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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:本文根据主要成分回归分析,涉及中长期的电力负荷预测。本文首先审查了对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和主成分回归分析模型的基本理论。最后,以北京为例,本文从北京相关经济因素的主要经济因素中提取了主要成分,然后在主组件上建立了多参数回归预测模型(主成分回归模型)。结果表明,预测负荷和实际负载之间的误差较小,证明了该模型是一种可行和有效的负载预测方法。

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