Title :
Research on dynamic load modelling based on power quality monitoring system
Author :
Ren-Feng Yuan ; Qian Ai ; Xing He
Author_Institution :
Dept. of Electr. Eng., Key Lab. of Control of Power Transm. & Transformation, Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
This study proposes a novel approach for load modelling fulfilled in Guangdong Power Grid, Southern China. Dynamic load modelling lies on real-time data provided by load disturbances. These data can be acquired by power quality equipment fixed on each substation. This study introduces the approach to data processing and load modelling during asymmetric disturbance to solve the problems of insufficient inartificial disturbance data. In order to improve the global optimisation capability and identification efficiency in multi-dimensional function, an improved clone selection algorithm is proposed, which includes adaptive-adjust Gaussian mutation operators and the directional evolution mechanism, and also using the character of parameters independence between induction motor model and ZIP model referring to the third-order induction-motor paralleling ZIP model in BPA. The results of practical load modelling prove that the proposed algorithm has great effects on improving model precision and adaptability. Finally, the influences on power angle, frequency, voltage and power between dynamic load model and ZIP are discussed.
Keywords :
Gaussian processes; induction motors; optimisation; power grids; power supply quality; power system measurement; real-time systems; BPA; Guangdong power grid; Southern China; adaptive-adjust Gaussian mutation operators; asymmetric disturbance; data processing; directional evolution mechanism; global optimisation capability; identification efficiency; improved clone selection algorithm; induction motor model; insufficient inartificial disturbance data; load disturbances; model adaptability; model precision; multidimensional function; power quality equipment; power quality monitoring system-based dynamic load modelling; real-time data; third-order induction-motor paralleling ZIP model;
Journal_Title :
Generation, Transmission & Distribution, IET
DOI :
10.1049/iet-gtd.2012.0365