基于人工神经网络的自主电力系统短期负荷预测数据预处理

S. Kiartzis, C. Zoumas, A. Bakirtzis, V. Petridis
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引用次数: 11

摘要

针对希腊公共电力公司(PPC)位于克里特岛的调度中心,建立了基于人工神经网络的短期负荷预测模型。该模型可以预测每日的负荷概况,提前时间为1至7天。本文介绍了模型开发过程中在输入变量的选择、人工神经网络结构和训练数据集预处理等方面所取得的经验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data pre-processing for short-term load forecasting in an autonomous power system using artificial neural networks
This paper presents the development of an Artificial Neural Network (ANN) based short-term load forecasting model for the Dispatching Center of the Greek Public Power Corporation (PPC) in the island of Crete. The model can forecast daily load profiles with a lead time of one to seven days. Experiences gained during the development of the model regarding the selection of the input variables, the ANN structure, and the training data set pre-processing are described in the paper.
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