DocumentCode :
1308691
Title :
Optimal Power Flow Solution Incorporating Wind Power
Author :
Shi, Libao ; Wang, Chen ; Yao, Liangzhong ; Ni, Yixin ; Bazargan, Masoud
Author_Institution :
Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China
Volume :
6
Issue :
2
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
233
Lastpage :
241
Abstract :
This paper presents a solution of optimal power flow (OPF) incorporating wind power. A paradigm for modeling the cost of wind-generated electricity from a wind farm is proposed. Based on the Weibull wind speed distribution and wind turbine model represented by function approximation, the frequency distribution of wind farm power output to be the basis for modeling wind generation cost is established via applying Monte Carlo simulation. The proposed wind generation cost model consists of the opportunity cost of wind power shortage and the opportunity cost of wind power surplus, which reflect the cost of dispatching additional reserve capacity and the cost of environmental benefit loss, respectively, and it is integrated into the conventional OPF program. Furthermore, the small signal stability constraints are considered simultaneously as well during optimization. A self-adaptive evolutionary programming method is employed to solve the OPF with wind power involved. A case study is conducted based on the IEEE New England test system (10-Generator-39-Bus) as a benchmark. The simulation results demonstrate the effectiveness and validity of the proposed model and method.
Keywords :
Monte Carlo methods; Weibull distribution; load flow; power system simulation; wind power; wind power plants; wind turbines; IEEE New England test system; Monte Carlo simulation; Weibull wind speed distribution; function approximation; optimal power flow solution; self-adaptive evolutionary programming method; wind farm; wind power; wind turbine model; wind-generated electricity; Eigenvalues and eigenfunctions; Electricity; Stability analysis; Wind farms; Wind power generation; Wind speed; Wind turbines; Monte Carlo; optimal power flow (OPF); self-adaptive evolutionary programming; small signal stability; wind power;
fLanguage :
English
Journal_Title :
Systems Journal, IEEE
Publisher :
ieee
ISSN :
1932-8184
Type :
jour
DOI :
10.1109/JSYST.2011.2162896
Filename :
6003750
Link To Document :
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