• Title of article

    Cloud speed impact on solar variability scaling – Application to the wavelet variability model

  • Author/Authors

    Matthew Lave a، نويسنده , , Jan Kleissl *، نويسنده ,

  • Issue Information
    ماهنامه با شماره پیاپی سال 2013
  • Pages
    11
  • From page
    11
  • To page
    21
  • Abstract
    The Wavelet Variability Model (WVM) for simulating solar photovoltaic (PV) powerplant output given a single irradiance sensor as input has been developed and validated previously. Central to the WVM method is a correlation scaling coefficient (A) that calibrates the decay of correlation of wavelet modes as a function of distance and timescale, and which varies by day and geographic location. Previously, a local irradiance sensor network was required to derive A. In this work, we determine A from cloud speeds. Cloud simulator results indicated that the A value is linearly proportional to the cloud speed (CS): A ¼ 1 2 CS. Cloud speeds from a numerical weather model (NWM) were then used to create a database of daily A values for North America. For validation, the WVM was run to simulate a 48MW PV plant with both NWM A values and with ground A values found from a sensor network. Both WVM methods closely matched the distribution of ramp rates (RRs) of measured power, and were a strong improvement over linearly scaling up a point sensor. The incremental error in using NWM A values over ground A values was small. The ability to use NWM-derived A values means that the WVM can be used to simulate a PV plant anywhere a single high-frequency irradiance sensor exists. This can greatly assist in module siting, plant sizing, and storage decisions for prospective PV plants. 2013 Elsevier Ltd. All rights reserved
  • Keywords
    WAVELET , variability , Cloud speed , Smoothing , PV powerplant
  • Journal title
    Solar Energy
  • Serial Year
    2013
  • Journal title
    Solar Energy
  • Record number

    941270