DocumentCode
2847589
Title
Calculation method of active power output of wind farms connected to grids based on FRC
Author
Chen, Ning ; Zhang, Yun
Author_Institution
Sch. of Mech. & Automotive Eng., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
fYear
2010
fDate
26-28 May 2010
Firstpage
2420
Lastpage
2423
Abstract
A new method to calculate active power output of large-scale wind farms connected to power grids, based on the fuzzy random chance-constrained programming(FRC )theory, is presented in this paper. The calculation of calculate active power output can be turned into a FRC programming problem which constrained conditions. A mathematical model of calculate active power in wind power integrated system based on FRC programming form is put forward, including ramp constrains of the generating units, output restricted zone, line transmission capacity, reserved capacity constraints, the balance of load, and so on. The problem can be solved by particle swarm optimization based fuzzy simulations. The results on IEEE30 system demonstrate the advantages of the proposed approach.
Keywords
fuzzy set theory; particle swarm optimisation; power grids; power system interconnection; power transmission lines; wind power plants; FRC theory; IEEE30 system; active power output; fuzzy random chance-constrained programming; fuzzy simulations; large-scale wind farms; line transmission capacity; load balance; particle swarm optimization; power grid connection; reserved capacity constraints; Fluctuations; Large-scale systems; Mathematical model; Mathematical programming; Particle swarm optimization; Wind energy; Wind energy generation; Wind farms; Wind speed; Wind turbines; active power output; fuzzy chance-constrained programming; particle swarm optimization; wind farms;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location
Xuzhou
Print_ISBN
978-1-4244-5181-4
Electronic_ISBN
978-1-4244-5182-1
Type
conf
DOI
10.1109/CCDC.2010.5498806
Filename
5498806
Link To Document