Research and Implementation of Electric Supply Reliability Evaluation Model for Distribution Network

The scale of distribution network is expanding, the construction of distribution automation and ubiquitous power Internet of Things is advancing, and the multi-level and multisource real-time operation monitoring data of distribution network is growing exponentially. On the one hand, big data provides data support for distribution network reliability evaluation and dispatching planning, in different aspects, this also raises other requirements for the calculation accuracy and speed of reliability evaluation. How to mine the factors that have a great impact on reliability and make better use of electric data analysis algorithm to predict the changes of distribution network reliability in the future time scale is the focus of research. This article mainly taking technical breakthrough in electric distribution network data analysis, and studies its reliability evaluation methods of electric data analysis from both recent and forward aspects. First of all, the source of distribution network big data is analyzed from the internal and external aspects of the power system, and the data, data formats and relationships among the data source systems are analyzed. The characteristics of distribution network big data, such as wide source, diverse structure, fine granularity and complex relationships, are obtained in many ways. In view of the characteristics of multi-source and heterogeneous distribution network data, this paper puts forward a data processing algorithm based on multi-source data and a truth value discovery algorithm based on block coordinate descent method, which find out a new approach to overcome the difficulty of inconsistency and conflict of multi-source monitoring data.