Power System Oscillation Mode Prediction Data

Citation Author(s):
South China University of Technology
Submitted by:
weike mo
Last updated:
Wed, 09/04/2019 - 02:02
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This paper utilizes modern statistical and machine learning methodology to track oscillation modes in complex power engineering systems. The damping ratio of the electromechanical oscillation mode is formulated as a function of power of the generators and loads as well as bus voltage magnitudes in the entire power system. The celebrated Lasso algorithm is implemented to solve this high-dimension modeling problem. By the nature of the $L_1$ design, the Lasso algorithm can automatically render a sparse solution, and by eliminating redundant features, it provides desirable prediction power. The resultant model processes a simple structure, and it is easily interpretable. The precision of our sparse modeling framework is demonstrated in the context of an IEEE 50-Generator 145-Bus power network.


Data struct (500 cases): 1-145 bus voltage magnitude, 146-245 active and reactive power of generators, 246-373 active and reactive power of loads, 374 the intra-area mode, 374 the inter-area mode.


Submitted by Kumar Prabhakar on Wed, 12/09/2020 - 02:26