Title :
Flatlands wind farm power generation and wake effect analysis based on Jensen model
Author :
Li Zhuonan ; Ai Xin
Author_Institution :
State Key Lab. of Alternate Electr. Power Syst. With Renewable Energy Sources, North China Electr. Power Univ., Beijing, China
Abstract :
Wind power forecast and accurate wind farm modeling play an important role in wind power generation. In this paper, models of power output, wind turbine layouts and wake effect including outage units are established. Theoretical calculations of power generation, wake effect in Jensen model and program of Back Propagation Neural Network algorithm are performed, for the purpose of having a comprehensive study on wind power generation forecast using BPNN algorithms as well as the influence of outage and wake effect. The calculation results are compared with the actual data collected from a wind farm in northeast China. The approach to an intuitive analysis of wake effect and wind power forecast in a specific wind farm is proposed.
Keywords :
backpropagation; load forecasting; neural nets; power engineering computing; power system planning; power system reliability; statistical distributions; wind power plants; wind turbines; BPNN algorithms; Jensen model; Northeast China; back propagation neural network algorithm; flatlands wind farm power generation; wake effect analysis; wind farm modeling; wind power forecast; wind turbine layouts; Generators; Power systems; Training; Wind farms; Wind power generation; Wind speed; Wind turbines; Back Propagation Neural Network; Jensen model; Wake effect; Wind power;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2013 IEEE PES Asia-Pacific
Conference_Location :
Kowloon
DOI :
10.1109/APPEEC.2013.6837159
