Verification of deterministic solar forecasts
•This review aims at standardizing the forecast verification approaches used in deterministic solar forecasting.•The distribution-oriented forecast verification framework is introduced.•RMSE skill score is recommended to be universally reported in solar forecasting studies.•A series of practical iss...
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| Veröffentlicht in: | Solar energy Jg. 210; S. 20 - 37 |
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Elsevier Ltd
01.11.2020
Pergamon Press Inc Elsevier |
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| ISSN: | 0038-092X, 1471-1257, 1471-1257 |
| Online-Zugang: | Volltext |
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| Abstract | •This review aims at standardizing the forecast verification approaches used in deterministic solar forecasting.•The distribution-oriented forecast verification framework is introduced.•RMSE skill score is recommended to be universally reported in solar forecasting studies.•A series of practical issues during verification are reviewed.
The field of energy forecasting has attracted many researchers from different fields (e.g., meteorology, data sciences, mechanical or electrical engineering) over the last decade. Solar forecasting is a fast-growing subdomain of energy forecasting. Despite several previous attempts, the methods and measures used for verification of deterministic (also known as single-valued or point) solar forecasts are still far from being standardized, making forecast analysis and comparison difficult.
To analyze and compare solar forecasts, the well-established Murphy–Winkler framework for distribution-oriented forecast verification is recommended as a standard practice. This framework examines aspects of forecast quality, such as reliability, resolution, association, or discrimination, and analyzes the joint distribution of forecasts and observations, which contains all time-independent information relevant to verification. To verify forecasts, one can use any graphical display or mathematical/statistical measure to provide insights and summarize the aspects of forecast quality. The majority of graphical methods and accuracy measures known to solar forecasters are specific methods under this general framework.
Additionally, measuring the overall skillfulness of forecasters is also of general interest. The use of the root mean square error (RMSE) skill score based on the optimal convex combination of climatology and persistence methods is highly recommended. By standardizing the accuracy measure and reference forecasting method, the RMSE skill score allows—with appropriate caveats—comparison of forecasts made using different models, across different locations and time periods. |
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| AbstractList | The field of energy forecasting has attracted many researchers from different fields (e.g., meteorology, data sciences, mechanical or electrical engineering) over the last decade. Solar forecasting is a fast-growing sub-domain of energy forecasting. Despite several previous attempts, the methods and measures used for verification of deterministic (also known as single-valued or point) solar forecasts are still far from being standardized, making forecast analysis and comparison difficult. To analyze and compare solar forecasts, the well-established Murphy-Winkler framework for distribution-oriented forecast verification is recommended as a standard practice. This framework examines aspects of forecast quality, such as reliability, resolution, association, or discrimination, and analyzes the joint distribution of forecasts and observations, which contains all time-independent information relevant to verification. To verify forecasts, one can use any graphical display or mathematical/statistical measure to provide insights and summarize the aspects of forecast quality. The majority of graphical methods and accuracy measures known to solar forecasters are specific methods under this general framework. Additionally, measuring the overall skillfulness of forecasters is also of general interest. The use of the root mean square error (RMSE) skill score based on the optimal convex combination of climatology and persistence methods is highly recommended. By standardizing the accuracy measure and reference forecasting method, the RMSE skill score allows-with appropriate caveats-comparison of forecasts made using different models, across different locations and time periods. The field of energy forecasting has attracted many researchers from different fields (e.g., meteorology, data sciences, mechanical or electrical engineering) over the last decade. Solar forecasting is a fast-growing subdomain of energy forecasting. Despite several previous attempts, the methods and measures used for verification of deterministic (also known as single-valued or point) solar forecasts are still far from being standardized, making forecast analysis and comparison difficult. To analyze and compare solar forecasts, the well-established Murphy–Winkler framework for distribution-oriented forecast verification is recommended as a standard practice. This framework examines aspects of forecast quality, such as reliability, resolution, association, or discrimination, and analyzes the joint distribution of forecasts and observations, which contains all time-independent information relevant to verification. To verify forecasts, one can use any graphical display or mathematical/statistical measure to provide insights and summarize the aspects of forecast quality. The majority of graphical methods and accuracy measures known to solar forecasters are specific methods under this general framework. Additionally, measuring the overall skillfulness of forecasters is also of general interest. The use of the root mean square error (RMSE) skill score based on the optimal convex combination of climatology and persistence methods is highly recommended. By standardizing the accuracy measure and reference forecasting method, the RMSE skill score allows-with appropriate caveats-comparison of forecasts made using different models, across different locations and time periods. •This review aims at standardizing the forecast verification approaches used in deterministic solar forecasting.•The distribution-oriented forecast verification framework is introduced.•RMSE skill score is recommended to be universally reported in solar forecasting studies.•A series of practical issues during verification are reviewed. The field of energy forecasting has attracted many researchers from different fields (e.g., meteorology, data sciences, mechanical or electrical engineering) over the last decade. Solar forecasting is a fast-growing subdomain of energy forecasting. Despite several previous attempts, the methods and measures used for verification of deterministic (also known as single-valued or point) solar forecasts are still far from being standardized, making forecast analysis and comparison difficult. To analyze and compare solar forecasts, the well-established Murphy–Winkler framework for distribution-oriented forecast verification is recommended as a standard practice. This framework examines aspects of forecast quality, such as reliability, resolution, association, or discrimination, and analyzes the joint distribution of forecasts and observations, which contains all time-independent information relevant to verification. To verify forecasts, one can use any graphical display or mathematical/statistical measure to provide insights and summarize the aspects of forecast quality. The majority of graphical methods and accuracy measures known to solar forecasters are specific methods under this general framework. Additionally, measuring the overall skillfulness of forecasters is also of general interest. The use of the root mean square error (RMSE) skill score based on the optimal convex combination of climatology and persistence methods is highly recommended. By standardizing the accuracy measure and reference forecasting method, the RMSE skill score allows—with appropriate caveats—comparison of forecasts made using different models, across different locations and time periods. |
| Author | Beyer, Hans Georg Alessandrini, Stefano Killinger, Sven Perpiñán-Lamigueiro, Oscar Renné, David Paulescu, Marius Antonanzas, Javier Gueymard, Christian A. Frimane, Âzeddine van der Meer, Dennis Badescu, Viorel Vignola, Frank David, Mathieu Reikard, Gordon Saint-Drenan, Yves-Marie Bright, Jamie M. Hong, Tao Verbois, Hadrien Blaga, Robert Kay, Merlinde J. Lauret, Philippe Shuai, Yong Kleissl, Jan Peters, Ian Marius Urraca, Ruben Coimbra, Carlos F.M. Yang, Dazhi Voyant, Cyril Lorenz, Elke Zhang, Jie Antonanzas-Torres, Fernando Boland, John Perez, Richard |
| Author_xml | – sequence: 1 givenname: Dazhi orcidid: 0000-0001-8427-0718 surname: Yang fullname: Yang, Dazhi email: yangdazhi.nus@gmail.com organization: Singapore Institute of Manufacturing Technology, Agency for Science, Technology and Research, Singapore – sequence: 2 givenname: Stefano orcidid: 0000-0002-7382-1294 surname: Alessandrini fullname: Alessandrini, Stefano organization: Research Application Laboratory, National Center for Atmospheric Research, Boulder, CO, USA – sequence: 3 givenname: Javier surname: Antonanzas fullname: Antonanzas, Javier organization: Deparment of Mechanical Engineering, University of La Rioja, Logrono, Spain – sequence: 4 givenname: Fernando surname: Antonanzas-Torres fullname: Antonanzas-Torres, Fernando organization: Deparment of Mechanical Engineering, University of La Rioja, Logrono, Spain – sequence: 5 givenname: Viorel surname: Badescu fullname: Badescu, Viorel organization: Candida Oancea Institute, Polytechnic University of Bucharest, Bucharest, Romania – sequence: 6 givenname: Hans Georg surname: Beyer fullname: Beyer, Hans Georg organization: Faculty of Science and Technology, University of the Faroe Islands, Tórshavn, Faroe Islands – sequence: 7 givenname: Robert orcidid: 0000-0001-9379-9701 surname: Blaga fullname: Blaga, Robert organization: Faculty of Physics, West University of Timisoara, Timisoara, Romania – sequence: 8 givenname: John orcidid: 0000-0003-0362-4655 surname: Boland fullname: Boland, John organization: Centre for Industrial and Applied Mathematics, University of South Australia, Mawson Lakes, SA, Australia – sequence: 9 givenname: Jamie M. surname: Bright fullname: Bright, Jamie M. organization: Solar Energy Research Institute of Singapore, National University of Singapore, Singapore – sequence: 10 givenname: Carlos F.M. surname: Coimbra fullname: Coimbra, Carlos F.M. organization: Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA, USA – sequence: 11 givenname: Mathieu orcidid: 0000-0002-4134-7196 surname: David fullname: David, Mathieu organization: PIMENT Laboratory, University of La Reunion, Reunion, France – sequence: 12 givenname: Âzeddine surname: Frimane fullname: Frimane, Âzeddine organization: Faculty of Science, Ibn Tofail University, Kenitra, Morocco – sequence: 13 givenname: Christian A. surname: Gueymard fullname: Gueymard, Christian A. organization: Solar Consulting Services, Colebrook, NH, USA – sequence: 14 givenname: Tao orcidid: 0000-0003-0453-1143 surname: Hong fullname: Hong, Tao organization: Department of Systems Engineering and Engineering Management, University of North Carolina at Charlotte, Charlotte, NC, USA – sequence: 15 givenname: Merlinde J. surname: Kay fullname: Kay, Merlinde J. organization: School of Photovoltaic and Renewable Energy Engineering, University of New South Wales, Sydney, NSW, Australia – sequence: 16 givenname: Sven orcidid: 0000-0003-2959-6146 surname: Killinger fullname: Killinger, Sven organization: Fraunhofer Institute for Solar Energy Systems ISE, Freiburg, Germany – sequence: 17 givenname: Jan surname: Kleissl fullname: Kleissl, Jan organization: Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA, USA – sequence: 18 givenname: Philippe orcidid: 0000-0003-2574-0745 surname: Lauret fullname: Lauret, Philippe organization: PIMENT Laboratory, University of La Reunion, Reunion, France – sequence: 19 givenname: Elke surname: Lorenz fullname: Lorenz, Elke organization: Fraunhofer Institute for Solar Energy Systems ISE, Freiburg, Germany – sequence: 20 givenname: Dennis orcidid: 0000-0001-8197-5181 surname: van der Meer fullname: van der Meer, Dennis organization: Department of Civil and Industrial Engineering, Uppsala University, Uppsala, Sweden – sequence: 21 givenname: Marius surname: Paulescu fullname: Paulescu, Marius organization: Faculty of Physics, West University of Timisoara, Timisoara, Romania – sequence: 22 givenname: Richard surname: Perez fullname: Perez, Richard organization: Atmospheric Sciences Research Center, University at Albany, SUNY, Albany, NY, USA – sequence: 23 givenname: Oscar surname: Perpiñán-Lamigueiro fullname: Perpiñán-Lamigueiro, Oscar organization: School of Engineering and Industrial Design, Polytechnic University of Madrid, Madrid, Spain – sequence: 24 givenname: Ian Marius surname: Peters fullname: Peters, Ian Marius organization: Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA – sequence: 25 givenname: Gordon orcidid: 0000-0003-1132-7589 surname: Reikard fullname: Reikard, Gordon organization: Statistics Department, U.S. Cellular, Chicago, IL, USA – sequence: 26 givenname: David surname: Renné fullname: Renné, David organization: Dave Renné Renewables, Boulder, CO, USA – sequence: 27 givenname: Yves-Marie surname: Saint-Drenan fullname: Saint-Drenan, Yves-Marie organization: MINES ParisTech, PSL Research University, Sophia Antipolis, France – sequence: 28 givenname: Yong orcidid: 0000-0003-0242-7377 surname: Shuai fullname: Shuai, Yong organization: School of Energy Science and Engineering, Harbin Institute of Technology, Harbin, Heilongjiang, China – sequence: 29 givenname: Ruben orcidid: 0000-0003-2977-5697 surname: Urraca fullname: Urraca, Ruben organization: Deparment of Mechanical Engineering, University of La Rioja, Logrono, Spain – sequence: 30 givenname: Hadrien orcidid: 0000-0002-9465-3453 surname: Verbois fullname: Verbois, Hadrien organization: Solar Energy Research Institute of Singapore, National University of Singapore, Singapore – sequence: 31 givenname: Frank surname: Vignola fullname: Vignola, Frank organization: Material Science Institute, University of Oregon, Eugene, OR, USA – sequence: 32 givenname: Cyril surname: Voyant fullname: Voyant, Cyril organization: PIMENT Laboratory, University of La Reunion, Reunion, France – sequence: 33 givenname: Jie surname: Zhang fullname: Zhang, Jie organization: Department of Mechanical Engineering, University of Texas at Dallas, Richardson, TX, USA |
| BackLink | https://hal.science/hal-02899290$$DView record in HAL https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-424636$$DView record from Swedish Publication Index (Uppsala universitet) |
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| Cites_doi | 10.1016/j.solener.2019.12.042 10.1016/j.rser.2019.04.006 10.1016/j.solener.2016.06.069 10.1063/5.0003495 10.5194/gmd-7-1247-2014 10.1016/j.solener.2018.02.008 10.2174/1874282300802010023 10.1016/j.solener.2017.02.010 10.1016/j.solener.2015.10.010 10.1016/j.energy.2014.11.082 10.1198/016214506000001437 10.1016/j.solener.2014.10.016 10.1016/j.pecs.2018.10.003 10.1057/palgrave.jors.2602597 10.18777/ieashc-task46-2015-0001 10.1016/j.solener.2013.05.005 10.1016/j.rser.2018.08.023 10.1002/pip.2799 10.1016/j.solener.2016.01.049 10.1016/j.solener.2017.04.064 10.1016/j.solener.2015.09.031 10.1016/j.rser.2019.02.032 10.1016/j.solener.2019.08.078 10.1002/met.60 10.1016/j.solener.2017.09.043 10.1016/j.solener.2017.09.032 10.3354/cr030079 10.1063/1.5114985 10.1063/1.5087588 10.1002/2013JD020301 10.1016/j.solener.2018.10.065 10.1016/j.solener.2019.11.090 10.1016/j.renene.2015.12.031 10.1016/j.energy.2013.04.027 10.1175/1520-0434(1989)004<0485:DVOTF>2.0.CO;2 10.1016/j.solener.2018.06.048 10.1016/j.solener.2015.04.032 10.1016/j.solener.2016.06.062 10.1016/j.rser.2015.04.081 10.1175/1520-0434(1993)008<0281:WIAGFA>2.0.CO;2 10.1016/j.solener.2017.07.032 10.1175/2008WAF2222133.1 10.1016/j.rser.2017.05.212 10.1016/j.solener.2011.06.031 10.1127/metz/2019/0946 10.1115/1.4007496 10.1016/j.solener.2012.12.004 10.1002/pip.2225 10.1016/S0169-2070(00)00065-0 10.1260/030952405776234599 10.1016/j.solener.2017.01.058 10.1002/pip.1127 10.1063/1.5087463 10.1016/j.pecs.2013.06.002 10.1016/0038-092X(90)90055-H 10.1016/j.solener.2015.12.031 10.1198/jasa.2011.r10138 10.1016/j.renene.2016.12.095 10.1175/1520-0493(1988)116<2417:SSBOTM>2.0.CO;2 10.1175/2010BAMS2819.1 10.1016/j.solener.2017.11.023 10.1016/j.ijforecast.2016.02.001 10.1175/1520-0434(1992)007<0692:CPATLC>2.0.CO;2 10.1016/j.rser.2018.04.116 10.1063/1.5087462 10.1016/j.solener.2016.12.053 10.1115/ES2011-54519 10.1016/j.solener.2019.10.006 10.5194/amt-6-2403-2013 10.1016/j.solener.2011.11.011 10.1175/1520-0477(1971)052<0239:FAPFSC>2.0.CO;2 10.1016/j.ijforecast.2006.03.001 10.1016/j.solener.2017.10.052 10.1016/j.renene.2017.04.049 10.3390/atmos9070264 10.1175/1520-0493(1987)115<1330:AGFFFV>2.0.CO;2 |
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| Copyright | 2020 International Solar Energy Society Copyright Pergamon Press Inc. Nov 1, 2020 Distributed under a Creative Commons Attribution 4.0 International License |
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| Keywords | Combination of climatology and persistence Distribution-oriented forecast verification Solar forecasting Skill score Measure-oriented forecast verification |
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| References | Lave, M., Kleissl, J., Arias-Castro, E., 2012. High-frequency irradiance fluctuations and geographic smoothing. Sol. Energy 86, 2190–2199. URL Gneiting, Raftery (b0080) 2007; 102 Inman, Edson, Coimbra (b0120) 2015; 117 van der Meer, Widén, Munkhammar (b0225) 2018; 81 Armstrong (b0025) 2001 Antonanzas-Torres, Urraca, Polo, Perpiñán-Lamigueiro, Escobar (b0020) 2019; 107 Yang, Perez (b0410) 2019; 11 Hong, Pinson, Fan, Zareipour, Troccoli, Hyndman (b0105) 2016; 32 Blaga (b0035) 2019; 191 Yang (b0395) 2019; 11 Yang, D., Kleissl, J., Gueymard, C.A., Pedro, H.T.C., Coimbra, C.F.M., 2018. History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining. Sol. Energy 168, 60–101. Advances in Solar Resource Assessment and Forecasting. URL Murphy, Brown, Chen (b0255) 1989; 4 Willmott, Matsuura (b0370) 2005; 30 Gneiting (b0075) 2011; 106 Sun, Bright, Gueymard, Acord, Wang, Engerer (b0330) 2019; 111 Urraca, Huld, Lindfors, Riihelä, de Pison, Sanz-Garcia (b0345) 2018; 176 Hoff, Perez, Kleissl, Renne, Stein (b0100) 2013; 21 Murphy (b0250) 1997 Schilling (b0320) 2017 Perpiñán, Marcos, Lorenzo (b0290) 2013; 88 Yang (bib426) 2020; 12 Dong, Yang, Reindl, Walsh (b0055) 2013; 55 Martinez-Anido, Botor, Florita, Draxl, Lu, Hamann, Hodge (b0220) 2016; 129 Antonanzas, Osorio, Escobar, Urraca, de Pison, Antonanzas-Torres (b0010) 2016; 136 Reno, Hansen (b0305) 2016; 90 Perez, Ineichen, Seals, Michalsky, Stewart (b0275) 1990; 44 The M3- Competition. Voyant, Notton (b0355) 2018; 92 Murphy (b0240) 1992; 7 Yang (b0375) 2016; 136 Murphy, Winkler (b0260) 1971; 52 Urraca, Gracia-Amillo, Huld, de Pison, Trentmann, Lindfors, Riihelä, Sanz-Garcia (b0340) 2017; 158 Madsen, Pinson, Kariniotakis, Nielsen, Nielsen (b0195) 2005; 29 Yang (b0380) 2018; 97 . Sengupta, M., Habte, A., Kurtz, S., Dobos, A., Wilbert, S., Lorenz, E., Stoffel, T., Renné, D., Gueymard, C.A., Myers, D., et al., 2015. Best practices handbook for the collection and use of solar resource data for solar energy applications. Technical Report NREL/TP-5D00-63112. National Renewable Energy Laboratory. Special issue: Progress in Solar Energy. Lorenz, Kühnert, Heinemann, Nielsen, Remund, Müller (b0190) 2016; 24 Blaga, Sabadus, Stefu, Dughir, Paulescu, Badescu (b0040) 2019; 70 Gschwind, Wald, Blanc, Lefèvre, Schroedter-Homscheidt, Arola (b0085) 2019; 28 Klingler, Teichtmann (b0150) 2017; 158 Zhang, Florita, Hodge, Lu, Hamann, Banunarayanan, Brockway (b0425) 2015; 111 Murphy (b0235) 1988; 116 Perez, Schlemmer, Kankiewicz, Dise, Tadese, Hoff (b0285) 2017 Antonanzas, Pozo-Vázquez, Fernandez-Jimenez, de Pison (b0015) 2017; 158 Gilleland, Ahijevych, Brown, Ebert (b0070) 2010; 91 Long, Shi (b0185) 2008; 2 Murphy (b0245) 1993; 8 Gueymard, C.A., Ruiz-Arias, J.A., 2016. Extensive worldwide validation and climate sensitivity analysis of direct irradiance predictions from 1-min global irradiance. Sol. Energy 128, 1–30. URL Jolliffe (b0135) 2008; 15 Marquez, Coimbra (b0215) 2013; 135 Yang, Boland (b0400) 2019; 11 Polo, Martín-Pomares, Gueymard, Balenzategui, Fabero, Silva (b0295) 2019 Wasserman (b0365) 2013 Murphy, Winkler (b0265) 1987; 115 Perez, Lorenz, Pelland, Beauharnois, Knowe, Hemker, Heinemann, Remund, Müller, Traunmüller, Steinmauer, Pozo, Ruiz-Arias, Lara-Fanego, Ramirez-Santigosa, Gaston-Romero, Pomares (b0280) 2013; 94 Yang, Sharma, Ye, Lim, Zhao, Aryaputera (b0420) 2015; 81 Yang (b0390) 2019; 193 Yang, Quan, Disfani, Liu (b0415) 2017; 146 Jolliffe, Stephenson (b0140) 2012 Vallance, Charbonnier, Paul, Dubost, Blanc (b0350) 2017; 150 Huang, Thatcher (b0110) 2017; 144 Law, Kay, Taylor (b0160) 2016; 125 Lohmann (b0180) 2018; 9 Fildes, Nikolopoulos, Crone, Syntetos (b0060) 2008; 59 Järvelä, Lappalainen, Valkealahti (b0130) 2020; 196 García, García, Cuevas, Cachorro, Romero-Campos, Ramos, de Frutos (b0065) 2014; 119 Marcos, Marroyo, Lorenzo, Garcáa (b0205) 2012; 20 Makridakis, Wheelwright, Hyndman (b0200) 2008 Yang (b0385) 2019; 11 Hyndman, Koehler (b0115) 2006; 22 Coimbra, Kleissl, Marquez (b0050) 2013 Progress in Solar Energy 3. Gueymard, C.A., 2012. Clear-sky irradiance predictions for solar resource mapping and large-scale applications: Improved validation methodology and detailed performance analysis of 18 broadband radiative models. Sol. Energy 86, 2145–2169. URL Beyer, H.G., Polo Martinez, J., Suri, M., Torres, J.L., Lorenz, E., Müller, S.C., Hoyer-Klick, C., Ineichen, P., 2009. Benchmarking of Radiation Products. Technical Report 038665. Mesor Report D.1.1.3. Almeida, Muñoz, de la Parra, Perpiñán (b0005) 2017; 155 Li, Chen, Zhao, Zhao, Wang (b0170) 2017; 111 Pedro, Coimbra (b0270) 2015; 122 Moskaitis (b0230) 2008; 23 Lindsay, Libois, Badosa, Migan-Dubois, Bourdin (b0175) 2020; 197 Tashman, L.J., 2000. Out-of-sample tests of forecasting accuracy: an analysis and review. Int. J. Forecast. 16, 437–450. URL Voyant, Notton, Kalogirou, Nivet, Paoli, Motte, Fouilloy (b0360) 2017; 105 Ruiz-Arias, Gueymard (b0310) 2018; 171 Killinger, Engerer, Müller (b0145) 2017; 143 Marquez, R., Coimbra, C.F.M., 2011. A novel metric for evaluation of solar forecasting models. In: ASME 2011 5th International Conference on Energy Sustainability. ASME, pp. 1459–1467. Ruiz-Arias, J.A., Gueymard, C.A., 2018b. Worldwide inter-comparison of clear-sky solar radiation models: Consensus-based review of direct and global irradiance components simulated at the earth surface. Sol. Energy 168, 10–29. Advances in Solar Resource Assessment and Forecasting. URL Inman, Pedro, Coimbra (b0125) 2013; 39 Lefèvre, Oumbe, Blanc, Espinar, Gschwind, Qu, Wald, Schroedter-Homscheidt, Hoyer-Klick, Arola, Benedetti, Kaiser, Morcrette (b0165) 2013; 6 Ren, Suganthan, Srikanth (b0300) 2015; 50 Chai, Draxler (b0045) 2014; 7 Pedro (10.1016/j.solener.2020.04.019_b0270) 2015; 122 Ren (10.1016/j.solener.2020.04.019_b0300) 2015; 50 García (10.1016/j.solener.2020.04.019_b0065) 2014; 119 Willmott (10.1016/j.solener.2020.04.019_b0370) 2005; 30 Yang (10.1016/j.solener.2020.04.019_b0380) 2018; 97 Yang (10.1016/j.solener.2020.04.019_b0395) 2019; 11 Marcos (10.1016/j.solener.2020.04.019_b0205) 2012; 20 Gilleland (10.1016/j.solener.2020.04.019_b0070) 2010; 91 10.1016/j.solener.2020.04.019_b0155 10.1016/j.solener.2020.04.019_b0030 Yang (10.1016/j.solener.2020.04.019_b0400) 2019; 11 Murphy (10.1016/j.solener.2020.04.019_b0260) 1971; 52 Zhang (10.1016/j.solener.2020.04.019_b0425) 2015; 111 Yang (10.1016/j.solener.2020.04.019_b0415) 2017; 146 Murphy (10.1016/j.solener.2020.04.019_b0245) 1993; 8 Klingler (10.1016/j.solener.2020.04.019_b0150) 2017; 158 Lefèvre (10.1016/j.solener.2020.04.019_b0165) 2013; 6 Madsen (10.1016/j.solener.2020.04.019_b0195) 2005; 29 Polo (10.1016/j.solener.2020.04.019_b0295) 2019 Yang (10.1016/j.solener.2020.04.019_b0420) 2015; 81 Perez (10.1016/j.solener.2020.04.019_b0275) 1990; 44 Voyant (10.1016/j.solener.2020.04.019_b0355) 2018; 92 Martinez-Anido (10.1016/j.solener.2020.04.019_b0220) 2016; 129 Perpiñán (10.1016/j.solener.2020.04.019_b0290) 2013; 88 Inman (10.1016/j.solener.2020.04.019_b0120) 2015; 117 Murphy (10.1016/j.solener.2020.04.019_b0235) 1988; 116 Sun (10.1016/j.solener.2020.04.019_b0330) 2019; 111 Ruiz-Arias (10.1016/j.solener.2020.04.019_b0310) 2018; 171 Murphy (10.1016/j.solener.2020.04.019_b0250) 1997 Perez (10.1016/j.solener.2020.04.019_b0285) 2017 Voyant (10.1016/j.solener.2020.04.019_b0360) 2017; 105 Inman (10.1016/j.solener.2020.04.019_b0125) 2013; 39 Urraca (10.1016/j.solener.2020.04.019_b0345) 2018; 176 Antonanzas-Torres (10.1016/j.solener.2020.04.019_b0020) 2019; 107 Coimbra (10.1016/j.solener.2020.04.019_b0050) 2013 Gschwind (10.1016/j.solener.2020.04.019_b0085) 2019; 28 10.1016/j.solener.2020.04.019_b0335 Killinger (10.1016/j.solener.2020.04.019_b0145) 2017; 143 Lindsay (10.1016/j.solener.2020.04.019_b0175) 2020; 197 Vallance (10.1016/j.solener.2020.04.019_b0350) 2017; 150 Antonanzas (10.1016/j.solener.2020.04.019_b0010) 2016; 136 Reno (10.1016/j.solener.2020.04.019_b0305) 2016; 90 Dong (10.1016/j.solener.2020.04.019_b0055) 2013; 55 Murphy (10.1016/j.solener.2020.04.019_b0240) 1992; 7 10.1016/j.solener.2020.04.019_b0095 Järvelä (10.1016/j.solener.2020.04.019_b0130) 2020; 196 10.1016/j.solener.2020.04.019_b0090 Yang (10.1016/j.solener.2020.04.019_b0375) 2016; 136 Urraca (10.1016/j.solener.2020.04.019_b0340) 2017; 158 Fildes (10.1016/j.solener.2020.04.019_b0060) 2008; 59 10.1016/j.solener.2020.04.019_b0210 Almeida (10.1016/j.solener.2020.04.019_b0005) 2017; 155 Yang (10.1016/j.solener.2020.04.019_b0390) 2019; 193 Yang (10.1016/j.solener.2020.04.019_b0410) 2019; 11 Long (10.1016/j.solener.2020.04.019_b0185) 2008; 2 Moskaitis (10.1016/j.solener.2020.04.019_b0230) 2008; 23 Jolliffe (10.1016/j.solener.2020.04.019_b0140) 2012 10.1016/j.solener.2020.04.019_b0405 Li (10.1016/j.solener.2020.04.019_b0170) 2017; 111 Makridakis (10.1016/j.solener.2020.04.019_b0200) 2008 Hyndman (10.1016/j.solener.2020.04.019_b0115) 2006; 22 10.1016/j.solener.2020.04.019_b0325 Antonanzas (10.1016/j.solener.2020.04.019_b0015) 2017; 158 Lohmann (10.1016/j.solener.2020.04.019_b0180) 2018; 9 Lorenz (10.1016/j.solener.2020.04.019_b0190) 2016; 24 Yang (10.1016/j.solener.2020.04.019_b0385) 2019; 11 Yang (10.1016/j.solener.2020.04.019_bib426) 2020; 12 Chai (10.1016/j.solener.2020.04.019_b0045) 2014; 7 Wasserman (10.1016/j.solener.2020.04.019_b0365) 2013 Schilling (10.1016/j.solener.2020.04.019_b0320) 2017 Hong (10.1016/j.solener.2020.04.019_b0105) 2016; 32 Jolliffe (10.1016/j.solener.2020.04.019_b0135) 2008; 15 Marquez (10.1016/j.solener.2020.04.019_b0215) 2013; 135 Huang (10.1016/j.solener.2020.04.019_b0110) 2017; 144 Law (10.1016/j.solener.2020.04.019_b0160) 2016; 125 Armstrong (10.1016/j.solener.2020.04.019_b0025) 2001 Blaga (10.1016/j.solener.2020.04.019_b0040) 2019; 70 Gneiting (10.1016/j.solener.2020.04.019_b0080) 2007; 102 10.1016/j.solener.2020.04.019_b0315 Hoff (10.1016/j.solener.2020.04.019_b0100) 2013; 21 Perez (10.1016/j.solener.2020.04.019_b0280) 2013; 94 Gneiting (10.1016/j.solener.2020.04.019_b0075) 2011; 106 van der Meer (10.1016/j.solener.2020.04.019_b0225) 2018; 81 Blaga (10.1016/j.solener.2020.04.019_b0035) 2019; 191 Murphy (10.1016/j.solener.2020.04.019_b0255) 1989; 4 Murphy (10.1016/j.solener.2020.04.019_b0265) 1987; 115 |
| References_xml | – volume: 29 start-page: 475 year: 2005 end-page: 489 ident: b0195 article-title: Standardizing the performance evaluation of short-term wind power prediction models publication-title: Wind Eng. – volume: 4 start-page: 485 year: 1989 end-page: 501 ident: b0255 article-title: Diagnostic verification of temperature forecasts publication-title: Weather Forecast. – volume: 171 start-page: 447 year: 2018 end-page: 465 ident: b0310 article-title: A multi-model benchmarking of direct and global clear-sky solar irradiance predictions at arid sites using a reference physical radiative transfer model publication-title: Sol. Energy – start-page: 443 year: 2001 end-page: 472 ident: b0025 article-title: Evaluating forecasting methods publication-title: Principles of Forecasting – volume: 146 start-page: 276 year: 2017 end-page: 286 ident: b0415 article-title: Reconciling solar forecasts: Geographical hierarchy publication-title: Sol. Energy – year: 2017 ident: b0320 article-title: Measures, Integrals and Martingales – volume: 176 start-page: 663 year: 2018 end-page: 677 ident: b0345 article-title: Quantifying the amplified bias of PV system simulations due to uncertainties in solar radiation estimates publication-title: Sol. Energy – start-page: 1104 year: 2017 end-page: 1109 ident: b0285 article-title: Detecting calibration drift at ground truth stations a demonstration of satellite irradiance models’ accuracy publication-title: 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC) – volume: 102 start-page: 359 year: 2007 end-page: 378 ident: b0080 article-title: Strictly proper scoring rules, prediction, and estimation publication-title: J. Am. Statist. Assoc. – volume: 191 start-page: 371 year: 2019 end-page: 381 ident: b0035 article-title: The impact of temporal smoothing on the accuracy of separation models publication-title: Sol. Energy – volume: 70 start-page: 119 year: 2019 end-page: 144 ident: b0040 article-title: A current perspective on the accuracy of incoming solar energy forecasting publication-title: Prog. Energy Combust. Sci. – volume: 122 start-page: 587 year: 2015 end-page: 602 ident: b0270 article-title: Short-term irradiance forecastability for various solar micro-climates publication-title: Sol. Energy – volume: 136 start-page: 78 year: 2016 end-page: 111 ident: b0010 article-title: Review of photovoltaic power forecasting publication-title: Sol. Energy – volume: 9 year: 2018 ident: b0180 article-title: Irradiance variability quantification and small-scale averaging in space and time: A short review publication-title: Atmosphere – year: 2008 ident: b0200 article-title: Forecasting Methods and Applications – reference: Beyer, H.G., Polo Martinez, J., Suri, M., Torres, J.L., Lorenz, E., Müller, S.C., Hoyer-Klick, C., Ineichen, P., 2009. Benchmarking of Radiation Products. Technical Report 038665. Mesor Report D.1.1.3. – reference: . Progress in Solar Energy 3. – volume: 24 start-page: 1626 year: 2016 end-page: 1640 ident: b0190 article-title: Comparison of global horizontal irradiance forecasts based on numerical weather prediction models with different spatio-temporal resolutions publication-title: Prog. Photovoltaics Res. Appl. – volume: 111 start-page: 157 year: 2015 end-page: 175 ident: b0425 article-title: A suite of metrics for assessing the performance of solar power forecasting publication-title: Sol. Energy – volume: 158 start-page: 861 year: 2017 end-page: 868 ident: b0150 article-title: Impacts of a forecast-based operation strategy for grid-connected PV storage systems on profitability and the energy system publication-title: Sol. Energy – volume: 125 start-page: 267 year: 2016 end-page: 281 ident: b0160 article-title: Calculating the financial value of a concentrated solar thermal plant operated using direct normal irradiance forecasts publication-title: Sol. Energy – volume: 23 start-page: 1195 year: 2008 end-page: 1220 ident: b0230 article-title: A case study of deterministic forecast verification: Tropical cyclone intensity publication-title: Weather Forecast. – reference: Tashman, L.J., 2000. Out-of-sample tests of forecasting accuracy: an analysis and review. Int. J. Forecast. 16, 437–450. URL: – volume: 21 start-page: 1514 year: 2013 end-page: 1519 ident: b0100 article-title: Reporting of irradiance modeling relative prediction errors publication-title: Prog. Photovoltaics Res. Appl. – volume: 12 start-page: 26101 year: 2020 ident: bib426 article-title: Choice of clear-sky model in solar forecasting publication-title: J. Renewable Sustainable Energy – volume: 32 start-page: 896 year: 2016 end-page: 913 ident: b0105 article-title: Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond publication-title: Int. J. Forecast. – reference: Marquez, R., Coimbra, C.F.M., 2011. A novel metric for evaluation of solar forecasting models. In: ASME 2011 5th International Conference on Energy Sustainability. ASME, pp. 1459–1467. – volume: 94 start-page: 305 year: 2013 end-page: 326 ident: b0280 article-title: Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe publication-title: Sol. Energy – volume: 7 start-page: 692 year: 1992 end-page: 698 ident: b0240 article-title: Climatology, persistence, and their linear combination as standards of reference in skill scores publication-title: Weather Forecast. – volume: 136 start-page: 288 year: 2016 end-page: 302 ident: b0375 article-title: Solar radiation on inclined surfaces: Corrections and benchmarks publication-title: Sol. Energy – volume: 20 start-page: 226 year: 2012 end-page: 237 ident: b0205 article-title: Smoothing of PV power fluctuations by geographical dispersion publication-title: Prog. Photovoltaics Res. Appl. – start-page: 171 year: 2013 end-page: 194 ident: b0050 article-title: Chapter 8 - Overview of solar-forecasting methods and a metric for accuracy evaluation publication-title: Solar Energy Forecasting and Resource Assessment – volume: 52 start-page: 239 year: 1971 end-page: 248 ident: b0260 article-title: forecasters and probability forecasts: some current problems publication-title: Bull. Am. Meteorol. Soc. – volume: 97 start-page: 152 year: 2018 end-page: 155 ident: b0380 article-title: A correct validation of the National Solar Radiation Data Base (NSRDB) publication-title: Renew. Sustain. Energy Rev. – reference: . – volume: 8 start-page: 281 year: 1993 end-page: 293 ident: b0245 article-title: What is a good forecast? An essay on the nature of goodness in weather forecasting publication-title: Weather Forecast. – volume: 111 start-page: 550 year: 2019 end-page: 570 ident: b0330 article-title: Worldwide performance assessment of 75 global clear-sky irradiance models using principal component analysis publication-title: Renew. Sustain. Energy Rev. – volume: 135 start-page: 011016 year: 2013 ident: b0215 article-title: Proposed metric for evaluation of solar forecasting models publication-title: J. Solar Energy Eng. – volume: 119 start-page: 179 year: 2014 end-page: 194 ident: b0065 article-title: Solar radiation measurements compared to simulations at the BSRN Izaña station. mineral dust radiative forcing and efficiency study publication-title: J. Geophys. Res.: Atmosph. – year: 2012 ident: b0140 article-title: Forecast Verification: A Practitioner’s Guide in Atmospheric Science – year: 2013 ident: b0365 article-title: All of Statistics: A Concise Course in Statistical Inference – volume: 106 start-page: 746 year: 2011 end-page: 762 ident: b0075 article-title: Making and evaluating point forecasts publication-title: J. Am. Stat. Assoc. – volume: 90 start-page: 520 year: 2016 end-page: 531 ident: b0305 article-title: Global horizontal irradiance clear sky models: Implementation and analysis publication-title: Renewable Energy – volume: 6 start-page: 2403 year: 2013 end-page: 2418 ident: b0165 article-title: McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions publication-title: Atmospheric Measur. Tech. – volume: 92 start-page: 343 year: 2018 end-page: 352 ident: b0355 article-title: Solar irradiation nowcasting by stochastic persistence: A new parsimonious, simple and efficient forecasting tool publication-title: Renew. Sustain. Energy Rev. – reference: Gueymard, C.A., 2012. Clear-sky irradiance predictions for solar resource mapping and large-scale applications: Improved validation methodology and detailed performance analysis of 18 broadband radiative models. Sol. Energy 86, 2145–2169. URL: – reference: Sengupta, M., Habte, A., Kurtz, S., Dobos, A., Wilbert, S., Lorenz, E., Stoffel, T., Renné, D., Gueymard, C.A., Myers, D., et al., 2015. Best practices handbook for the collection and use of solar resource data for solar energy applications. Technical Report NREL/TP-5D00-63112. National Renewable Energy Laboratory. – volume: 155 start-page: 854 year: 2017 end-page: 866 ident: b0005 article-title: Comparative study of PV power forecast using parametric and nonparametric PV models publication-title: Sol. Energy – reference: Lave, M., Kleissl, J., Arias-Castro, E., 2012. High-frequency irradiance fluctuations and geographic smoothing. Sol. Energy 86, 2190–2199. URL: – volume: 11 start-page: 53702 year: 2019 ident: b0395 article-title: Standard of reference in operational day-ahead deterministic solar forecasting publication-title: J. Renewable Sustainable Energy – volume: 11 start-page: 023704 year: 2019 ident: b0410 article-title: Can we gauge forecasts using satellite-derived solar irradiance? publication-title: J. Renewable Sustainable Energy – reference: Yang, D., Kleissl, J., Gueymard, C.A., Pedro, H.T.C., Coimbra, C.F.M., 2018. History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining. Sol. Energy 168, 60–101. Advances in Solar Resource Assessment and Forecasting. URL: – volume: 81 start-page: 111 year: 2015 end-page: 119 ident: b0420 article-title: Forecasting of global horizontal irradiance by exponential smoothing, using decompositions publication-title: Energy – volume: 111 start-page: 732 year: 2017 end-page: 739 ident: b0170 article-title: Development of a PV performance model for power output simulation at minutely resolution publication-title: Renewable Energy – volume: 107 start-page: 374 year: 2019 end-page: 387 ident: b0020 article-title: Clear sky solar irradiance models: A review of seventy models publication-title: Renew. Sustain. Energy Rev. – volume: 22 start-page: 679 year: 2006 end-page: 688 ident: b0115 article-title: Another look at measures of forecast accuracy publication-title: Int. J. Forecast. – volume: 117 start-page: 125 year: 2015 end-page: 138 ident: b0120 article-title: Impact of local broadband turbidity estimation on forecasting of clear sky direct normal irradiance publication-title: Sol. Energy – volume: 7 start-page: 1247 year: 2014 end-page: 1250 ident: b0045 article-title: Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature publication-title: Geoscientific Model Devel. – volume: 59 start-page: 1150 year: 2008 end-page: 1172 ident: b0060 article-title: Forecasting and operational research: a review publication-title: J. Oper. Res. Soc. – volume: 129 start-page: 192 year: 2016 end-page: 203 ident: b0220 article-title: The value of day-ahead solar power forecasting improvement publication-title: Sol. Energy – volume: 150 start-page: 408 year: 2017 end-page: 422 ident: b0350 article-title: Towards a standardized procedure to assess solar forecast accuracy: A new ramp and time alignment metric publication-title: Sol. Energy – volume: 105 start-page: 569 year: 2017 end-page: 582 ident: b0360 article-title: Machine learning methods for solar radiation forecasting: A review publication-title: Renewable Energy – volume: 158 start-page: 49 year: 2017 end-page: 62 ident: b0340 article-title: Quality control of global solar radiation data with satellite-based products publication-title: Sol. Energy – volume: 44 start-page: 271 year: 1990 end-page: 289 ident: b0275 article-title: Modeling daylight availability and irradiance components from direct and global irradiance publication-title: Sol. Energy – volume: 50 start-page: 82 year: 2015 end-page: 91 ident: b0300 article-title: Ensemble methods for wind and solar power forecasting—A state-of-the-art review publication-title: Renew. Sustain. Energy Rev. – volume: 88 start-page: 227 year: 2013 end-page: 241 ident: b0290 article-title: Electrical power fluctuations in a network of DC/AC inverters in a large PV plant: Relationship between correlation, distance and time scale publication-title: Sol. Energy – volume: 28 start-page: 147 year: 2019 end-page: 163 ident: b0085 article-title: Improving the McClear model estimating the downwelling solar radiation at ground level in cloud-free conditions – McClear-v3 publication-title: Meteorol. Z. – volume: 116 start-page: 2417 year: 1988 end-page: 2424 ident: b0235 article-title: Skill scores based on the mean square error and their relationships to the correlation coefficient publication-title: Mon. Weather Rev. – volume: 115 start-page: 1330 year: 1987 end-page: 1338 ident: b0265 article-title: A general framework for forecast verification publication-title: Mon. Weather Rev. – reference: Gueymard, C.A., Ruiz-Arias, J.A., 2016. Extensive worldwide validation and climate sensitivity analysis of direct irradiance predictions from 1-min global irradiance. Sol. Energy 128, 1–30. URL: – volume: 81 start-page: 1484 year: 2018 end-page: 1512 ident: b0225 article-title: Review on probabilistic forecasting of photovoltaic power production and electricity consumption publication-title: Renew. Sustain. Energy Rev. – volume: 91 start-page: 1365 year: 2010 end-page: 1376 ident: b0070 article-title: Verifying forecasts spatially publication-title: Bull. Am. Meteorol. Soc. – reference: . Special issue: Progress in Solar Energy. – volume: 158 start-page: 140 year: 2017 end-page: 146 ident: b0015 article-title: The value of day-ahead forecasting for photovoltaics in the Spanish electricity market publication-title: Sol. Energy – volume: 193 start-page: 981 year: 2019 end-page: 985 ident: b0390 article-title: Making reference solar forecasts with climatology, persistence, and their optimal convex combination publication-title: Sol. Energy – volume: 197 start-page: 266 year: 2020 end-page: 278 ident: b0175 article-title: Errors in PV power modelling due to the lack of spectral and angular details of solar irradiance inputs publication-title: Sol. Energy – volume: 2 start-page: 23 year: 2008 end-page: 37 ident: b0185 article-title: An automated quality assessment and control algorithm for surface radiation measurements publication-title: Open Atmospheric Sci. J. – volume: 11 start-page: 22701 year: 2019 ident: b0385 article-title: A guideline to solar forecasting research practice: Reproducible, operational, probabilistic or physically-based, ensemble, and skill (ROPES) publication-title: J. Renewable Sustainable Energy – start-page: 1 year: 2019 end-page: 14 ident: b0295 article-title: Fundamentals: Quantities, definitions, and units publication-title: Solar Resources Mapping: Fundamentals and Applications – reference: . – volume: 196 start-page: 137 year: 2020 end-page: 145 ident: b0130 article-title: Characteristics of the cloud enhancement phenomenon and PV power plants publication-title: Sol. Energy – volume: 15 start-page: 25 year: 2008 end-page: 29 ident: b0135 article-title: The impenetrable hedge: a note on propriety, equitability and consistency publication-title: Meteorolog. Appl. – volume: 30 start-page: 79 year: 2005 end-page: 82 ident: b0370 article-title: Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance publication-title: Climate Res. – volume: 39 start-page: 535 year: 2013 end-page: 576 ident: b0125 article-title: Solar forecasting methods for renewable energy integration publication-title: Prog. Energy Combust. Sci. – volume: 143 start-page: 120 year: 2017 end-page: 131 ident: b0145 article-title: QCPV: A quality control algorithm for distributed photovoltaic array power output publication-title: Sol. Energy – reference: Ruiz-Arias, J.A., Gueymard, C.A., 2018b. Worldwide inter-comparison of clear-sky solar radiation models: Consensus-based review of direct and global irradiance components simulated at the earth surface. Sol. Energy 168, 10–29. Advances in Solar Resource Assessment and Forecasting. URL: – start-page: 19 year: 1997 end-page: 74 ident: b0250 article-title: Forecast verification publication-title: Economic Value of Weather and Climate Forecasts – reference: . The M3- Competition. – volume: 144 start-page: 529 year: 2017 end-page: 539 ident: b0110 article-title: Assessing the value of simulated regional weather variability in solar forecasting using numerical weather prediction publication-title: Sol. Energy – volume: 11 start-page: 023705 year: 2019 ident: b0400 article-title: Satellite-augmented diffuse solar radiation separation models publication-title: J. Renewable Sustainable Energy – volume: 55 start-page: 1104 year: 2013 end-page: 1113 ident: b0055 article-title: Short-term solar irradiance forecasting using exponential smoothing state space model publication-title: Energy – volume: 197 start-page: 266 year: 2020 ident: 10.1016/j.solener.2020.04.019_b0175 article-title: Errors in PV power modelling due to the lack of spectral and angular details of solar irradiance inputs publication-title: Sol. Energy doi: 10.1016/j.solener.2019.12.042 – volume: 111 start-page: 550 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0330 article-title: Worldwide performance assessment of 75 global clear-sky irradiance models using principal component analysis publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2019.04.006 – volume: 136 start-page: 78 year: 2016 ident: 10.1016/j.solener.2020.04.019_b0010 article-title: Review of photovoltaic power forecasting publication-title: Sol. Energy doi: 10.1016/j.solener.2016.06.069 – volume: 12 start-page: 26101 issue: 2 year: 2020 ident: 10.1016/j.solener.2020.04.019_bib426 article-title: Choice of clear-sky model in solar forecasting publication-title: J. Renewable Sustainable Energy doi: 10.1063/5.0003495 – volume: 7 start-page: 1247 year: 2014 ident: 10.1016/j.solener.2020.04.019_b0045 article-title: Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature publication-title: Geoscientific Model Devel. doi: 10.5194/gmd-7-1247-2014 – ident: 10.1016/j.solener.2020.04.019_b0030 – ident: 10.1016/j.solener.2020.04.019_b0315 doi: 10.1016/j.solener.2018.02.008 – volume: 2 start-page: 23 year: 2008 ident: 10.1016/j.solener.2020.04.019_b0185 article-title: An automated quality assessment and control algorithm for surface radiation measurements publication-title: Open Atmospheric Sci. J. doi: 10.2174/1874282300802010023 – start-page: 1 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0295 article-title: Fundamentals: Quantities, definitions, and units – volume: 146 start-page: 276 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0415 article-title: Reconciling solar forecasts: Geographical hierarchy publication-title: Sol. Energy doi: 10.1016/j.solener.2017.02.010 – ident: 10.1016/j.solener.2020.04.019_b0095 doi: 10.1016/j.solener.2015.10.010 – volume: 81 start-page: 111 year: 2015 ident: 10.1016/j.solener.2020.04.019_b0420 article-title: Forecasting of global horizontal irradiance by exponential smoothing, using decompositions publication-title: Energy doi: 10.1016/j.energy.2014.11.082 – volume: 102 start-page: 359 year: 2007 ident: 10.1016/j.solener.2020.04.019_b0080 article-title: Strictly proper scoring rules, prediction, and estimation publication-title: J. Am. Statist. Assoc. doi: 10.1198/016214506000001437 – volume: 111 start-page: 157 year: 2015 ident: 10.1016/j.solener.2020.04.019_b0425 article-title: A suite of metrics for assessing the performance of solar power forecasting publication-title: Sol. Energy doi: 10.1016/j.solener.2014.10.016 – volume: 70 start-page: 119 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0040 article-title: A current perspective on the accuracy of incoming solar energy forecasting publication-title: Prog. Energy Combust. Sci. doi: 10.1016/j.pecs.2018.10.003 – volume: 59 start-page: 1150 year: 2008 ident: 10.1016/j.solener.2020.04.019_b0060 article-title: Forecasting and operational research: a review publication-title: J. Oper. Res. Soc. doi: 10.1057/palgrave.jors.2602597 – ident: 10.1016/j.solener.2020.04.019_b0325 doi: 10.18777/ieashc-task46-2015-0001 – volume: 94 start-page: 305 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0280 article-title: Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe publication-title: Sol. Energy doi: 10.1016/j.solener.2013.05.005 – volume: 97 start-page: 152 year: 2018 ident: 10.1016/j.solener.2020.04.019_b0380 article-title: A correct validation of the National Solar Radiation Data Base (NSRDB) publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2018.08.023 – volume: 24 start-page: 1626 year: 2016 ident: 10.1016/j.solener.2020.04.019_b0190 article-title: Comparison of global horizontal irradiance forecasts based on numerical weather prediction models with different spatio-temporal resolutions publication-title: Prog. Photovoltaics Res. Appl. doi: 10.1002/pip.2799 – volume: 129 start-page: 192 year: 2016 ident: 10.1016/j.solener.2020.04.019_b0220 article-title: The value of day-ahead solar power forecasting improvement publication-title: Sol. Energy doi: 10.1016/j.solener.2016.01.049 – start-page: 171 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0050 article-title: Chapter 8 - Overview of solar-forecasting methods and a metric for accuracy evaluation – volume: 150 start-page: 408 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0350 article-title: Towards a standardized procedure to assess solar forecast accuracy: A new ramp and time alignment metric publication-title: Sol. Energy doi: 10.1016/j.solener.2017.04.064 – volume: 122 start-page: 587 year: 2015 ident: 10.1016/j.solener.2020.04.019_b0270 article-title: Short-term irradiance forecastability for various solar micro-climates publication-title: Sol. Energy doi: 10.1016/j.solener.2015.09.031 – volume: 107 start-page: 374 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0020 article-title: Clear sky solar irradiance models: A review of seventy models publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2019.02.032 – volume: 191 start-page: 371 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0035 article-title: The impact of temporal smoothing on the accuracy of separation models publication-title: Sol. Energy doi: 10.1016/j.solener.2019.08.078 – volume: 15 start-page: 25 year: 2008 ident: 10.1016/j.solener.2020.04.019_b0135 article-title: The impenetrable hedge: a note on propriety, equitability and consistency publication-title: Meteorolog. Appl. doi: 10.1002/met.60 – volume: 158 start-page: 140 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0015 article-title: The value of day-ahead forecasting for photovoltaics in the Spanish electricity market publication-title: Sol. Energy doi: 10.1016/j.solener.2017.09.043 – volume: 158 start-page: 49 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0340 article-title: Quality control of global solar radiation data with satellite-based products publication-title: Sol. Energy doi: 10.1016/j.solener.2017.09.032 – start-page: 1104 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0285 article-title: Detecting calibration drift at ground truth stations a demonstration of satellite irradiance models’ accuracy – volume: 30 start-page: 79 year: 2005 ident: 10.1016/j.solener.2020.04.019_b0370 article-title: Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance publication-title: Climate Res. doi: 10.3354/cr030079 – volume: 11 start-page: 53702 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0395 article-title: Standard of reference in operational day-ahead deterministic solar forecasting publication-title: J. Renewable Sustainable Energy doi: 10.1063/1.5114985 – volume: 11 start-page: 023704 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0410 article-title: Can we gauge forecasts using satellite-derived solar irradiance? publication-title: J. Renewable Sustainable Energy doi: 10.1063/1.5087588 – volume: 119 start-page: 179 year: 2014 ident: 10.1016/j.solener.2020.04.019_b0065 article-title: Solar radiation measurements compared to simulations at the BSRN Izaña station. mineral dust radiative forcing and efficiency study publication-title: J. Geophys. Res.: Atmosph. doi: 10.1002/2013JD020301 – year: 2012 ident: 10.1016/j.solener.2020.04.019_b0140 – volume: 176 start-page: 663 year: 2018 ident: 10.1016/j.solener.2020.04.019_b0345 article-title: Quantifying the amplified bias of PV system simulations due to uncertainties in solar radiation estimates publication-title: Sol. Energy doi: 10.1016/j.solener.2018.10.065 – volume: 196 start-page: 137 year: 2020 ident: 10.1016/j.solener.2020.04.019_b0130 article-title: Characteristics of the cloud enhancement phenomenon and PV power plants publication-title: Sol. Energy doi: 10.1016/j.solener.2019.11.090 – start-page: 443 year: 2001 ident: 10.1016/j.solener.2020.04.019_b0025 article-title: Evaluating forecasting methods – volume: 90 start-page: 520 year: 2016 ident: 10.1016/j.solener.2020.04.019_b0305 article-title: Global horizontal irradiance clear sky models: Implementation and analysis publication-title: Renewable Energy doi: 10.1016/j.renene.2015.12.031 – volume: 55 start-page: 1104 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0055 article-title: Short-term solar irradiance forecasting using exponential smoothing state space model publication-title: Energy doi: 10.1016/j.energy.2013.04.027 – volume: 4 start-page: 485 year: 1989 ident: 10.1016/j.solener.2020.04.019_b0255 article-title: Diagnostic verification of temperature forecasts publication-title: Weather Forecast. doi: 10.1175/1520-0434(1989)004<0485:DVOTF>2.0.CO;2 – volume: 171 start-page: 447 year: 2018 ident: 10.1016/j.solener.2020.04.019_b0310 article-title: A multi-model benchmarking of direct and global clear-sky solar irradiance predictions at arid sites using a reference physical radiative transfer model publication-title: Sol. Energy doi: 10.1016/j.solener.2018.06.048 – volume: 117 start-page: 125 year: 2015 ident: 10.1016/j.solener.2020.04.019_b0120 article-title: Impact of local broadband turbidity estimation on forecasting of clear sky direct normal irradiance publication-title: Sol. Energy doi: 10.1016/j.solener.2015.04.032 – volume: 136 start-page: 288 year: 2016 ident: 10.1016/j.solener.2020.04.019_b0375 article-title: Solar radiation on inclined surfaces: Corrections and benchmarks publication-title: Sol. Energy doi: 10.1016/j.solener.2016.06.062 – volume: 50 start-page: 82 year: 2015 ident: 10.1016/j.solener.2020.04.019_b0300 article-title: Ensemble methods for wind and solar power forecasting—A state-of-the-art review publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2015.04.081 – volume: 8 start-page: 281 year: 1993 ident: 10.1016/j.solener.2020.04.019_b0245 article-title: What is a good forecast? An essay on the nature of goodness in weather forecasting publication-title: Weather Forecast. doi: 10.1175/1520-0434(1993)008<0281:WIAGFA>2.0.CO;2 – volume: 155 start-page: 854 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0005 article-title: Comparative study of PV power forecast using parametric and nonparametric PV models publication-title: Sol. Energy doi: 10.1016/j.solener.2017.07.032 – volume: 23 start-page: 1195 year: 2008 ident: 10.1016/j.solener.2020.04.019_b0230 article-title: A case study of deterministic forecast verification: Tropical cyclone intensity publication-title: Weather Forecast. doi: 10.1175/2008WAF2222133.1 – volume: 81 start-page: 1484 year: 2018 ident: 10.1016/j.solener.2020.04.019_b0225 article-title: Review on probabilistic forecasting of photovoltaic power production and electricity consumption publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2017.05.212 – ident: 10.1016/j.solener.2020.04.019_b0155 doi: 10.1016/j.solener.2011.06.031 – volume: 28 start-page: 147 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0085 article-title: Improving the McClear model estimating the downwelling solar radiation at ground level in cloud-free conditions – McClear-v3 publication-title: Meteorol. Z. doi: 10.1127/metz/2019/0946 – volume: 135 start-page: 011016 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0215 article-title: Proposed metric for evaluation of solar forecasting models publication-title: J. Solar Energy Eng. doi: 10.1115/1.4007496 – volume: 88 start-page: 227 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0290 article-title: Electrical power fluctuations in a network of DC/AC inverters in a large PV plant: Relationship between correlation, distance and time scale publication-title: Sol. Energy doi: 10.1016/j.solener.2012.12.004 – volume: 21 start-page: 1514 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0100 article-title: Reporting of irradiance modeling relative prediction errors publication-title: Prog. Photovoltaics Res. Appl. doi: 10.1002/pip.2225 – ident: 10.1016/j.solener.2020.04.019_b0335 doi: 10.1016/S0169-2070(00)00065-0 – volume: 29 start-page: 475 year: 2005 ident: 10.1016/j.solener.2020.04.019_b0195 article-title: Standardizing the performance evaluation of short-term wind power prediction models publication-title: Wind Eng. doi: 10.1260/030952405776234599 – volume: 144 start-page: 529 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0110 article-title: Assessing the value of simulated regional weather variability in solar forecasting using numerical weather prediction publication-title: Sol. Energy doi: 10.1016/j.solener.2017.01.058 – volume: 20 start-page: 226 year: 2012 ident: 10.1016/j.solener.2020.04.019_b0205 article-title: Smoothing of PV power fluctuations by geographical dispersion publication-title: Prog. Photovoltaics Res. Appl. doi: 10.1002/pip.1127 – volume: 11 start-page: 023705 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0400 article-title: Satellite-augmented diffuse solar radiation separation models publication-title: J. Renewable Sustainable Energy doi: 10.1063/1.5087463 – volume: 39 start-page: 535 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0125 article-title: Solar forecasting methods for renewable energy integration publication-title: Prog. Energy Combust. Sci. doi: 10.1016/j.pecs.2013.06.002 – volume: 44 start-page: 271 year: 1990 ident: 10.1016/j.solener.2020.04.019_b0275 article-title: Modeling daylight availability and irradiance components from direct and global irradiance publication-title: Sol. Energy doi: 10.1016/0038-092X(90)90055-H – volume: 125 start-page: 267 year: 2016 ident: 10.1016/j.solener.2020.04.019_b0160 article-title: Calculating the financial value of a concentrated solar thermal plant operated using direct normal irradiance forecasts publication-title: Sol. Energy doi: 10.1016/j.solener.2015.12.031 – volume: 106 start-page: 746 year: 2011 ident: 10.1016/j.solener.2020.04.019_b0075 article-title: Making and evaluating point forecasts publication-title: J. Am. Stat. Assoc. doi: 10.1198/jasa.2011.r10138 – volume: 105 start-page: 569 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0360 article-title: Machine learning methods for solar radiation forecasting: A review publication-title: Renewable Energy doi: 10.1016/j.renene.2016.12.095 – year: 2008 ident: 10.1016/j.solener.2020.04.019_b0200 – volume: 116 start-page: 2417 year: 1988 ident: 10.1016/j.solener.2020.04.019_b0235 article-title: Skill scores based on the mean square error and their relationships to the correlation coefficient publication-title: Mon. Weather Rev. doi: 10.1175/1520-0493(1988)116<2417:SSBOTM>2.0.CO;2 – volume: 91 start-page: 1365 year: 2010 ident: 10.1016/j.solener.2020.04.019_b0070 article-title: Verifying forecasts spatially publication-title: Bull. Am. Meteorol. Soc. doi: 10.1175/2010BAMS2819.1 – ident: 10.1016/j.solener.2020.04.019_b0405 doi: 10.1016/j.solener.2017.11.023 – volume: 32 start-page: 896 year: 2016 ident: 10.1016/j.solener.2020.04.019_b0105 article-title: Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond publication-title: Int. J. Forecast. doi: 10.1016/j.ijforecast.2016.02.001 – volume: 7 start-page: 692 year: 1992 ident: 10.1016/j.solener.2020.04.019_b0240 article-title: Climatology, persistence, and their linear combination as standards of reference in skill scores publication-title: Weather Forecast. doi: 10.1175/1520-0434(1992)007<0692:CPATLC>2.0.CO;2 – volume: 92 start-page: 343 year: 2018 ident: 10.1016/j.solener.2020.04.019_b0355 article-title: Solar irradiation nowcasting by stochastic persistence: A new parsimonious, simple and efficient forecasting tool publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2018.04.116 – volume: 11 start-page: 22701 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0385 article-title: A guideline to solar forecasting research practice: Reproducible, operational, probabilistic or physically-based, ensemble, and skill (ROPES) publication-title: J. Renewable Sustainable Energy doi: 10.1063/1.5087462 – volume: 143 start-page: 120 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0145 article-title: QCPV: A quality control algorithm for distributed photovoltaic array power output publication-title: Sol. Energy doi: 10.1016/j.solener.2016.12.053 – start-page: 19 year: 1997 ident: 10.1016/j.solener.2020.04.019_b0250 article-title: Forecast verification – year: 2017 ident: 10.1016/j.solener.2020.04.019_b0320 – ident: 10.1016/j.solener.2020.04.019_b0210 doi: 10.1115/ES2011-54519 – year: 2013 ident: 10.1016/j.solener.2020.04.019_b0365 – volume: 193 start-page: 981 year: 2019 ident: 10.1016/j.solener.2020.04.019_b0390 article-title: Making reference solar forecasts with climatology, persistence, and their optimal convex combination publication-title: Sol. Energy doi: 10.1016/j.solener.2019.10.006 – volume: 6 start-page: 2403 year: 2013 ident: 10.1016/j.solener.2020.04.019_b0165 article-title: McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions publication-title: Atmospheric Measur. Tech. doi: 10.5194/amt-6-2403-2013 – ident: 10.1016/j.solener.2020.04.019_b0090 doi: 10.1016/j.solener.2011.11.011 – volume: 52 start-page: 239 year: 1971 ident: 10.1016/j.solener.2020.04.019_b0260 article-title: forecasters and probability forecasts: some current problems publication-title: Bull. Am. Meteorol. Soc. doi: 10.1175/1520-0477(1971)052<0239:FAPFSC>2.0.CO;2 – volume: 22 start-page: 679 year: 2006 ident: 10.1016/j.solener.2020.04.019_b0115 article-title: Another look at measures of forecast accuracy publication-title: Int. J. Forecast. doi: 10.1016/j.ijforecast.2006.03.001 – volume: 158 start-page: 861 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0150 article-title: Impacts of a forecast-based operation strategy for grid-connected PV storage systems on profitability and the energy system publication-title: Sol. Energy doi: 10.1016/j.solener.2017.10.052 – volume: 111 start-page: 732 year: 2017 ident: 10.1016/j.solener.2020.04.019_b0170 article-title: Development of a PV performance model for power output simulation at minutely resolution publication-title: Renewable Energy doi: 10.1016/j.renene.2017.04.049 – volume: 9 year: 2018 ident: 10.1016/j.solener.2020.04.019_b0180 article-title: Irradiance variability quantification and small-scale averaging in space and time: A short review publication-title: Atmosphere doi: 10.3390/atmos9070264 – volume: 115 start-page: 1330 year: 1987 ident: 10.1016/j.solener.2020.04.019_b0265 article-title: A general framework for forecast verification publication-title: Mon. Weather Rev. doi: 10.1175/1520-0493(1987)115<1330:AGFFFV>2.0.CO;2 |
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| Snippet | •This review aims at standardizing the forecast verification approaches used in deterministic solar forecasting.•The distribution-oriented forecast... The field of energy forecasting has attracted many researchers from different fields (e.g., meteorology, data sciences, mechanical or electrical engineering)... |
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| SubjectTerms | Accuracy Climatology Combination of climatology and persistence Distribution-oriented forecast verification Engineering Science with specialization in Civil Engineering and Built Environment Engineering Sciences Environmental Sciences Forecasting Graphical methods Mathematical models Measure-oriented forecast verification Meteorology Reliability analysis Reliability aspects Root-mean-square errors Skill score Solar energy Solar forecasting Teknisk fysik med inriktning mot byggteknik och byggd miljö Verification |
| Title | Verification of deterministic solar forecasts |
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