IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v216y2018icp172-182.html
   My bibliography  Save this article

Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data

Author

Listed:
  • Zhang, Hengxu
  • Cao, Yongji
  • Zhang, Yi
  • Terzija, Vladimir

Abstract

Considering the volatility and synergies of renewable energy sources, sufficient resource assessment is of great significance for investors and planners to reduce power fluctuations, increase integration capacity, and improve economic and social benefits. This paper proposes a tri-level framework to evaluate and visualize the spatiotemporal characteristics of regional wind and solar energy resources from the perspective of data mining. Furthermore, a free, open-source software package named Quantitative Synergy Assessment Toolbox for renewable energy sources (QSAT V1.0) has been developed with Python and hosted on GitHub, which is a useful tool for the resources assessment and preliminary regional synergetic planning. In the first level, the long-term reanalysis meteorological data of wind speed, solar irradiation and ambient temperature are acquired from MERRA, processed via virtual generation systems, and corrected by in-situ measured data. For the progressive two levels of single-site and wide-area data assessments, the data mining methods incorporating attribute construction, principal components analysis and k-means clustering are used to reduce the dimensionality and capture the temporal and spatial synergy patterns. According to the extracted patterns, the rational combinations of sub-regions can be selected as candidates to make full use of the synergies. Shandong province in China is taken as a demonstration to quantify and analyze the complementarities of solar and wind resources. The proposed method and tools can help enhance the planning of renewable energy sources.

Suggested Citation

  • Zhang, Hengxu & Cao, Yongji & Zhang, Yi & Terzija, Vladimir, 2018. "Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data," Applied Energy, Elsevier, vol. 216(C), pages 172-182.
    • Handle: RePEc:eee:appene:v:216:y:2018:i:c:p:172-182
    DOI: 10.1016/j.apenergy.2018.02.094
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918302198
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2018.02.094?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. 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.
    2. Zhou, Wei & Lou, Chengzhi & Li, Zhongshi & Lu, Lin & Yang, Hongxing, 2010. "Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems," Applied Energy, Elsevier, vol. 87(2), pages 380-389, February.
    3. Pietzcker, Robert Carl & Stetter, Daniel & Manger, Susanne & Luderer, Gunnar, 2014. "Using the sun to decarbonize the power sector: The economic potential of photovoltaics and concentrating solar power," Applied Energy, Elsevier, vol. 135(C), pages 704-720.
    4. Yang, H.X. & Lu, L. & Burnett, J., 2003. "Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong," Renewable Energy, Elsevier, vol. 28(11), pages 1813-1824.
    5. de Jong, Pieter & Dargaville, Roger & Silver, Jeremy & Utembe, Steven & Kiperstok, Asher & Torres, Ednildo Andrade, 2017. "Forecasting high proportions of wind energy supplying the Brazilian Northeast electricity grid," Applied Energy, Elsevier, vol. 195(C), pages 538-555.
    6. Bhandari, Binayak & Lee, Kyung-Tae & Lee, Caroline Sunyong & Song, Chul-Ki & Maskey, Ramesh K. & Ahn, Sung-Hoon, 2014. "A novel off-grid hybrid power system comprised of solar photovoltaic, wind, and hydro energy sources," Applied Energy, Elsevier, vol. 133(C), pages 236-242.
    7. Ermolenko, Boris V. & Ermolenko, Georgy V. & Fetisova, Yulia A. & Proskuryakova, Liliana N., 2017. "Wind and solar PV technical potentials: Measurement methodology and assessments for Russia," Energy, Elsevier, vol. 137(C), pages 1001-1012.
    8. Monforti, Fabio & Gonzalez-Aparicio, Iratxe, 2017. "Comparing the impact of uncertainties on technical and meteorological parameters in wind power time series modelling in the European Union," Applied Energy, Elsevier, vol. 206(C), pages 439-450.
    9. Suomalainen, Kiti & Wang, Vincent & Sharp, Basil, 2017. "Rooftop solar potential based on LiDAR data: Bottom-up assessment at neighbourhood level," Renewable Energy, Elsevier, vol. 111(C), pages 463-475.
    10. Gadad, Sanjeev & Deka, Paresh Chandra, 2016. "Offshore wind power resource assessment using Oceansat-2 scatterometer data at a regional scale," Applied Energy, Elsevier, vol. 176(C), pages 157-170.
    11. Monforti, F. & Huld, T. & Bódis, K. & Vitali, L. & D'Isidoro, M. & Lacal-Arántegui, R., 2014. "Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach," Renewable Energy, Elsevier, vol. 63(C), pages 576-586.
    12. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island," Applied Energy, Elsevier, vol. 121(C), pages 149-158.
    13. Sharp, Ed & Dodds, Paul & Barrett, Mark & Spataru, Catalina, 2015. "Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information," Renewable Energy, Elsevier, vol. 77(C), pages 527-538.
    14. Solomon, A.A. & Kammen, Daniel M. & Callaway, D., 2016. "Investigating the impact of wind–solar complementarities on energy storage requirement and the corresponding supply reliability criteria," Applied Energy, Elsevier, vol. 168(C), pages 130-145.
    15. Yang, Hongxing & Wei, Zhou & Chengzhi, Lou, 2009. "Optimal design and techno-economic analysis of a hybrid solar-wind power generation system," Applied Energy, Elsevier, vol. 86(2), pages 163-169, February.
    16. Akinyele, D.O. & Rayudu, R.K., 2016. "Community-based hybrid electricity supply system: A practical and comparative approach," Applied Energy, Elsevier, vol. 171(C), pages 608-628.
    17. Sorapipatana, Chumnong, 2010. "An assessment of solar energy potential in Kampuchea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2174-2178, October.
    18. Huber, Matthias & Dimkova, Desislava & Hamacher, Thomas, 2014. "Integration of wind and solar power in Europe: Assessment of flexibility requirements," Energy, Elsevier, vol. 69(C), pages 236-246.
    19. Sheridan, Blaise & Baker, Scott D. & Pearre, Nathaniel S. & Firestone, Jeremy & Kempton, Willett, 2012. "Calculating the offshore wind power resource: Robust assessment methods applied to the U.S. Atlantic Coast," Renewable Energy, Elsevier, vol. 43(C), pages 224-233.
    20. Khahro, Shahnawaz Farhan & Tabbassum, Kavita & Mahmood Soomro, Amir & Liao, Xiaozhong & Alvi, Muhammad Bux & Dong, Lei & Manzoor, M. Farhan, 2014. "Techno-economical evaluation of wind energy potential and analysis of power generation from wind at Gharo, Sindh Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 460-474.
    21. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    22. Bekele, Getachew & Palm, Björn, 2010. "Feasibility study for a standalone solar-wind-based hybrid energy system for application in Ethiopia," Applied Energy, Elsevier, vol. 87(2), pages 487-495, February.
    23. 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.
    24. Cannon, D.J. & Brayshaw, D.J. & Methven, J. & Coker, P.J. & Lenaghan, D., 2015. "Using reanalysis data to quantify extreme wind power generation statistics: A 33 year case study in Great Britain," Renewable Energy, Elsevier, vol. 75(C), pages 767-778.
    25. Pfenninger, Stefan & DeCarolis, Joseph & Hirth, Lion & Quoilin, Sylvain & Staffell, Iain, 2017. "The importance of open data and software: Is energy research lagging behind?," Energy Policy, Elsevier, vol. 101(C), pages 211-215.
    26. Ulazia, Alain & Saenz, Jon & Ibarra-Berastegui, Gabriel, 2016. "Sensitivity to the use of 3DVAR data assimilation in a mesoscale model for estimating offshore wind energy potential. A case study of the Iberian northern coastline," Applied Energy, Elsevier, vol. 180(C), pages 617-627.
    27. Hoicka, Christina E. & Rowlands, Ian H., 2011. "Solar and wind resource complementarity: Advancing options for renewable electricity integration in Ontario, Canada," Renewable Energy, Elsevier, vol. 36(1), pages 97-107.
    28. Bosch, Jonathan & Staffell, Iain & Hawkes, Adam D., 2018. "Temporally explicit and spatially resolved global offshore wind energy potentials," Energy, Elsevier, vol. 163(C), pages 766-781.
    29. Fillol, Erwann & Albarelo, Tommy & Primerose, Antoine & Wald, Lucien & Linguet, Laurent, 2017. "Spatiotemporal indicators of solar energy potential in the Guiana Shield using GOES images," Renewable Energy, Elsevier, vol. 111(C), pages 11-25.
    30. Bossavy, Arthur & Girard, Robin & Kariniotakis, Georges, 2016. "Sensitivity analysis in the technical potential assessment of onshore wind and ground solar photovoltaic power resources at regional scale," Applied Energy, Elsevier, vol. 182(C), pages 145-153.
    31. Widén, Joakim & Carpman, Nicole & Castellucci, Valeria & Lingfors, David & Olauson, Jon & Remouit, Flore & Bergkvist, Mikael & Grabbe, Mårten & Waters, Rafael, 2015. "Variability assessment and forecasting of renewables: A review for solar, wind, wave and tidal resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 356-375.
    32. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    33. Langodan, Sabique & Viswanadhapalli, Yesubabu & Dasari, Hari Prasad & Knio, Omar & Hoteit, Ibrahim, 2016. "A high-resolution assessment of wind and wave energy potentials in the Red Sea," Applied Energy, Elsevier, vol. 181(C), pages 244-255.
    34. Ramirez Camargo, Luis & Dorner, Wolfgang, 2016. "Comparison of satellite imagery based data, reanalysis data and statistical methods for mapping global solar radiation in the Lerma Valley (Salta, Argentina)," Renewable Energy, Elsevier, vol. 99(C), pages 57-68.
    Full references (including those not matched with items on IDEAS)

    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. Han, Shuang & Zhang, Lu-na & Liu, Yong-qian & Zhang, Hao & Yan, Jie & Li, Li & Lei, Xiao-hui & Wang, Xu, 2019. "Quantitative evaluation method for the complementarity of wind–solar–hydro power and optimization of wind–solar ratio," Applied Energy, Elsevier, vol. 236(C), pages 973-984.
    2. Alexis Tantet & Marc Stéfanon & Philippe Drobinski & Jordi Badosa & Silvia Concettini & Anna Cretì & Claudia D’Ambrosio & Dimitri Thomopulos & Peter Tankov, 2019. "e 4 clim 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy," Energies, MDPI, vol. 12(22), pages 1-37, November.
    3. Gruber, Katharina & Regner, Peter & Wehrle, Sebastian & Zeyringer, Marianne & Schmidt, Johannes, 2022. "Towards global validation of wind power simulations: A multi-country assessment of wind power simulation from MERRA-2 and ERA-5 reanalyses bias-corrected with the global wind atlas," Energy, Elsevier, vol. 238(PA).
    4. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Spatial and temporal assessments of complementarity for renewable energy resources in China," Energy, Elsevier, vol. 177(C), pages 262-275.
    5. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    6. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    7. 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, July.
    8. Hayes, Liam & Stocks, Matthew & Blakers, Andrew, 2021. "Accurate long-term power generation model for offshore wind farms in Europe using ERA5 reanalysis," Energy, Elsevier, vol. 229(C).
    9. 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.
    10. Mahesh, Aeidapu & Sandhu, Kanwarjit Singh, 2015. "Hybrid wind/photovoltaic energy system developments: Critical review and findings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1135-1147.
    11. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    12. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    13. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2017. "Optimisation of stand-alone hybrid energy systems supplemented by combustion-based prime movers," Applied Energy, Elsevier, vol. 196(C), pages 18-33.
    14. Berger, Mathias & Radu, David & Fonteneau, Raphaël & Henry, Robin & Glavic, Mevludin & Fettweis, Xavier & Le Du, Marc & Panciatici, Patrick & Balea, Lucian & Ernst, Damien, 2020. "Critical time windows for renewable resource complementarity assessment," Energy, Elsevier, vol. 198(C).
    15. Ingeborg Graabak & Magnus Korpås, 2016. "Variability Characteristics of European Wind and Solar Power Resources—A Review," Energies, MDPI, vol. 9(6), pages 1, June.
    16. 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.
    17. Ramirez Camargo, Luis & Gruber, Katharina & Nitsch, Felix, 2019. "Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems," Renewable Energy, Elsevier, vol. 133(C), pages 1468-1478.
    18. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
    19. Wang, Gang & Zhang, Zhen & Lin, Jianqing, 2024. "Multi-energy complementary power systems based on solar energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    20. Rabbani, R. & Zeeshan, M., 2020. "Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan," Renewable Energy, Elsevier, vol. 154(C), pages 1240-1251.

    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:appene:v:216:y:2018:i:c:p:172-182. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.