IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i2p385-d308180.html
   My bibliography  Save this article

Assessment of Simulated Solar Irradiance on Days of High Intermittency Using WRF-Solar

Author

Listed:
  • Abhnil Amtesh Prasad

    (School of Photovoltaics and Renewable Energy Engineering, University of New South Wales, Sydney, NSW 2052, Australia)

  • Merlinde Kay

    (School of Photovoltaics and Renewable Energy Engineering, University of New South Wales, Sydney, NSW 2052, Australia)

Abstract

Improvements in the short-term predictability of irradiance in numerical weather prediction models can assist grid operators in managing intermittent solar-generated electricity. In this study, the performance of the Weather Research and Forecasting (WRF) model when simulating different components of solar irradiance was tested under days of high intermittency at Mildura, a site located on the border of New South Wales and Victoria, Australia. Initially, four intermittent and clear case days were chosen, later extending to a full year study in 2005. A specific configuration and augmentation of the WRF model (version 3.6.1) designed for solar energy applications (WRF-Solar) with an optimum physics ensemble derived from literature over Australia was used to simulate solar irradiance with four nested domains nudged to ERA-Interim boundary conditions at grid resolutions (45, 15, 5, and 1.7 km) centred over Mildura. The Bureau of Meteorology (BOM) station dataset available at minute timescales and hourly derived satellite irradiance products were used to validate the simulated products. Results showed that on days of high intermittency, simulated solar irradiance at finer resolution was affected by errors in simulated humidity and winds (speed and direction) affecting clouds and circulation, but the latter improves at coarser resolutions; this is most likely from reduced displacement errors in clouds.

Suggested Citation

  • Abhnil Amtesh Prasad & Merlinde Kay, 2020. "Assessment of Simulated Solar Irradiance on Days of High Intermittency Using WRF-Solar," Energies, MDPI, vol. 13(2), pages 1-22, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:385-:d:308180
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/2/385/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/2/385/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dasari, Hari Prasad & Desamsetti, Srinivas & Langodan, Sabique & Attada, Raju & Kunchala, Ravi Kumar & Viswanadhapalli, Yesubabu & Knio, Omar & Hoteit, Ibrahim, 2019. "High-resolution assessment of solar energy resources over the Arabian Peninsula," Applied Energy, Elsevier, vol. 248(C), pages 354-371.
    2. Jun Yin & Amilcare Porporato, 2017. "Diurnal cloud cycle biases in climate models," Nature Communications, Nature, vol. 8(1), pages 1-8, December.
    3. Verbois, Hadrien & Blanc, Philippe & Huva, Robert & Saint-Drenan, Yves-Marie & Rusydi, Andrivo & Thiery, Alexandre, 2020. "Beyond quadratic error: Case-study of a multiple criteria approach to the performance assessment of numerical forecasts of solar irradiance in the tropics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    4. Kannan, Nadarajah & Vakeesan, Divagar, 2016. "Solar energy for future world: - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1092-1105.
    5. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2015. "Assessment of direct normal irradiance and cloud connections using satellite data over Australia," Applied Energy, Elsevier, vol. 143(C), pages 301-311.
    6. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    7. Reikard, Gordon & Haupt, Sue Ellen & Jensen, Tara, 2017. "Forecasting ground-level irradiance over short horizons: Time series, meteorological, and time-varying parameter models," Renewable Energy, Elsevier, vol. 112(C), pages 474-485.
    8. Huang, Jing & Troccoli, Alberto & Coppin, Peter, 2014. "An analytical comparison of four approaches to modelling the daily variability of solar irradiance using meteorological records," Renewable Energy, Elsevier, vol. 72(C), pages 195-202.
    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. Abhnil Amtesh Prasad & Merlinde Kay, 2021. "Prediction of Solar Power Using Near-Real Time Satellite Data," Energies, MDPI, vol. 14(18), pages 1-20, September.
    2. Caitlin M. Berry & William Kleiber & Bri‐Mathias Hodge, 2023. "Subordinated Gaussian processes for solar irradiance," Environmetrics, John Wiley & Sons, Ltd., vol. 34(6), September.
    3. Maldonado-Salguero, Patricia & Bueso-Sánchez, María Carmen & Molina-García, Ángel & Sánchez-Lozano, Juan Miguel, 2022. "Spatio-temporal dynamic clustering modeling for solar irradiance resource assessment," Renewable Energy, Elsevier, vol. 200(C), pages 344-359.
    4. Prasad, Abhnil Amtesh & Yang, Yuqing & Kay, Merlinde & Menictas, Chris & Bremner, Stephen, 2021. "Synergy of solar photovoltaics-wind-battery systems in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    5. Dimitris Drikakis & Talib Dbouk, 2022. "The Role of Computational Science in Wind and Solar Energy: A Critical Review," Energies, MDPI, vol. 15(24), pages 1-20, December.
    6. Wen-Chang Tsai & Chia-Sheng Tu & Chih-Ming Hong & Whei-Min Lin, 2023. "A Review of State-of-the-Art and Short-Term Forecasting Models for Solar PV Power Generation," Energies, MDPI, vol. 16(14), pages 1-30, July.
    7. Prasad, Abhnil Amtesh & Nishant, Nidhi & Kay, Merlinde, 2022. "Dust cycle and soiling issues affecting solar energy reductions in Australia using multiple datasets," Applied Energy, Elsevier, vol. 310(C).
    8. Cheng, Xinghong & Ye, Dong & Shen, Yanbo & Li, Deping & Feng, Jinming, 2022. "Studies on the improvement of modelled solar radiation and the attenuation effect of aerosol using the WRF-Solar model with satellite-based AOD data over north China," Renewable Energy, Elsevier, vol. 196(C), pages 358-365.

    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. Dasari, Hari Prasad & Desamsetti, Srinivas & Langodan, Sabique & Attada, Raju & Kunchala, Ravi Kumar & Viswanadhapalli, Yesubabu & Knio, Omar & Hoteit, Ibrahim, 2019. "High-resolution assessment of solar energy resources over the Arabian Peninsula," Applied Energy, Elsevier, vol. 248(C), pages 354-371.
    2. Prasad, Abhnil Amtesh & Yang, Yuqing & Kay, Merlinde & Menictas, Chris & Bremner, Stephen, 2021. "Synergy of solar photovoltaics-wind-battery systems in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    3. Abhnil Amtesh Prasad & Merlinde Kay, 2021. "Prediction of Solar Power Using Near-Real Time Satellite Data," Energies, MDPI, vol. 14(18), pages 1-20, September.
    4. Moreira, Alexandre & Pozo, David & Street, Alexandre & Sauma, Enzo & Strbac, Goran, 2021. "Climate‐aware generation and transmission expansion planning: A three‐stage robust optimization approach," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1099-1118.
    5. 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.
    6. Mohammadi, Kasra & Goudarzi, Navid, 2018. "Association of direct normal irradiance with El Niño Southern Oscillation and its consequence on concentrated solar power production in the US Southwest," Applied Energy, Elsevier, vol. 212(C), pages 1126-1137.
    7. Jurasz, Jakub & Beluco, Alexandre & Canales, Fausto A., 2018. "The impact of complementarity on power supply reliability of small scale hybrid energy systems," Energy, Elsevier, vol. 161(C), pages 737-743.
    8. Trigo-González, Mauricio & Batlles, F.J. & Alonso-Montesinos, Joaquín & Ferrada, Pablo & del Sagrado, J. & Martínez-Durbán, M. & Cortés, Marcelo & Portillo, Carlos & Marzo, Aitor, 2019. "Hourly PV production estimation by means of an exportable multiple linear regression model," Renewable Energy, Elsevier, vol. 135(C), pages 303-312.
    9. Pedro, Hugo T.C. & Lim, Edwin & Coimbra, Carlos F.M., 2018. "A database infrastructure to implement real-time solar and wind power generation intra-hour forecasts," Renewable Energy, Elsevier, vol. 123(C), pages 513-525.
    10. 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.
    11. Shuhao Chang & Qiancheng Wang & Haihua Hu & Zijian Ding & Hansen Guo, 2018. "An NNwC MPPT-Based Energy Supply Solution for Sensor Nodes in Buildings and Its Feasibility Study," Energies, MDPI, vol. 12(1), pages 1-20, December.
    12. Liu, Hailiang & Andresen, Gorm Bruun & Greiner, Martin, 2018. "Cost-optimal design of a simplified highly renewable Chinese electricity network," Energy, Elsevier, vol. 147(C), pages 534-546.
    13. Diane Palmer & Elena Koubli & Tom Betts & Ralph Gottschalg, 2017. "The UK Solar Farm Fleet: A Challenge for the National Grid? †," Energies, MDPI, vol. 10(8), pages 1-22, August.
    14. Al-Nimr, Moh'd.A. & Dawahdeh, Ahmad I., 2023. "A novel hybrid reverse osmosis and flash desalination system powered by solar photovoltaic/thermal collectors," Renewable Energy, Elsevier, vol. 218(C).
    15. Muhammad Suleman Malik & Naveed Iftikhar & Abdul Wadood & Muhammad Omer Khan & Muhammad Usman Asghar & Shahbaz Khan & Tahir Khurshaid & Ki-Chai Kim & Zabdur Rehman & S. Tauqeer ul Islam Rizvi, 2020. "Design and Fabrication of Solar Thermal Energy Storage System Using Potash Alum as a PCM," Energies, MDPI, vol. 13(23), pages 1-16, November.
    16. Nantian Huang & Ruiqing Li & Lin Lin & Zhiyong Yu & Guowei Cai, 2018. "Low Redundancy Feature Selection of Short Term Solar Irradiance Prediction Using Conditional Mutual Information and Gauss Process Regression," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
    17. Tingting Zhu & Yuanzhe Li & Zhenye Li & Yiren Guo & Chao Ni, 2022. "Inter-Hour Forecast of Solar Radiation Based on Long Short-Term Memory with Attention Mechanism and Genetic Algorithm," Energies, MDPI, vol. 15(3), pages 1-14, January.
    18. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    19. Bertrand, Cédric & Vanderveken, Gilles & Journée, Michel, 2015. "Evaluation of decomposition models of various complexity to estimate the direct solar irradiance over Belgium," Renewable Energy, Elsevier, vol. 74(C), pages 618-626.
    20. Schinke-Nendza, A. & von Loeper, F. & Osinski, P. & Schaumann, P. & Schmidt, V. & Weber, C., 2021. "Probabilistic forecasting of photovoltaic power supply — A hybrid approach using D-vine copulas to model spatial dependencies," Applied Energy, Elsevier, vol. 304(C).

    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:gam:jeners:v:13:y:2020:i:2:p:385-:d:308180. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.