IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v171y2019icp135-148.html
   My bibliography  Save this article

CMIP-5 models project photovoltaics are a no-regrets investment in Europe irrespective of climate change

Author

Listed:
  • Müller, Johannes
  • Folini, Doris
  • Wild, Martin
  • Pfenninger, Stefan

Abstract

Using projections of surface solar radiation and temperature from 23 CMIP5 global climate models for two climate change scenarios (RCP4.5 & 8.5) we quantify the average change in PV electricity production expected in the years 2060–2080 compared to the present (2007–2027). We upsample daily radiation data to hourly resolution with a sinusoidal diurnal cycle model and split it into direct and diffuse radiation with the semi-empirical BRL model as input to a PV electricity generation model. Locally, changes in PV potential from −6% to +3% in annual and −25% to +10% in monthly means are shown. These projections are combined with a PV deployment scenario and show countries benefitting from increased PV yields include Spain, France, Italy and Germany. We also calculate uncertainties when calculating PV yield with input data at daily or lower resolution, demonstrating that our method to derive synthetic hourly profiles should be of use for other researchers using input data with low temporal resolution. We conclude that PV is an attractive and no-regrets investment in Europe irrespective of future climate change, and can continue to play a key role in energy system decarbonisation.

Suggested Citation

  • Müller, Johannes & Folini, Doris & Wild, Martin & Pfenninger, Stefan, 2019. "CMIP-5 models project photovoltaics are a no-regrets investment in Europe irrespective of climate change," Energy, Elsevier, vol. 171(C), pages 135-148.
    • Handle: RePEc:eee:energy:v:171:y:2019:i:c:p:135-148
    DOI: 10.1016/j.energy.2018.12.139
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218325118
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.12.139?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Torres, J.L. & De Blas, M. & García, A. & de Francisco, A., 2010. "Comparative study of various models in estimating hourly diffuse solar irradiance," Renewable Energy, Elsevier, vol. 35(6), pages 1325-1332.
    2. Gaetani, Marco & Huld, Thomas & Vignati, Elisabetta & Monforti-Ferrario, Fabio & Dosio, Alessandro & Raes, Frank, 2014. "The near future availability of photovoltaic energy in Europe and Africa in climate-aerosol modeling experiments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 706-716.
    3. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    4. Yadav, Amit Kumar & Chandel, S.S., 2013. "Tilt angle optimization to maximize incident solar radiation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 503-513.
    5. Elminir, Hamdy K. & Azzam, Yosry A. & Younes, Farag I., 2007. "Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models," Energy, Elsevier, vol. 32(8), pages 1513-1523.
    6. Al- Sabounchi, A.M., 1998. "Effect of ambient temperature on the demanded energy of solar cells at different inclinations," Renewable Energy, Elsevier, vol. 14(1), pages 149-155.
    7. Burnett, Dougal & Barbour, Edward & Harrison, Gareth P., 2014. "The UK solar energy resource and the impact of climate change," Renewable Energy, Elsevier, vol. 71(C), pages 333-343.
    8. Detlef Vuuren & Jae Edmonds & Mikiko Kainuma & Keywan Riahi & Allison Thomson & Kathy Hibbard & George Hurtt & Tom Kram & Volker Krey & Jean-Francois Lamarque & Toshihiko Masui & Malte Meinshausen & N, 2011. "The representative concentration pathways: an overview," Climatic Change, Springer, vol. 109(1), pages 5-31, November.
    9. Ridley, Barbara & Boland, John & Lauret, Philippe, 2010. "Modelling of diffuse solar fraction with multiple predictors," Renewable Energy, Elsevier, vol. 35(2), pages 478-483.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Barbón, A. & Ayuso, P. Fortuny & Bayón, L. & Silva, C.A., 2021. "A comparative study between racking systems for photovoltaic power systems," Renewable Energy, Elsevier, vol. 180(C), pages 424-437.
    2. Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Rodríguez-Suanzes, C., 2022. "Analysis of the tilt and azimuth angles of photovoltaic systems in non-ideal positions for urban applications," Applied Energy, Elsevier, vol. 305(C).
    3. Ha, Subin & Zhou, Zixuan & Im, Eun-Soon & Lee, Young-Mi, 2023. "Comparative assessment of future solar power potential based on CMIP5 and CMIP6 multi-model ensembles," Renewable Energy, Elsevier, vol. 206(C), pages 324-335.
    4. Bloomfield, H.C. & Brayshaw, D.J. & Troccoli, A. & Goodess, C.M. & De Felice, M. & Dubus, L. & Bett, P.E. & Saint-Drenan, Y.-M., 2021. "Quantifying the sensitivity of european power systems to energy scenarios and climate change projections," Renewable Energy, Elsevier, vol. 164(C), pages 1062-1075.
    5. Henckes, Philipp & Frank, Christopher & Küchler, Nils & Peter, Jakob & Wagner, Johannes, 2020. "Uncertainty estimation of investment planning models under high shares of renewables using reanalysis data," Energy, Elsevier, vol. 208(C).
    6. Chen, Xie & Zhou, Chaohui & Tian, Zhiyong & Mao, Hongzhi & Luo, Yongqiang & Sun, Deyu & Fan, Jianhua & Jiang, Liguang & Deng, Jie & Rosen, Marc A., 2023. "Different photovoltaic power potential variations in East and West China," Applied Energy, Elsevier, vol. 351(C).
    7. Yang, Zhikai & Liu, Pan & Cheng, Lei & Liu, Deli & Ming, Bo & Li, He & Xia, Qian, 2021. "Sizing utility-scale photovoltaic power generation for integration into a hydropower plant considering the effects of climate change: A case study in the Longyangxia of China," Energy, Elsevier, vol. 236(C).
    8. Zuluaga, Cristian Felipe & Avila-Diaz, Alvaro & Justino, Flavio B. & Martins, Fernando Ramos & Ceron, Wilmar L., 2022. "The climate change perspective of photovoltaic power potential in Brazil," Renewable Energy, Elsevier, vol. 193(C), pages 1019-1031.
    9. Ohba, Masamichi & Kanno, Yuki & Bando, Shigeru, 2023. "Effects of meteorological and climatological factors on extremely high residual load and possible future changes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    10. Reimuth, Andrea & Locherer, Veronika & Danner, Martin & Mauser, Wolfram, 2020. "How do changes in climate and consumption loads affect residential PV coupled battery energy systems?," Energy, Elsevier, vol. 198(C).
    11. Leirpoll, Malene Eldegard & Næss, Jan Sandstad & Cavalett, Otavio & Dorber, Martin & Hu, Xiangping & Cherubini, Francesco, 2021. "Optimal combination of bioenergy and solar photovoltaic for renewable energy production on abandoned cropland," Renewable Energy, Elsevier, vol. 168(C), pages 45-56.
    12. Coker, Phil J. & Bloomfield, Hannah C. & Drew, Daniel R. & Brayshaw, David J., 2020. "Interannual weather variability and the challenges for Great Britain’s electricity market design," Renewable Energy, Elsevier, vol. 150(C), pages 509-522.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chinchilla, Monica & Santos-Martín, David & Carpintero-Rentería, Miguel & Lemon, Scott, 2021. "Worldwide annual optimum tilt angle model for solar collectors and photovoltaic systems in the absence of site meteorological data," Applied Energy, Elsevier, vol. 281(C).
    2. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C. & Chan, Wilco W.H., 2016. "Prediction of diffuse solar irradiance using machine learning and multivariable regression," Applied Energy, Elsevier, vol. 181(C), pages 367-374.
    3. Madeleine McPherson & Theofilos Sotiropoulos-Michalakakos & LD Danny Harvey & Bryan Karney, 2017. "An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset," Energies, MDPI, vol. 10(7), pages 1-14, July.
    4. Zhang, Xingxing & Shen, Jingchun & Lu, Yan & He, Wei & Xu, Peng & Zhao, Xudong & Qiu, Zhongzhu & Zhu, Zishang & Zhou, Jinzhi & Dong, Xiaoqiang, 2015. "Active Solar Thermal Facades (ASTFs): From concept, application to research questions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 32-63.
    5. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2016. "Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 246-260.
    6. Deo, Ravinesh C. & Şahin, Mehmet, 2017. "Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 828-848.
    7. Copper, J.K. & Sproul, A.B., 2012. "Comparative study of mathematical models in estimating solar irradiance for Australia," Renewable Energy, Elsevier, vol. 43(C), pages 130-139.
    8. Kuo, Chia-Wei & Chang, Wen-Chey & Chang, Keh-Chin, 2014. "Modeling the hourly solar diffuse fraction in Taiwan," Renewable Energy, Elsevier, vol. 66(C), pages 56-61.
    9. Buffat, René & Grassi, Stefano & Raubal, Martin, 2018. "A scalable method for estimating rooftop solar irradiation potential over large regions," Applied Energy, Elsevier, vol. 216(C), pages 389-401.
    10. Nunez Munoz, Maria & Ballantyne, Erica E.F. & Stone, David A., 2022. "Development and evaluation of empirical models for the estimation of hourly horizontal diffuse solar irradiance in the United Kingdom," Energy, Elsevier, vol. 241(C).
    11. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    12. Haghdadi, Navid & Copper, Jessie & Bruce, Anna & MacGill, Iain, 2017. "A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data," Renewable Energy, Elsevier, vol. 108(C), pages 390-400.
    13. Starke, Allan R. & Lemos, Leonardo F.L. & Barni, Cristian M. & Machado, Rubinei D. & Cardemil, José M. & Boland, John & Colle, Sergio, 2021. "Assessing one-minute diffuse fraction models based on worldwide climate features," Renewable Energy, Elsevier, vol. 177(C), pages 700-714.
    14. Marques Filho, Edson P. & Oliveira, Amauri P. & Vita, Willian A. & Mesquita, Francisco L.L. & Codato, Georgia & Escobedo, João F. & Cassol, Mariana & França, José Ricardo A., 2016. "Global, diffuse and direct solar radiation at the surface in the city of Rio de Janeiro: Observational characterization and empirical modeling," Renewable Energy, Elsevier, vol. 91(C), pages 64-74.
    15. Moretón, R. & Lorenzo, E. & Pinto, A. & Muñoz, J. & Narvarte, L., 2017. "From broadband horizontal to effective in-plane irradiation: A review of modelling and derived uncertainty for PV yield prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 886-903.
    16. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    17. Sawadogo, Windmanagda & Abiodun, Babatunde J. & Okogbue, Emmanuel C., 2020. "Impacts of global warming on photovoltaic power generation over West Africa," Renewable Energy, Elsevier, vol. 151(C), pages 263-277.
    18. Abreu, Edgar F.M. & Canhoto, Paulo & Costa, Maria João, 2019. "Prediction of diffuse horizontal irradiance using a new climate zone model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 28-42.
    19. Starke, Allan R. & Lemos, Leonardo F.L. & Boland, John & Cardemil, José M. & Colle, Sergio, 2018. "Resolution of the cloud enhancement problem for one-minute diffuse radiation prediction," Renewable Energy, Elsevier, vol. 125(C), pages 472-484.
    20. Pérez, Juan C. & González, Albano & Díaz, Juan P. & Expósito, Francisco J. & Felipe, Jonatan, 2019. "Climate change impact on future photovoltaic resource potential in an orographically complex archipelago, the Canary Islands," Renewable Energy, Elsevier, vol. 133(C), pages 749-759.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:171:y:2019:i:c:p:135-148. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.