Open AccessReliability Analysis of Distribution Network Operation Based On Short-Term Future Big Data Technology
Author(s) -
Zhe Jing,
C.-Y. Yu,
Feiruo Xi,
Fengzhi Wu,
Zhixiang Tao,
Peihao Yang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1584/1/012027
Subject(s) - reliability (semiconductor) , computer science , index (typography) , principal component analysis , reliability engineering , data mining , artificial neural network , term (time) , engineering , artificial intelligence , power (physics) , physics , quantum mechanics , world wide web
This paper firstly establishes a four-dimensional index system for distribution network operation reliability. Using principal component analysis method, it extracts the main evaluation indicators from a large amount of data, and analyzes the influencing factors of the indicators according to the main evaluation indicators. According to the parallel association rules The method establishes the relevant model, and extracts the main indicators of operational reliability and the strong correlation rules between each influencing factors, so as to obtain the main influencing factors. The artificial neural network is proposed to predict, based on historical data and real-time data. The main influencing factors are used as the input and output of the forecast, and the output is expressed by the main evaluation index, and the operational reliability index for a period of time is judged. The calculation of the proposed strategy can quickly and effectively predict the operational reliability of the distribution network.