Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat; Black, Jon; Tedesco, John

doi:10.1016/j.solener.2015.09.047

Title: Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

Abstract

Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial tomore » power systems operations.« less

Authors:

Zhang, Jie ^[1]; Hodge, Bri -Mathias ^[1]; Lu, Siyuan ^[2]; Hamann, Hendrik F. ^[2]; Lehman, Brad ^[3]; Simmons, Joseph ^[4]; Campos, Edwin ^[5]; Banunarayanan, Venkat ^[6]; Black, Jon ^[7]; Tedesco, John ^[8]

National Renewable Energy Lab. (NREL), Golden, CO (United States)
IBM TJ Watson Research Center, Yorktown Heights, NY (United States)
Northeastern Univ., Boston, MA (United States)
Univ. of Arizona, Tucson, AZ (United States)
Argonne National Lab. (ANL), Lemont, IL (United States)
U.S. Dept. of Energy, Washington, D.C. (United States)
ISO New England, Holyoke, MA (United States)
Green Mountain Power, Colchester, VT (United States)

Publication Date:: Tue Nov 10 00:00:00 EST 2015

Research Org.:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

OSTI Identifier:: 1238036

Alternate Identifier(s):: OSTI ID: 1245234

Report Number(s):: NREL/JA-5D00-65285
Journal ID: ISSN 0038-092X

Grant/Contract Number:: AC36-08GO28308; AC36-08-GO28308

Resource Type:: Accepted Manuscript

Journal Name:: Solar Energy

Additional Journal Information:: Journal Volume: 122; Related Information: Solar Energy; Journal ID: ISSN 0038-092X

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 14 SOLAR ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; numerical weather prediction; operating reserve; ramp forecasting; PV power forecasting; National Renewable Energy Laboratory; NREL

Citation Formats


                    Zhang, Jie, Hodge, Bri -Mathias, Lu, Siyuan, Hamann, Hendrik F., Lehman, Brad, Simmons, Joseph, Campos, Edwin, Banunarayanan, Venkat, Black, Jon, and Tedesco, John. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting.  United States: N. p., 2015. 
Web.  doi:10.1016/j.solener.2015.09.047.

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                    Zhang, Jie, Hodge, Bri -Mathias, Lu, Siyuan, Hamann, Hendrik F., Lehman, Brad, Simmons, Joseph, Campos, Edwin, Banunarayanan, Venkat, Black, Jon, & Tedesco, John. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting.  United States.  https://doi.org/10.1016/j.solener.2015.09.047

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                    Zhang, Jie, Hodge, Bri -Mathias, Lu, Siyuan, Hamann, Hendrik F., Lehman, Brad, Simmons, Joseph, Campos, Edwin, Banunarayanan, Venkat, Black, Jon, and Tedesco, John. Tue .  
"Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting".  United States.  https://doi.org/10.1016/j.solener.2015.09.047.  https://www.osti.gov/servlets/purl/1238036.

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@article{osti_1238036,

  title        = {Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting},

  author       = {Zhang, Jie and Hodge, Bri -Mathias and Lu, Siyuan and Hamann, Hendrik F. and Lehman, Brad and Simmons, Joseph and Campos, Edwin and Banunarayanan, Venkat and Black, Jon and Tedesco, John},

  abstractNote = {Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.},

  doi          = {10.1016/j.solener.2015.09.047},

  journal      = {Solar Energy},

  number       = ,

  volume       = 122,

  place        = {United States},

  year         = {Tue Nov 10 00:00:00 EST 2015},

  month        = {Tue Nov 10 00:00:00 EST 2015}

}

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Works referencing / citing this record:

Spatial autocorrelation and entropy for renewable energy forecasting
journal, January 2019

Ceci, Michelangelo; Corizzo, Roberto; Malerba, Donato
Data Mining and Knowledge Discovery, Vol. 33, Issue 3
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Predictive analysis of photovoltaic plants specific yield with the implementation of multiple linear regression tool
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Babatunde, Akinola A.; Abbasoglu, Serkan
Environmental Progress & Sustainable Energy, Vol. 38, Issue 4
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Title: Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

Abstract

Citation Formats

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