Title :
Statistical Characterization of Wind Power Ramps Via Extreme Value Analysis
Author :
Ganger, David ; Junshan Zhang ; Vittal, Vijay
Author_Institution :
Sch. of Electr., Comput., & Energy Eng., Arizona State Univ., Tempe, AZ, USA
Abstract :
Extreme power fluctuations in wind farms are rare but high-impact events, so proper characterization of these extreme fluctuations would assist with power systems operations planning in a power system with a high penetration of wind power. This work applies extreme value analysis methods to the statistical characterization of wind power ramps with 10-min resolution. The annual maxima series (AMS) method and peaks over threshold (POT) method are used to determine the probability of extreme wind power ramp events in a wind farm.
Keywords :
fluctuations; power system planning; wind power plants; AMS; POT; annual maxima series; extreme fluctuations; extreme power fluctuations; extreme value analysis; peaks over threshold; power systems operations planning; statistical characterization; wind farms; wind power ramps; Power generation planning; Statistical analysis; Wind energy; Wind farms; Wind forecasting; Wind power generation; Extreme events; extreme value analysis; ramp events; statistical analysis; wind energy;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2014.2315491