DocumentCode :
2067209
Title :
Power system probabilistic cost production simulation with wind power penetration based on multi-state system theory
Author :
Xu Liu ; Hongtao Wang ; Qinyong Zhou ; Bin Hu
Author_Institution :
Sch. of Electr. Eng., Shandong Univ., Jinan, China
fYear :
2012
fDate :
22-26 July 2012
Firstpage :
1
Lastpage :
7
Abstract :
A new model and the relevant algorithm for the power system probabilistic cost production simulation with wind power penetration based on chronological load curve using universal generating function (UGF) methods of multi-state system theory considering the characteristics of both load and wind power are presented in this paper. The power output models of wind farm, conventional units and load considering the reliability of conventional units and wind turbine generators(WTGs), wind speed correlation and load forecast uncertainty are developed using universal generating function methods in each sub-period. The special operators for these UGFs are defined to describe the process of the power system probabilistic cost production simulation with wind power penetration. The calculation and analysis have been executed on the IEEE-RTS test system integrated wind farms.
Keywords :
AC generators; IEEE standards; costing; load forecasting; power generation reliability; probability; wind power plants; IEEE-RTS test system integrated wind farms; UGF methods; WTG; chronological load curve; conventional unit reliability; load forecast uncertainty; multistate system theory; power system probabilistic cost production simulation; universal generating function methods; wind farm power output models; wind power penetration; wind speed correlation; wind turbine generators; Load modeling; Power systems; Probabilistic logic; Production; Reliability; Wind farms; Wind power generation; Multi-State System Theory; Operating Cost; Probabilistic Cost Production Simulation; Universal Generating Function; Wind Power;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PESGM.2012.6345615
Filename :
6345615
Link To Document :
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