Big Data Based Analysis Between Power Distribution Network Reliability Parameters and Economic and Social External Environment
Liu Yuanhong, Wei Tao, Wei Liu, Wei Zhang, Yuanpeng Tan, Cao Quanzhi, Bo Yang, Xueqian Zhao
Abstract
The distribution network planning gradually focuses on the construction of active, green and coordinated intelligent distribution network, the urgent need for in-depth analysis of economic and social environment on the distribution network reliability, and then guide the distribution Network planning. This paper presents a method for analyzing the reliability of distribution network based on big data and the external environment of economy and society. The LASSO method is used to estimate the socioeconomic variables of the reliability parameters of the distribution network. The results show that the GDP of the primary industry and the bad weather have a significant positive impact on the average power failure time. The per capita GDP, the GDP growth rate and the secondary industry have a significant negative impact on the average power failure time.