WAMS/SCADA Data Fusion Method Study Based on Time-Series Data Correlation Mining LiJin Zhao1, Liang Huang1, Qiansu Lv1, Tao Yang1,Daqian Wei2 Electric Power Research Institute of Guizhou Power Grid Co., Ltd,GuiZhou 550000,China School of Electrical Engineering, Wuhan University, Wuhan 430072,China Abstract: Hybrid measurement state estimation of WAMS data and the SCADA system is an effective method to improve the traditional state estimation. However, as the WAMS data and the SCADA data belong to different systems, there are great differences between them. To solve this problem, WAMS/SCADA data fusion method based on the correlation mining of time-series data is proposed in this paper. Firstly, WAMS/SCADA correlation estimation is done with the derivation of Pearson correlation coefficient. Then, solving the function model for the time difference issue and the alignment problem of correlation curves. After that, analyzing the measurement precision by considering the measurement weight and calculate the matrix of time series data weight to complete the optimization for the measurement precision. Finally, forming the effective fusion scheme based on the correlation of timing data. Simulation results on the IEEE 118 nodes system, with set a comparison of different hybrid measurement state estimation and different state estimation algorithm, effectiveness and stability of the proposed method has been proved. Keywords: Time-series data; correlation mining; WAMS/SCADA data fusion. Instruction With the Power Grid becoming smarter and more integrative, real-time data transmission and analysis in Power Grid is much more important. SCADA plays an important role in traditional power system analysis for a long time. As the WAMS proposed and perfected, it can provide a new method of monitoring and analyzing of Power Grid. Taking no account of time delay, the WAMS is able to monitor measurement data of the whole Power Grid and provide unprecedented data stream to keep the Power Grid safe and stable. However, it is difficult to analyze measurement data, make decisions and become a single reliable system source within a short time because of the inadequacy of deployment of WAMS and high-speed data sources. Therefore, hybrid measurement data of SCADA and WAMS based on response is an important on-line method to estimate and analyze the Power Grid. Because of the differences between WAMS and SCADA’s technology platform, they are different in component, precision, transmission time delay and refresh rate.
WAMS/SCADA Data Fusion Method Study Based on Time-Series Data Correlation Mining LiJin Zhao1, Liang Huang1, Qiansu Lv1, Tao Yang1,Daqian Wei2 Electric Power Research Institute of Guizhou Power Grid Co., Ltd,GuiZhou 550000,China School of Electrical Engineering, Wuhan University, Wuhan 430072,China Abstract: Hybrid measurement state estimation of WAMS data and the SCADA system is an effective method to improve the traditional state estimation. However, as the WAMS data and the SCADA data belong to different systems, there are great differences between them. To solve this problem, WAMS/SCADA data fusion method based on the correlation mining of time-series data is proposed in this paper. Firstly, WAMS/SCADA correlation estimation is done with the derivation of Pearson correlation coefficient. Then, solving the function model for the time difference issue and the alignment problem of correlation curves. After that, analyzing the measurement precision by considering the measurement weight and calculate the matrix of time series data weight to complete the optimization for the measurement precision. Finally, forming the effective fusion scheme based on the correlation of timing data. Simulation results on the IEEE 118 nodes system, with set a comparison of different hybrid measurement state estimation and different state estimation algorithm, effectiveness and stability of the proposed method has been proved. Keywords: Time-series data; correlation mining; WAMS/SCADA data fusion. Instruction With the Power Grid becoming smarter and more integrative, real-time data transmission and analysis in Power Grid is much more important. SCADA plays an important role in traditional power system analysis for a long time. As the WAMS proposed and perfected, it can provide a new method of monitoring and analyzing of Power Grid. Taking no account of time delay, the WAMS is able to monitor measurement data of the whole Power Grid and provide unprecedented data stream to keep the Power Grid safe and stable. However, it is difficult to analyze measurement data, make decisions and become a single reliable system source within a short time because of the inadequacy of deployment of WAMS and high-speed data sources. Therefore, hybrid measurement data of SCADA and WAMS based on response is an important on-line method to estimate and analyze the Power Grid. Because of the differences between WAMS and SCADA’s technology platform, they are different in component, precision, transmission time delay and refresh rate.