期刊
ELECTRIC POWER SYSTEMS RESEARCH
卷 176, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2019.105977
关键词
Data clustering; Distribution systems; Monte Carlo simulation; Non-linear loads; Probabilistic harmonic load flow; Uncertainty
Due to the ever-increasing use of non-linear loads and their undesired effects on distribution systems operation, harmonic analysis should be taken into consideration. On the other hand, the probabilistic nature of power systems makes it necessary to consider the harmonic analysis in a probabilistic environment. In this paper, a data clustering based algorithm is used for probabilistic assessment of harmonic load flow, for the first time. Despite the previous probabilistic harmonic load flow (PHLF), in which uncertainties are considered on grid connected renewable generations, load demands, generators, transmission lines probable failure, etc., this paper considers uncertainties on the location and non-linear load portion of nodal loads. Moreover, an organized PHLF algorithm is formulated in this paper. In order to show the superior abilities of the proposed method, the method is applied on the IEEE 37 node test system and the results are compared by the Monte Carlo simulation (MCS) method.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据