一种实用的发电自动化神经网络方法

Mahmoud Moghavvemi, Soo Siang Yang, M. Kashem
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引用次数: 9

摘要

提出了一种实用的基于人工神经网络的基于用户负荷分布的发电调度自动化技术。采用带反向传播学习算法的多层神经网络来预测满足用户需求所需的发电量。该技术已应用于一个典型的4/spl次/ 8mw的热电联产电厂。测试结果表明,该人工神经网络模型能够准确地自动执行发电机组调度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A practical neural network approach for power generation automation
This paper presents a practical artificial neural network (ANN) based technique for the automation of power generation scheduling based on the consumer's load profile. A multi-layered neural network with backpropagation learning algorithm is used to predict the required power generation to fulfill the consumer's demands. The proposed technique has been applied to a typical co-generation power plant of 4/spl times/8 MW rating. Test results indicates that the ANN model can automatically perform generator scheduling accurately.
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