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The Forecasting of Electrical Consumption Proportion of Different Industries in Substation Based on SCADA and the Daily Load Curve of Load Control System

机译:基于SCADA和负荷控制系统日负荷曲线的变电站行业用电比例预测。

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摘要

In order to forecast the integrated load model of substation with a certain random time variation character and increase the accuracy of forecasting, this article put forward a forecasting method of electrical consumption proportion of different industries in substation based on the daily load curve. First of all, load sequence is decomposed into a number of different frequency stationary components by using EMD, according to the variation of the components, select the appropriate SVM parameter and support vector machine with different kernel function construction to forecast separately, and get the load curve forecasting value combined from each forecasted value by SVM. Then, classify the attributive for each industry and combine the industry equivalent daily load curve by using the fuzzy C means clustering principle. Finally, structure the related relation with the forecasted load curve, namely that obtain the final forecasted industry electrical consumption proportion in substation industry through the normalized projection of forecasted load curve calculated by industry typical feature vector. Refer to the simulation result, there are strong generalization ability and high precision for this method.
机译:为了预测具有一定随机时间变化特征的变电站综合负荷模型,提高预测的准确性,提出了一种基于日负荷曲线的变电站不同行业用电量比例的预测方法。首先,利用EMD将载荷序列分解为多个不同频率的平稳分量,根据分量的变化,选择合适的SVM参数,采用具有不同核函数构造的支持向量机分别进行预测,得到载荷通过SVM将每个预测值组合而成的曲线预测值。然后,使用模糊C均值聚类原理对每个行业的属性进行分类,并组合行业等效日负荷曲线。最后,建立与负荷预测曲线的相关关系,即通过行业典型特征向量计算出的负荷预测曲线的归一化投影,得出变电站行业最终的预测工业用电量比例。参考仿真结果,该方法具有较强的泛化能力和较高的精度。

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