Composite Neural Network Load Models for Power System Stability Analysis

Ali Keyhani, Wenzhe Lu, Gerald T. Heydt
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA

This paper appears in: IEEE Power Engineering Society 2004 Power Systems Conference & Exposition
Date: October 10-13, 2004
Location: New York City, NY

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Abstract:
Proper load models are essential to power system stability analysis. This paper proposes a methodology for the development of neural network (NN) based composite load mod-els for power system stability analysis. A two-step modeling pro-cedure is proposed. First knowledge is acquired from a test bed of power systems based on detail load models of a bus to the dis-tribution level. Then, the test bed data is used to develop a com-posite NN model. The developed NN model is updated based on measurements. A case study on a power inverter controling an induction motor load is presented.