DocumentCode
2055434
Title
Robust optimization with box set for reactive power optimization in wind power integrated system
Author
Yuwei Yang ; Renjun Zhou ; Xiaohong Ran
Author_Institution
Power Eng., Changsha Univ. of Sci. & Technol., Changsha, China
fYear
2012
fDate
22-26 July 2012
Firstpage
1
Lastpage
6
Abstract
The character of reactive power in wind power integrated system affects active power losses and voltage level of the entire system. For the influence from the randomness of wind speed to entire system power flow, a reactive power optimization model based on Robust Optimization (RO) is presented firstly. With minimizing power losses as an objective, the uncertainty of the wind speed is taken as a random variable and demonstrated in a "box" uncertainty set for transforming the uncertain constraints into the certain form. The duality theorem is utilized to simplify the model to be general linear programming ones. IEEE30-node system is used as an example to test the model and method. The results show that the random wind speed is quantitated effectively, power losses are reduced, and even the voltage of entire system can be restricted within regular range. The reactive power optimization method with RO is simple, feasible and significant.
Keywords
linear programming; reactive power; wind power plants; IEEE 30-node system; active power loss; box set; box uncertainty set; duality theorem; linear programming; random variable; reactive power optimization model; robust optimization; voltage level; wind power integrated system; wind speed uncertainty; Mathematical model; Optimization; Reactive power; Uncertainty; Wind farms; Wind power generation; Wind speed; Robust Optimization (RO); box uncertainty set; duality theorem; power losses; reactive power optimization; the randomness of wind speed;
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.2012.6345174
Filename
6345174
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