Study on big data with time-space multi-scale for smart grid power flow
LI Ze-we · Dianli kexue yu jishu xuebao · 2015
With the rapid development of power business and the continuous perfection of big data technologies,the age of big data in power system is drawing near. Nevertheless,current electric power data is not able to meet the demand of smart grid on safety and stability analysis,where comprehensive information reflecting power flow observability is needed. To solve this problem,the big data with time-space multi-scale was analyzed for smart-grid power flow in this paper,it was nanosecond and broadband data obtained by wide-area real-time broadband time-space multi-scale synchronous measurement,and it was capable of precisely reflecting the power flow characteristics of power grids. The data can provide comprehensive information for smart grid research with higher accuracy,and which is helpful for solving the complex problems of power grid dynamic security and stability supervision,dimension reduction and decoupling of complex and huge power grids. The proposed data has great theoretical value and extensive application prospect.