Title :
Power system load modeling by learning based on system measurements
Author :
Wen, J.Y. ; Jiang, L. ; Wu, Q.H. ; Cheng, S.J.
Author_Institution :
Dept. of Electr. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, Taiwan
fDate :
4/1/2003 12:00:00 AM
Abstract :
This paper is concerned with an investigation of a methodology using intelligent learning techniques based on system measurements to construct power system load models alongside with distribution network reduction. A comprehensive load model is proposed to represent the loads in an area of a power system. A population diversity-based genetic algorithm (GA) is developed to obtain the structure and parameters of the load model. Simulation results on a five-bus power system and an IEEE 30-bus power system are given to show the potential of this new methodology of power system modeling.
Keywords :
distribution networks; genetic algorithms; load (electric); power system simulation; IEEE 30-bus power system; distribution network reduction; five-bus power system; intelligent learning techniques; learning; population diversity; population diversity-based genetic algorithm; power system load modeling; system measurements; Genetic algorithms; Load modeling; Machine learning algorithms; Mathematical model; Power measurement; Power system dynamics; Power system measurements; Power system modeling; Power system planning; Power system simulation;
Journal_Title :
Power Delivery, IEEE Transactions on
DOI :
10.1109/TPWRD.2003.809730
