Development of peak load forecasting system using neural networks and fuzzy theory
Development of peak load forecasting system using neural networks and fuzzy theory
复制标题
利用神经网络和模糊理论开发峰值负荷预测系统
DOI：
10.1002/eej.4391170304
复制
发表时间：
1995
影响因子：
0.4
通讯作者：
R. Araya
中科院分区：
文献类型：
--
作者：
Y. Ueki;T. Matsui;H. Endo;T. Kato;R. Araya
本文提出了一种基于多层神经网络和模糊理论的高峰负荷预测系统。电力系统负荷预测是电力系统可靠性和经济运行的一项重要任务。日高峰负荷预测是次日发电计划的基本工作之一。因此，许多统计方法已被开发和用于这种预测，即使它一直很难构建一个适当的功能模型。
该系统应用神经网络和模糊理论对日、周、月高峰负荷进行预测。该系统由工程工作站（EWS）和个人计算机（PC）组成。EWS用于学习和数据库，PC机用于人机接口，如预测操作。
该系统自1993年6月以来一直在使用。10个月的绝对平均误差为1.63%。结果表明，神经网络和模糊理论相结合的系统具有较高的有效性。
This paper presents a peak load forecasting system using multilayer neural networks and fuzzy theory. Electric load forecasting in power systems is a very important task from the perspective of reliability and economic operation. Daily peak load forecasting is one of the basic operations of generation scheduling for the following day. Therefore, many statistical methods have been developed and used for such forecasting even though it has been difficult to construct a proper functional model.
The developed system is applied by neural network and fuzzy theory to forecast for daily, weekly and monthly peak load. The system consists of an engineering workstation (EWS) and a personal computer (PC). The EWS is for learning and data-bases, and the PC is for man-machine interface such as forecasting operation.
The system has been used since June 1993. The result evaluated with an absolute mean error is 1.63 percent for 10 months. From the results shown here, the system applied by neural network and fuzzy theory has high validity.