Storage and Indexing of Big Data for Power Distribution Networks
Naiwang Guo, Yun Su, Hongshan Yang · 2018
With the construction of power distribution networks, a large amount of various types of data has accumulated, including automation and information technology system data as well as customer power consumption data, including distribution transformer, distribution transformer station, distribution switch station, meter, and electrical energy quality. The storage and index association of a large amount of different data is the basis for big data analysis. As a massive type of time-series data, customer power consumption load includes large-scale customers and high-density data collection. To improve the efficiency of query and analysis, this study proposed time-series data indexing technology to reduce the time required for data query and retrieval, to improve the efficiency of time-series data analysis, and to enable power companies to deeply analyze and cluster the power consumption behaviors of their customers.