Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States

Galen Maclaurin; Wesley Cole; Anthony Lopez; Evan Rosenlieb; Billy Roberts; Andrew Reimers

doi:10.1109/PMAPS.2018.8440289

Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States

Galen Maclaurin, Wesley Cole, Anthony Lopez, Evan Rosenlieb, Billy Roberts, Andrew Reimers

Strategic Energy Analysis Center

Research output: Contribution to conference › Paper › peer-review

3 Scopus Citations

Abstract

Year-to-year variability of photovoltaic (PV) generation is an important factor for project financing as well as for modeling the reliability and resource adequacy of power systems. In this work, we analyze inter-annual variability of PV generation across the contiguous United States using the National Solar Radiation Database (NSRDB) from 1998 to 2014. We compare the estimated PV generation from the typical meteorological year (TMY) against the long-term mean, and find that on average the TMY tends to overpredict estimated PV production. However, we also found significant regional bias and spatial clustering in that comparison, such that there are many regional pockets of underprediction as well. Finally, we show that there is not a single year of data that most closely approximates a representative 'resource year' for all regions of the United States. These results point to the need to understand inter-annual variability at individual sites and to be aware of the shortcomings of using TMY or a single year of data for project or grid modeling.

Original language	American English
Number of pages	4
DOIs	https://doi.org/10.1109/PMAPS.2018.8440289 https://doi.org/10.1109/PMAPS.2018.8440289
State	Published - 17 Aug 2018
Event	2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018 - Boise, United States Duration: 24 Jun 2018 → 28 Jun 2018

Conference

Conference	2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018
Country/Territory	United States
City	Boise
Period	24/06/18 → 28/06/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

NREL Publication Number

NREL/CP-6A20-70726

Keywords

Capacity Value
Long-term Variability
National Solar Radiation Database
Probability Exceedance
PV

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Maclaurin, G., Cole, W., Lopez, A., Rosenlieb, E., Roberts, B., & Reimers, A. (2018). Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States. Paper presented at 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018, Boise, United States. https://doi.org/10.1109/PMAPS.2018.8440289, https://doi.org/10.1109/PMAPS.2018.8440289

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abstract = "Year-to-year variability of photovoltaic (PV) generation is an important factor for project financing as well as for modeling the reliability and resource adequacy of power systems. In this work, we analyze inter-annual variability of PV generation across the contiguous United States using the National Solar Radiation Database (NSRDB) from 1998 to 2014. We compare the estimated PV generation from the typical meteorological year (TMY) against the long-term mean, and find that on average the TMY tends to overpredict estimated PV production. However, we also found significant regional bias and spatial clustering in that comparison, such that there are many regional pockets of underprediction as well. Finally, we show that there is not a single year of data that most closely approximates a representative 'resource year' for all regions of the United States. These results point to the need to understand inter-annual variability at individual sites and to be aware of the shortcomings of using TMY or a single year of data for project or grid modeling.",

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Maclaurin, G , Cole, W , Lopez, A , Rosenlieb, E , Roberts, B & Reimers, A 2018, 'Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States', Paper presented at 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018, Boise, United States, 24/06/18 - 28/06/18. https://doi.org/10.1109/PMAPS.2018.8440289, https://doi.org/10.1109/PMAPS.2018.8440289

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T1 - Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States

AU - Maclaurin, Galen

AU - Cole, Wesley

AU - Lopez, Anthony

AU - Rosenlieb, Evan

AU - Roberts, Billy

AU - Reimers, Andrew

PY - 2018/8/17

Y1 - 2018/8/17

N2 - Year-to-year variability of photovoltaic (PV) generation is an important factor for project financing as well as for modeling the reliability and resource adequacy of power systems. In this work, we analyze inter-annual variability of PV generation across the contiguous United States using the National Solar Radiation Database (NSRDB) from 1998 to 2014. We compare the estimated PV generation from the typical meteorological year (TMY) against the long-term mean, and find that on average the TMY tends to overpredict estimated PV production. However, we also found significant regional bias and spatial clustering in that comparison, such that there are many regional pockets of underprediction as well. Finally, we show that there is not a single year of data that most closely approximates a representative 'resource year' for all regions of the United States. These results point to the need to understand inter-annual variability at individual sites and to be aware of the shortcomings of using TMY or a single year of data for project or grid modeling.

AB - Year-to-year variability of photovoltaic (PV) generation is an important factor for project financing as well as for modeling the reliability and resource adequacy of power systems. In this work, we analyze inter-annual variability of PV generation across the contiguous United States using the National Solar Radiation Database (NSRDB) from 1998 to 2014. We compare the estimated PV generation from the typical meteorological year (TMY) against the long-term mean, and find that on average the TMY tends to overpredict estimated PV production. However, we also found significant regional bias and spatial clustering in that comparison, such that there are many regional pockets of underprediction as well. Finally, we show that there is not a single year of data that most closely approximates a representative 'resource year' for all regions of the United States. These results point to the need to understand inter-annual variability at individual sites and to be aware of the shortcomings of using TMY or a single year of data for project or grid modeling.

KW - Capacity Value

KW - Long-term Variability

KW - National Solar Radiation Database

KW - Probability Exceedance

KW - PV

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ER -

Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States

Abstract

Conference

Bibliographical note

NREL Publication Number

Keywords

UN SDGs

Access to Document

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