Data Challenges in Estimating the Capacity Value of Solar Photovoltaics

Paul Denholm, Dhruv Gami, Ramteen Sioshansi

Research output: Contribution to journalArticlepeer-review

20 Scopus Citations

Abstract

We examine the robustness of solar capacity-value estimates to three important data issues. The first is the sensitivity to using hourly averaged as opposed to subhourly solar-insolation data. The second is the sensitivity to errors in recording and interpreting load data. The third is the sensitivity to using modeled as opposed to measured solar-insolation data. We demonstrate that capacity-value estimates of solar are sensitive to all three of these factors, with potentially large errors in the capacity-value estimate in a particular year. If multiple years of data are available, the biases introduced by using hourly averaged solar-insolation can be smoothed out. Multiple years of data will not necessarily address the other data-related issues that we examine. Our analysis calls into question the accuracy of a number of solar capacity-value estimates relying exclusively on modeled solar-insolation data that are reported in the literature (including our own previous works). Our analysis also suggests that multiple years' historical data should be used for remunerating solar generators for their capacity value in organized wholesale electricity markets.

Original languageAmerican English
Article number7915674
Pages (from-to)1065-1073
Number of pages9
JournalIEEE Journal of Photovoltaics
Volume7
Issue number4
DOIs
StatePublished - Jul 2017

Bibliographical note

Publisher Copyright:
© 2011-2012 IEEE.

NREL Publication Number

  • NREL/JA-6A20-66888

Keywords

  • Capacity value
  • photovoltaic (PV) solar power generation
  • power system reliability

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