电力系统数据预测的深度学习方法研究
摘 要
本论文主要研究了基于深度学习的电力系统数据分析和预报方法。电力系统是一个涉及到海量数据的复杂系统。论文首先对电力系统数据分析的几种方法进行了评述，主要有数据可视化、统计分析、时-频分析等。其次，对目前常用的基于统计的、人工神经网络的、深度学习的电力负荷预测和电网运行状况预测进行了详细的分析。在此基础上，研究基于全连接神经网络，卷积神经网络，循环神经网络，以及长短时记忆网络的深度学习方法。最后，论文还介绍了电力系统中的数据采集和处理技术，包括传统的数据采集方法， Internet技术， WSN技术等。本课题的目标是更好地为电网的规划、调度和运行提供支撑，从而提升电网的可靠性和效益。
关键词：深度学习 、电力负荷预测 、电网运行状态预测
Abstract
This paper mainly studies the method of power system data analysis and prediction based on deep learning. Power system is a complex system involving massive data. Firstly, several methods of power system data analysis are reviewed, including data visualization, statistical analysis, time-frequency analysis, etc. Secondly, the power load prediction and power network operation condition prediction based on statistics, artificial neural network and deep learning are analyzed in detail. On this basis, deep learning methods based on fully connected neural networks, convolutional neural networks, cyclic neural networks and short and long term memory networks are studied. Finally, the paper also introduces the data acquisition and processing technology in the power system, including the traditional data acquisition method, Internet technology, WSN technology, etc. The ob jective of this project is to provide better support for the planning, dispatching and operation of the power grid, so as to improve the reliability and efficiency of the power grid.
Keyword:Deep learning、Power load forecasting、Power grid operation state prediction
目 录
1绪论 1
1.1研究背景及意义 1
1.2研究内容 1
2电力系统数据分析与预测方法综述 1
2.1电力系统数据分析方法 1
2.2电力负荷预测方法 2
2.3电网运行状态预测方法 2
2.4基于深度学习的电力系统数据分析与预测方法 3
3电力系统数据采集与处理 4
3.1电力系统数据采集技术 4
3.2电力系统数据预处理方法 4
4基于深度学习的电力系统数据分析与预测算法设计 4
4.1搭建深度学习模型 4
4.2基于深度学习的电力负荷预测算法设计 5
4.3基于深度学习的电网运行状态预测算法设计 5
结论 5
参考文献 7
致谢 8
摘 要
本论文主要研究了基于深度学习的电力系统数据分析和预报方法。电力系统是一个涉及到海量数据的复杂系统。论文首先对电力系统数据分析的几种方法进行了评述，主要有数据可视化、统计分析、时-频分析等。其次，对目前常用的基于统计的、人工神经网络的、深度学习的电力负荷预测和电网运行状况预测进行了详细的分析。在此基础上，研究基于全连接神经网络，卷积神经网络，循环神经网络，以及长短时记忆网络的深度学习方法。最后，论文还介绍了电力系统中的数据采集和处理技术，包括传统的数据采集方法， Internet技术， WSN技术等。本课题的目标是更好地为电网的规划、调度和运行提供支撑，从而提升电网的可靠性和效益。
关键词：深度学习 、电力负荷预测 、电网运行状态预测
Abstract
This paper mainly studies the method of power system data analysis and prediction based on deep learning. Power system is a complex system involving massive data. Firstly, several methods of power system data analysis are reviewed, including data visualization, statistical analysis, time-frequency analysis, etc. Secondly, the power load prediction and power network operation condition prediction based on statistics, artificial neural network and deep learning are analyzed in detail. On this basis, deep learning methods based on fully connected neural networks, convolutional neural networks, cyclic neural networks and short and long term memory networks are studied. Finally, the paper also introduces the data acquisition and processing technology in the power system, including the traditional data acquisition method, Internet technology, WSN technology, etc. The ob jective of this project is to provide better support for the planning, dispatching and operation of the power grid, so as to improve the reliability and efficiency of the power grid.
Keyword:Deep learning、Power load forecasting、Power grid operation state prediction
目 录
1绪论 1
1.1研究背景及意义 1
1.2研究内容 1
2电力系统数据分析与预测方法综述 1
2.1电力系统数据分析方法 1
2.2电力负荷预测方法 2
2.3电网运行状态预测方法 2
2.4基于深度学习的电力系统数据分析与预测方法 3
3电力系统数据采集与处理 4
3.1电力系统数据采集技术 4
3.2电力系统数据预处理方法 4
4基于深度学习的电力系统数据分析与预测算法设计 4
4.1搭建深度学习模型 4
4.2基于深度学习的电力负荷预测算法设计 5
4.3基于深度学习的电网运行状态预测算法设计 5
结论 5
参考文献 7
致谢 8
