Identification of power system load dynamics using artificial neural networks

Power system loads are important for planning and operation of an electric power system. Load characteristics can significantly influence the results of synchronous stability and voltage stability studies. This paper presents a methodology for identification of power system load dynamics using neural networks. Input-output data of a power system dynamic load is used to design a neural network model which comprises delayed inputs and feedback connections. The developed neural network model can predict the future power system dynamic load behavior for arbitrary inputs. In particular, a third-order induction motor load neural network model is developed to verify the methodology. Neural network simulation results are illustrated and compared with the induction motor load response.