文档介绍：本科生毕业设计说明书(毕业论文)
题目:基于BP神经网络的
电力系统短期负荷预测
专业:电气工程及其自动化
基于BP神经网络的电力系统短期负荷预测
摘要
电力系统短期负荷预测在实时控制和保证电力系统经济、安全和可靠运行方面起着重要作用,它已成为电力系统中现代能量管理系统的一个重要组成部分。负荷预测的误差将导致运行和生产费用的剧增,因此,精确的预测就成了电力工作者和科技人员致力解决的问题。
电力系统负荷变化受多方面影响,一方面,负荷变化存在着未知不确定因素引起的波动;另一方面,又有周期变化的规律性,这使得负荷曲线具有相似性。同时,由于受天气、节假日等特殊情况的影响,又使负荷变化出现差异,呈现强烈的非线性特性。
本文提出了一种基于BP神经网络的预测方法,这种方法的最大优点就是对大量的非线性特性、非准确性规律具有自适应功能。本文主要针对BP 神经网络应用于电力系统短期负荷预测做了进一步的研究,并通过MATLAB设计BP神经网络,仿真结果表明BP神经网络在短期负荷预测中的应用是可行的,能较好的反映负荷预测的非线性特性,但由于本文没有考虑气候,温度,节假日等因素的数据,做出来的仿真结果并不令人十分满意,不过依然可以肯定BP神经网络依然优于传统的预测方法,是一个有待于我们去研究和开发的新领域。
关键词:电力系统;BP神经网络;短期负荷预测
Based on BP work power system
Short-term load forecasting
Abstract
Short-term load forecasting in real-time power system control and to ensure economic, safe and reliable operation plays an important role, it has e a modern power system energy management system is an ponent. Load forecasting errors will lead to sharp increase in operating and production costs, therefore, accurately predict the power to e the workers and technical personnel to address the problem.
Various power system affected by the load change, on the one hand, there is the unknown load change caused by fluctuations in uncertainty; the other hand, there are periodic changes in the laws, which makes a similar load curve. At the same time, due to weather, holidays and other special circumstances of, and differences in the load changes occur, showing a strong nonlinearity.
In this paper, BP work based prediction method, the biggest advantage of this approach is that the nonlinear characteristics of a large number of non-accuracy of the law of adaptive function. In this paper, BP work for short term load forecasting in power system to do further research and design BP work through the MATLAB , simulation results show that BP work in the short-term load forecasting is feasible, and can better reflect the load predict the nonlinear characteristics, but because this article does not consider the climate, temperature, holidays