Exploring load disaggregation method for industrial loads considering economy-climate-production factors based on clustering technologies

Yu Long, Wenjun Ruan, Kang Xie, Yuhang Sun, Siwei Li, Long Yu, Liang Yue, Chang Liu, Meimei Duan
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Abstract

Power demand response is a significant method to provide regulation resources for the power system by adjusting the operating power of equipment. To obtain the regulation potential of each equipment, the load disaggregation is necessary from a large number of the smart meter data. However, the existing disaggregation methods mainly focus on residential and commercial users with the similar and fixed equipment. The industrial user loads are various, which is affected by many factors, such as the climate. To solve the above problems, this paper proposes a load disaggregation method for industrial loads considering economy-climate-production factors based on clustering technologies. First, the main affecting factors of the industrial production are analyzed from three dimensions, including the production load, the non-production load and the security load. On this basis, data marking and clustering methods are proposed to classify the industrial load data. Subsequently, an industrial load disaggregation method is presented for obtaining each type of the load power based on the single variable method. Finally, the effectiveness of the proposed models and methods is illustrated by numerical studies.
探索基于聚类技术的考虑经济气候生产因素的工业负荷分解方法
电力需求响应是通过调节设备运行功率为电力系统提供调节资源的重要手段。为了获得各设备的调节电位,需要从大量的智能电表数据中进行负荷分解。然而,现有的分解方法主要针对设备相似且固定的住宅和商业用户。工业用户负荷是多种多样的,受气候等因素的影响。针对上述问题,本文提出了一种基于聚类技术的考虑经济-气候-生产因素的工业负荷分解方法。首先,从生产负荷、非生产负荷和安全负荷三个维度分析了工业生产的主要影响因素;在此基础上,提出了数据标记和聚类方法对工业负荷数据进行分类。在此基础上,提出了一种基于单变量法的工业负荷分解方法,用于求解各类负荷功率。最后,通过数值研究验证了所提模型和方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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