Data challenges in estimating the capacity value of solar photovoltaics
- The Ohio State Univ., Columbus, OH (United States)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
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). Lastly, 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.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States); Alliance for Sustainable Energy, Lakewood, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- Grant/Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1354844
- Journal Information:
- IEEE Journal of Photovoltaics, Vol. 7, Issue 4; ISSN 2156-3381
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Capacity value estimation of random solar power through associative searching in a k‐d tree
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journal | May 2019 |
Inter-annual variability of wind and solar electricity generation and capacity values in Texas
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journal | April 2019 |
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