基于数据挖掘的负荷预测系统在农网供电企业中应用研究

发布时间：2018-01-28 11:10

本文关键词： 数据挖掘农村电网负荷预测 BP神经网络技术　出处：《华北电力大学(北京)》2016年硕士论文　论文类型：学位论文

【摘要】：电力负荷是指一个地区对电力和电量的消费的情况。而农村电网负荷预测是指从已知的农村经济、社会发展和电力系统需求出发,考虑农村的经济、气候和特殊事件等诸多因素,通过对农网历史数据的分析和研究,探索农村电网系统各参数之间内在联系和发展规律,以未来的经济和气候预测结果为依据,对未来农村电网需求做出估计和预测。农村电网负荷预测是农网管理系统的重要组成部分,它所提供的未来负荷数据,对农网系统的控制,运行和计划极为重要。农网系统由于设备比较陈旧,基础设施薄弱,因而系统稳定运行要求事先对负荷进行预测,才能早做准备,将设备资源进行合理调配,以保证农村用电安全可靠。因考虑到电力负荷的区域特性,本文从年负荷、月负荷和日负荷三个方面分析了枞阳县地区十二五期间负荷增长的特性,并着重分析了负荷的气象敏感性和重大节假日影响,通过这些分析,得出了农村电网负荷的一般特性。在分析电力负荷的基础上,利用点对点倍比法、一元线性回归法和BP神经网模型对枞阳县地区负荷进行短期负荷预测,并对三种负荷预测模型精度进行对比,得出适合农村电网的短期负荷预测模型。其结果对农村电网企业做好“迎峰度夏”和“迎峰度冬”的两项重点工作有较好的参考意义。
[Abstract]:Power load refers to the consumption of electricity and electricity in a region, while the load forecasting of rural power grid refers to the consideration of rural economy from the known rural economy, social development and the demand of power system. Through the analysis and study of the historical data of rural power grid, the inherent relationship and development law among the parameters of rural power grid system are explored, which is based on the future economic and climate prediction results. Rural power grid load forecasting is an important part of the rural power network management system, it provides future load data, the control of rural power network system. It is very important to run and plan. Because the equipment is old and the infrastructure is weak, the stable operation of the system requires forecasting the load in advance so as to prepare and allocate the equipment resources reasonably. In order to ensure the safety and reliability of rural power consumption, considering the regional characteristics of power load, this paper analyzes the characteristics of load growth in Zongyang County during the 12th Five-Year Plan period from three aspects: annual load, monthly load and daily load. Through these analyses, the general characteristics of the rural power grid load are obtained. Based on the analysis of the power load, the point-to-point ratio method is used. The linear regression method and BP neural network model are used to forecast the short-term load in Zongyang county, and the accuracy of the three load forecasting models is compared. A short-term load forecasting model suitable for rural power grid is obtained. The results have a good reference significance for rural power grid enterprises to do the two key work of "summering peak" and "winter kurtosis".
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TM715;TP311.13

【相似文献】