基于多源数据特征的变电站母线短期负荷预测算法

Quan Yuan, Qiang Zhang, A. Zhou
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引用次数: 0

摘要

为了避免母线供电区负荷转移、停电和小功率供电对母线负荷预测的不利影响,提出了一种基于多源数据特征的变电站母线短期负荷预测算法。通过将母线负荷转换为母线供电区域的理想电力负荷,将理想电力负荷修正为历史负荷数据,并采用多源数据特征负荷预测算法,获得初步预测结果。同时,得到了预报当天各影响因素的数值。预测结果消除了各种影响因素,间接预测了母线的负荷值。在此基础上,实验证明,与以母线网负荷值作为历史数据的直接预测方法相比,应用基于多源数据特征的变电站母线短期负荷预测算法可以显著提高供电区域小功率母线负荷预测的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short term load forecasting algorithm of substation bus based on multi source data characteristics
In order to avoid the adverse effects of load transfer, power outage and small power supply on bus load forecasting in bus power supply area, a short-term load forecasting algorithm for substation bus based on multi-source data characteristics is proposed. By converting the load of the bus to the ideal power load in the power supply area of the bus, the ideal power load is corrected as the historical load data, and the algorithm of multi-source data characteristic load forecasting is used to obtain the preliminary forecasting results. At the same time, the values of various influencing factors on the day to be forecasted are obtained. The forecasting results eliminate various influencing factors and indirectly predict the load value of the bus. Based on this, the experiment proves that the application of short-term load forecasting algorithm of substation bus based on multi-source data characteristics can significantly improve the accuracy of bus load forecasting with small power supply in the power supply area, compared with the direct forecasting method which takes the load value of bus network as historical data.
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