Simulating Solar Power Plant Variability: A Review of Current Methods

It is important to be able to accurately simulate the variability of solar PV power plants for grid integration studies. We aim to inform integration studies of the ease of implementation and application-specific accuracy of current PV power plant output simulation methods. This report reviews methods for producing simulated highresolution (sub-hour or even sub-minute) PV power plant output profiles for variability studies and describes their implementation. Two steps are involved in the simulations: estimation of average irradiance over the footprint of a PV plant and conversion of average irradiance to plant power output. Six models are described for simulating plant-average irradiance based on inputs of ground-measured irradiance, satellite-derived irradiance, or proxy plant measurements. The steps for converting plant-average irradiance to plant power output are detailed to understand the contributions to plant variability. A forthcoming report will quantify the accuracy of each method using application-specific validation metrics.

[1]  P. Ineichen,et al.  A new airmass independent formulation for the Linke turbidity coefficient , 2002 .

[2]  William A. Beckman,et al.  Improvement and validation of a model for photovoltaic array performance , 2006 .

[3]  A. D. Jones,et al.  A thermal model for photovoltaic systems , 2001 .

[4]  Kara Clark,et al.  Western Wind and Solar Integration Study , 2011 .

[5]  Luis Marroyo,et al.  From irradiance to output power fluctuations: the PV plant as a low pass filter , 2011 .

[6]  A. Ellis,et al.  Analyzing and simulating the reduction in PV powerplant variability due to geographic smoothing in Ota City, Japan and Alamosa, CO , 2012, 2012 IEEE 38th Photovoltaic Specialists Conference (PVSC) PART 2.

[7]  Clifford W. Hansen,et al.  Estimating Annual Synchronized 1-Min Power Output Profiles from Utility-Scale PV Plants at 10 Locations in Nevada for a Solar Grid Integration Study , 2011 .

[8]  M. Hummon,et al.  Sub-Hour Solar Data for Power System Modeling From Static Spatial Variability Analysis: Preprint , 2012 .

[9]  William E. Boyson,et al.  Photovoltaic array performance model. , 2004 .

[10]  Sandia Report,et al.  Time Series Power Flow Analysis for Distribution Connected PV Generation , 2013 .

[11]  J. Michalsky,et al.  Modeling daylight availability and irradiance components from direct and global irradiance , 1990 .

[12]  Joshua S. Stein,et al.  IMPROVEMENT AND VALIDATION OF A TRANSIENT MODEL TO PREDICT PHOTOVOLTAIC MODULE TEMPERATURE. , 2012 .

[13]  Jan Kleissl,et al.  Cloud speed impact on solar variability scaling – Application to the wavelet variability model , 2013 .

[14]  Sigifredo Gonzalez,et al.  Performance Model for Grid-Connected Photovoltaic Inverters , 2007 .

[15]  A. Longhetto,et al.  Effect of correlations in time and spatial extent on performance of very large solar conversion systems , 1989 .

[16]  Clifford W. Hansen Validation of simulated irradiance and power for the Western Wind and Solar Integration Study. Phase II. , 2012 .

[17]  Praveen Jain,et al.  Beyond the curves: Modeling the electrical efficiency of photovoltaic inverters , 2008, 2008 33rd IEEE Photovoltaic Specialists Conference.

[18]  S. Wilcox National Solar Radiation Database 1991-2010 Update: User's Manual , 2012 .

[19]  J. S. Stein,et al.  The photovoltaic Performance Modeling Collaborative (PVPMC) , 2012, 2012 38th IEEE Photovoltaic Specialists Conference.

[20]  A. Kimber,et al.  The Effect of Soiling on Large Grid-Connected Photovoltaic Systems in California and the Southwest Region of the United States , 2006, 2006 IEEE 4th World Conference on Photovoltaic Energy Conference.

[21]  P. Ineichen,et al.  A new operational model for satellite-derived irradiances: description and validation , 2002 .

[22]  J. Kleissl,et al.  A Wavelet-Based Variability Model (WVM) for Solar PV Power Plants , 2013, IEEE Transactions on Sustainable Energy.