Title :
Clustering based online identification of secondary dynamic parameters for measurement based composite load modeling
Author :
Shuqing Zhang ; Xiaofei Liu ; Junwei Cao ; Guoyu Tu ; Yuxin Wan
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Abstract :
Accurate modeling and parameter identification of electrical load is always a difficult problem, remaining unsolved but critical for stability analysis, prediction and decision-making of power systems. The development of wide area measurement system (WAMS) provides possible way´s to further address the challenge. In this work, based on an existing load modeling method for online identification of dominant parameters, we put forward an improvement with the clustering method, to get the reactance of the composite load model as a secondary dynamic parameter. Corresponding theoretical analysis, design principles and system implementation are presented. The reactive power damping time constant during disturbance is chosen as the clustering feature. Simulation results show effectiveness of our improvement with satisfactory accuracy.
Keywords :
load (electric); parameter estimation; pattern clustering; power system measurement; power system simulation; power system stability; reactive power; WAMS; clustering method; composite load modeling; dominant parameters; electrical load; online identification; power systems; reactive power damping time constant; secondary dynamic parameters; stability analysis; wide area measurement system; Accuracy; Algorithm design and analysis; Clustering algorithms; Damping; Load modeling; Power system dynamics; Simulation; WAMS; clustering; composite load modeling; parameter identification; secondary dynamic parameters;
Conference_Titel :
Innovative Smart Grid Technologies Conference (ISGT), 2015 IEEE Power & Energy Society
Conference_Location :
Washington, DC
DOI :
10.1109/ISGT.2015.7131911