Artificial neural network based dynamic load modeling

• Published in: IEEE transactions on power systems Vol. 12; no. 4; pp. 1576 - 1583
• Main Authors: Hiyama, T., Tokieda, M., Hubbi, W., Andou, H.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-11-1997; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Artificial neural networks; Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; Feedback loop; Frequency response; Load modeling; Power demand; Power networks and lines; Power system dynamics; Power system modeling; Power system transients; Testing; Theory. Simulation; Voltage; Power system load; Frequency response; Neural network; Dynamical system; Artificial intelligence; Modeling
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/59.627861

The aim of this research is to investigate the use of artificial neural networks (ANN) with feedback loops for the modeling of power system dynamic loads using field data. In addition to the power demand before the transient, only the phase voltages are assumed available at the recall stage. It is found that the load dynamics can be identified using the ANN developed for the season and the location of the load being emulated. The frequency response of the tested load is also obtained using the achieved ANN model.