用神经网络预测热发电量

Knežević Sonja, Žarković Mileta
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引用次数: 0

摘要

随着电力系统的发展,其复杂性也在不断增加,因此更需要良好的生产组织和有助于电力系统规划的信息。由于火力发电厂负责基本负荷,因此对其发电量的预测对良好的电力系统组织具有重要意义。本文介绍了利用人工神经网络预测火力发电厂发电量的方法。用于神经网络训练的数据是塞尔维亚电力系统中火力发电厂生产的测量数据。训练后的神经网络可用于预测全年的发电量,也可用于较短时间、每小时或每天的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predviđanje proizvodnje termoelektrane pomoću neuralnih mreža
With the power systems progress, its complexity grows and there is a greater need for good production organization and the need for information that would help in power system planning. As thermal power plants are responsible for covering the base load, the prediction of its production can be used significantly for good power system organization. This paper represents the use of artificial neural networks for the prediction of thermal plants power production. The data used for neural networks training are measurements of thermal power plant production in power systems of Serbia. Trained neural network can be used for prediction of production on yearly basis or for shorter, hourly or daily prediction.
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