DocumentCode :
1626940
Title :
Dynamic parameter identification of generators for smart grid development
Author :
Cheng, Yunzhi ; Lee, Wei-Jen ; Huang, Shun-Hsien ; Adams, John
Author_Institution :
PWR Solutions, Dallas, TX, USA
fYear :
2011
Firstpage :
1
Lastpage :
7
Abstract :
After 2003 blackout, wide area measurement, monitoring, and visualization become one of the most important areas of smart grid initiative. Synchrophasors are precise time-synchronized measurements of certain parameters on the electricity grid, now available from grid monitoring devices called phasor measurement units (PMUs). Phasor data and applications are valuable for grid reliability because they give grid operators and planners unprecedented insight into what is happening on the grid at high resolution, over a wide area in time synchronized mode, and where needed, in real-time. Phasor information gives operator the “current” situation of the system. However, engineers still rely on simulation tool to predict the behavior of the power system and provide possible mitigation measures for system problems. The accuracy of the dynamic parameters are the prerequisite for the reliable solutions. Dynamic parameter identification which aims at obtaining accurate dynamic parameters is one of the central topics in power system studies. This paper proposes a hybrid method combining particle swarm optimization (PSO) and sensitivity analysis (SA) for dynamic parameter identification. The proposed hybrid method provides the right balance and trade-off between convergence and computation speed. In addition, the parallel programming is used to take advantage of multiple core processors to significantly increase the computation speed. The simulation results show the validity and benefit of the proposed algorithm.
Keywords :
electric generators; parallel programming; particle swarm optimisation; power grids; power system measurement; power system parameter estimation; power system reliability; sensitivity analysis; PMU; PSO; dynamic parameter identification; generators; multiple core processors; parallel programming; particle swarm optimization; phasor information; phasor measurement units; power system; reliability; sensitivity analysis; smart grid development; synchrophasors; time-synchronized measurements; wide area measurement; Generators; Parameter estimation; Phasor measurement units; Power system dynamics; Power system reliability; Sensitivity analysis; Simulation; Parallel Programming; Parameter identification; Particle Swarm Optimization (PSO); Phasor Measurement Unit (PMU); Sensitivity Analysis (SA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PES.2011.6039436
Filename :
6039436
Link To Document :
بازگشت