采用谱分析建模和基于人工神经网络的短期负荷预测方案SHORT-TERM LOAD FORECASTING BASED ON ARTIFICIAL NEURAL NETWORK AND MODELING WITH SPECTRUM ANALYSIS
张雪莹,管霖,谢锦标
摘要(Abstract):
提出了一种基于谱分析法进行建模的短期负荷预测方案,该方案利用负荷历史数据的谱分析结果进行人工神经网络(ANN)模式分类和选择输入变量。方案采用快速傅立叶变换(FFT)进行负荷数据预处理,运用滤波算法及小时负荷曲线的频谱分析来研究电网负荷的周期特性,所得结果表明四季负荷的谱特性具有明显差异,应采用不同的模型和方案进行预测。谱分析有助于各时段预测方案提取输入变量。利用该思路构造的基于人工神经网络的负荷预测方案被用于预测广东省网的负荷,与其他普遍采用的输入变量预测结果的对比表明,所提方案在短期负荷预测中的性能良好。
关键词(KeyWords): 频谱分析;人工神经网络;短期负荷预测;快速傅立叶变换
基金项目(Foundation):
作者(Author): 张雪莹,管霖,谢锦标
Email:
DOI: 10.13335/j.1000-3673.pst.2004.11.011
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