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Application of Principal Component Regression Analysis in power load forecasting for medium and long term

机译:主成分回归分析在中长期电力负荷预测中的应用

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This paper deals with the power load forecasting for medium and long term using based on Principal Component Regression Analysis. The paper first reviews the research achievement of the load forecasting and its relationship with economic development, then introduces the basic theory of the principal component analysis and principal component regression analysis model. Finally, taking Beijing as an example, the paper extracts the principal components from the relevant economic factors related power consumption in Beijing, then establishes a multi-parameter regression prediction model (Principal component regression model) on the principal components. The results show that the error is small between prediction load and actual load, proving that the model is a feasible and effective method of load forecasting.
机译:本文采用基于主成分回归分析的中长期电力负荷预测方法。本文首先回顾了负荷预测的研究成果及其与经济发展的关系,然后介绍了主成分分析的基本理论和主成分回归分析模型。最后,以北京为例,从北京市相关用电相关经济因素中提取主成分,然后对主成分建立多参数回归预测模型(主成分回归模型)。结果表明,预测负荷与实际负荷之间的误差较小,证明了该模型是一种可行,有效的负荷预测方法。

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