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A Power Load Forecasting Method Based on Matching Coefficient of Meteorological Factors and Similar Load Modification

机译:一种基于匹配系数的气象因子和类似载荷修改的电力负荷预测方法

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摘要

It is of great significance to enhance the precision of power load forecasting for the security and stability of power system. According to the power load characteristics of both regularity and randomness, a novel load forecasting method based on the integration of similar load and recent historical load is proposed. In terms of similar load, this algorithm, firstly, utilizes matching coefficient of meteorological factors to quantify the similarity, then uses membership of day-type for the modification of similarity. After the process of filtering, the input sequence is made up of the combination of modified similar load and recent historical load. The results of simulation indicate that, compared with these forecasting algorithms merely based on similar load or on recent historical load, both mean relative error and mean square deviation of the algorithm presented in this paper are smaller and the precision of load prediction is higher.
机译:提高电力系统安全性和稳定性的功率负荷预测的精度具有重要意义。根据规律性和随机性的功率负荷特性,提出了一种基于相似负载和最近历史负荷集成的新型负荷预测方法。在类似的负载方面,该算法首先利用匹配的气象因素系数来量化相似性,然后使用日型的成员资格进行相似性的修改。在过滤过程之后,输入序列由修改的类似负载和最近的历史负载组成。仿真结果表明,与这些预测算法相比,仅基于类似的负载或最近的历史负载,本文呈现的算法的平均相对误差和均方偏差较小,负载预测的精度更高。

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