息】 华北电力大学(河北) , 电力系统及其自动化, 2003, 硕士

【摘要】 本文介绍了一个基于模糊神经网络的短期负荷预测系统。通过对电力系统负荷特性的认真深入分析,总结了影响短期负荷预测的各种因素如日类型、特殊节假日、各种天气因素等。系统中针对历史数据的预处理、短期负荷预测模型的建立、数据的远程网络传输、软件功能的开发等问题进行了分析及实现。开发了短期负荷预测软件系统,该软件系统除具有较高的预测精度外,还具有用户界面友好、方便快捷的数据管理、查询、分析等功能,同时实现了远程的网络数据传输。

【Abstract】 A Short-term Load Forecasting(STLF) System is introduced in this thesis. This present thesis analyzes the characteristics of the load in-depth. and studies the factors which effect the precision of the load forecasting, such as the type of day, special holidays, all kind of weather factors and so on. The system analyzes and realizes the advanced deal with of historical load data, the model establishment of STLF, the remote transmission of data and functions of software and so on. The load forecasting software is developed. The software provided with a friend man-machine interface and is excellent at calculating precision and administering of data, inquiring, analysis functions and so on. Simultaneously realizing the remote data transmission.

  • 【分类号】TM715
  • 【被引频次】4
  • 【下载频次】236
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