基于K-Means聚类和改进多分类相关向量机的台区线损计算方法

Calculation of Line Loss in Transformer District Based on K-Means Clustering Algorithm and Improved MRVM

  • 摘要: 配电网线损计算是配电网线损管理和分析的一项重要技术措施。针对传统配电网理论计算不能自动实现、工作量大、计算结果不准确等问题,提出了一种基于K-Means聚类和果蝇算法优化多分类相关向量机(Multi classification correlation vector machine,MRVM)的快速计算低压台区线损计算方法,并在Matlab中搭建算法模型。针对台区线损数值分散的问题,先使用K-Means聚类算法将台区样本进行归类。使用归类的样本对果蝇算法优化的MRVM进行训练,得到线损率和台区参数之间的映射关系。以四川某地的500个台区样本进行实例验证,并与传统理论线损计算方法结果进行了对比。结果表明,所提出的方法可以有更好的计算精度。同时可以提高当前线损理论计算的自动化程度,减少计算工作量,提高电网公司配电网运行效率。

     

    Abstract: The calculation of distribution network line loss is an important technical measure for the management and analysis of distribution network line loss. In order to solve the problems of traditional distribution network theory, such as unable to realize automatically, heavy workload and inaccurate calculation results, a fast calculation method of line loss in low-voltage substation area based on K-Means clustering and Drosophila algorithm optimization multi classification correlation vector machine (MRVM) is proposed, and an algorithm model is built in Matlab. In order to solve the problem of dispersion of line loss, K-Means clustering algorithm is used to classify the samples. Then, the MRVM optimized by the Drosophila algorithm is trained by using the classified samples, and the mapping relationship between the line loss rate and the platform area parameters is obtained. Finally, 500 samples of a certain area in Sichuan Province are used to verify the results, and the results are compared with the traditional theoretical line loss calculation method. The results show that the proposed method has better accuracy. At the same time, it can improve the automation degree of the current theoretical calculation of line loss, reduce the calculation workload, and improve the operation efficiency of the distribution network of the grid company.

     

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