Smart grid technology is a radical approach for improvisation in existing power grid. Some of the significant features of smart grid technology are bidirectional communication, AMI, SCADA, renewable integration, active consumer participation, distribution automation, and complete management of entire grid through wireless communication standards and technologies. Management of complex, hierarchical, and heterogeneous smart grid infrastructure requires data collection, storage, processing, analysis, retrieval, and communication for self-healing and complete automation. Data mining techniques can be an effective solution for smart grid operation and management. Data mining is a computational process for data analysis. Data scrutiny is unavoidable for unambiguous knowledge discovery as well as decision making practices. Data mining is inevitable for analysis of various statistics associated with power generation, distribution automation, data communications, billing, consumer participation, and fault diagnosis in smart power grid.
The Research on Correlation Model Between Customer Complaint and Power Grid Operation Failure Based on Multi Factor Analysis
