基于神经网络和回归模型的微区域短期负荷预测

Kubra Kaysal, F. Hocaoglu, Y. Oğuz, Ahmet Kaysal
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引用次数: 3

摘要

由于当今技术的进步,已经发展了一些技术,可以对发电、输配电学科进行面向未来的预测。在文献中,荷载预测研究一般是针对宏观沉降单元进行的。然而,确定影响宏观沉降单元荷载预测的参数是非常困难的。本研究以一个微型沉降单元(Denizli省g ney区)为研究对象,对可能影响荷载需求的因素进行了分析。然后,通过选取文献中常用的方法,实现对该区域的负荷预测。最后对各模型的计算结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short term load forecasting for a micro region using NNs and regression models
Thanks to today's advancing technology, some techniques have been developed to make future oriented forecast on energy generation, transmission and distribution subjects. In literature, load forecasting studies are generally realized for macro size settlement units. However, determination of parameters that effect load forecasting in macro size settlement units is very difficult. In this study, by considering a micro size settlement unit (Güney district of Denizli province), factors that may affect the load demand were examined. Then, by selecting popular methods used in the literature, load forecasting for the region was realized. Finally the results obtained from the models were compared.
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