Title :
A Wavelet-Based Variability Model (WVM) for Solar PV Power Plants
Author :
Lave, Matthew ; Kleissl, Jan ; Stein, Joshua S.
Author_Institution :
Mech. & Aerosp. Eng. Dept., Univ. of California, San Diego, La Jolla, CA, USA
fDate :
4/1/2013 12:00:00 AM
Abstract :
A wavelet variability model (WVM) for simulating solar photovoltaic (PV) power plant output given a single irradiance point sensor timeseries using spatio-temporal correlations is presented. The variability reduction (VR) that occurs in upscaling from the single point sensor to the entire PV plant at each timescale is simulated, then combined with the wavelet transform of the point sensor timeseries to produce a simulated power plant output. The WVM is validated against measurements at a 2-MW residential rooftop distributed PV power plant in Ota City, Japan and at a 48-MW utility-scale power plant in Copper Mountain, NV. The WVM simulation matches the actual power output well for all variability timescales, and the WVM compares well against other simulation methods.
Keywords :
photovoltaic power systems; solar power stations; wavelet transforms; Copper Mountain; Japan; NV; Ota City; WVM; power 2 MW; power 48 MW; residential rooftop distributed PV power plant; single irradiance point sensor timeseries; single point sensor; solar photovoltaic power plant; spatio-temporal correlations; utility-scale power plant; variability reduction; wavelet transform; wavelet-based variability model; Cities and towns; Clouds; Copper; Correlation; Indexes; Power generation; Wavelet transforms; Geographic dispersion; photovoltaic (PV); solar; upscaling; variability; wavelets;
Journal_Title :
Sustainable Energy, IEEE Transactions on
DOI :
10.1109/TSTE.2012.2205716