Analysis of Spatiotemporal Balancing between Wind and Solar Energy Resources in the Southern Iberian Peninsula

F. J. Santos-Alamillos Physics Department, University of Jaén, Andalusia, Spain

Search for other papers by F. J. Santos-Alamillos in
Current site
Google Scholar
PubMed
Close
,
D. Pozo-Vázquez Physics Department, University of Jaén, Andalusia, Spain

Search for other papers by D. Pozo-Vázquez in
Current site
Google Scholar
PubMed
Close
,
J. A. Ruiz-Arias Physics Department, University of Jaén, Andalusia, Spain

Search for other papers by J. A. Ruiz-Arias in
Current site
Google Scholar
PubMed
Close
,
V. Lara-Fanego Physics Department, University of Jaén, Andalusia, Spain

Search for other papers by V. Lara-Fanego in
Current site
Google Scholar
PubMed
Close
, and
J. Tovar-Pescador Physics Department, University of Jaén, Andalusia, Spain

Search for other papers by J. Tovar-Pescador in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Electricity from wind and, to a lesser extent, solar energy is intermittent and not controllable. Unlike conventional power generation, therefore, this electricity is not suitable to supply base-load electric power. In the future, with greater penetration of these renewable sources, intermittency and control problems will become critical. Here, the authors explore the use of canonical correlation analysis (CCA) for analyzing spatiotemporal balancing between regional solar and wind energy resources. The CCA allows optimal distribution of wind farms and solar energy plants across a territory to minimize the variability of total energy input into the power supply system. The method was tested in the southern half of the Iberian Peninsula, a region covering about 350 000 km2. The authors used daily-integrated wind and solar energy estimates in 2007 from the Weather Research and Forecasting (WRF) mesoscale model, at a spatial resolution of 9 km. Results showed valuable balancing patterns in the study region, but with a marked seasonality in strength, sign, and spatial coverage. The autumn season showed the most noteworthy results, with a balancing pattern extending almost over the entire study region. With location of reference wind farms and photovoltaic (PV) plants according to the balancing patterns, their combined power production shows substantially lower variability than production of the wind farms and PV plants separately and combined production obtained with any other locations. Atmospheric circulations associated with the balancing patterns were found to be significantly different between seasons. In this regard, synoptic-scale variability played an important role, but so did topographic conditions, especially near the Strait of Gibraltar.

Corresponding author address: D. Pozo-Vázquez, Physics Department, University of Jaén, Campus las Lagunillas, E23071 Jaén, Andalusia, Spain. E-mail: dpozo@ujaen.es

Abstract

Electricity from wind and, to a lesser extent, solar energy is intermittent and not controllable. Unlike conventional power generation, therefore, this electricity is not suitable to supply base-load electric power. In the future, with greater penetration of these renewable sources, intermittency and control problems will become critical. Here, the authors explore the use of canonical correlation analysis (CCA) for analyzing spatiotemporal balancing between regional solar and wind energy resources. The CCA allows optimal distribution of wind farms and solar energy plants across a territory to minimize the variability of total energy input into the power supply system. The method was tested in the southern half of the Iberian Peninsula, a region covering about 350 000 km2. The authors used daily-integrated wind and solar energy estimates in 2007 from the Weather Research and Forecasting (WRF) mesoscale model, at a spatial resolution of 9 km. Results showed valuable balancing patterns in the study region, but with a marked seasonality in strength, sign, and spatial coverage. The autumn season showed the most noteworthy results, with a balancing pattern extending almost over the entire study region. With location of reference wind farms and photovoltaic (PV) plants according to the balancing patterns, their combined power production shows substantially lower variability than production of the wind farms and PV plants separately and combined production obtained with any other locations. Atmospheric circulations associated with the balancing patterns were found to be significantly different between seasons. In this regard, synoptic-scale variability played an important role, but so did topographic conditions, especially near the Strait of Gibraltar.

Corresponding author address: D. Pozo-Vázquez, Physics Department, University of Jaén, Campus las Lagunillas, E23071 Jaén, Andalusia, Spain. E-mail: dpozo@ujaen.es
Save
  • Alsamamra, H., J. Ruiz-Arias, D. Pozo-Vázquez, and J. Tovar-Pescador, 2009: A comparative study of ordinary and residual kriging techniques for mapping global solar radiation over southern Spain. Agric. For. Meteor., 149, 13431357.

    • Search Google Scholar
    • Export Citation
  • Anderson, R., L. Tatham, and W. C. Black, 1998: Multivariate Data Analysis. J. F. Hair and E. Rolph, Eds., Prentice Hall, 116 pp.

  • Archer, C., and M. Jacobson, 2003: Spatial and temporal distributions of us winds and wind power at 80 m derived from measurements. J. Geophys. Res., 108, 120.

    • Search Google Scholar
    • Export Citation
  • Archer, C., and M. Jacobson, 2007: Supplying base load power and reducing transmission requirements by interconnecting wind farms. J. Appl. Meteor. Climatol., 46, 17011717.

    • Search Google Scholar
    • Export Citation
  • Argüeso, D., J. Hidalgo-Muñoz, S. Gámiz-Fortis, M. Esteban-Parra, J. Dudhia, and Y. Castro-Díez, 2011: Evaluation of WRF parameterizations for climate studies over southern Spain using a multistep regionalization. J. Climate, 24, 56335651.

    • Search Google Scholar
    • Export Citation
  • Barnett, T., and R. Preisendorfer, 1987: Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis. Mon. Wea. Rev., 115, 18251850.

    • Search Google Scholar
    • Export Citation
  • Bartlett, M. S., 1941: The statistical significance of canonical correlations. Biometrika, 32, 2938.

  • Borge, R., V. Alexandrov, J. José del Vas, J. Lumbreras, and E. Rodríguez, 2008: A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula. Atmos. Environ., 42, 85608574.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An intercomparison of methods for finding coupled patterns in climate data. J. Climate, 5, 541560.

    • Search Google Scholar
    • Export Citation
  • Cassola, F., M. Burlando, M. Antonelli, and C. Ratto, 2008: Optimization of the regional spatial distribution of wind power plants to minimize the variability of wind energy input into power supply systems. J. Appl. Meteor. Climatol., 47, 30993116.

    • Search Google Scholar
    • Export Citation
  • Castro-Díez, Y., D. Pozo-Vázquez, F. Rodrigo, and M. Esteban-Parra, 2002: NAO and winter temperature variability in southern Europe. Geophys. Res. Lett., 29, 1160.

    • Search Google Scholar
    • Export Citation
  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface-hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107.

    • Search Google Scholar
    • Export Citation
  • Fernández, J., J. Montávez, J. Sáenz, J. González-Rouco, and E. Zorita, 2007: Sensitivity of the MM5 mesoscale model to physical parameterizations for regional climate studies: Annual cycle. J. Geophys. Res., 112, D04101, doi:10.1029/2005JD006649.

    • Search Google Scholar
    • Export Citation
  • Gámiz-Fortis, S., D. Pozo-Vázquez, R. Trigo, and Y. Castro-Díez, 2008: Quantifying the predictability of winter river flow in Iberia. Part I: Interannual predictability. J. Climate, 21, 24842502.

    • Search Google Scholar
    • Export Citation
  • Gómez, A., J. Zubizarreta, C. Dopazo, and N. Fueyo, 2010: Spanish energy roadmap to 2020: Socioeconomic implications of renewable targets. Energy, 36, 19731985.

    • Search Google Scholar
    • Export Citation
  • Gueymard, C., and S. Wilcox, 2011: Assessment of spatial and temporal variability in the US solar resource from radiometric measurements and predictions from models using ground based or satellite data. Sol. Energy, 85, 10681084.

    • Search Google Scholar
    • Export Citation
  • Hahmann, A., D. Rostkier-Edelstein, F. Vandenberghe, Y. Liu, and S. Swerdlin, 2010: A reanalysis system for the generation of mesoscale climatographies. J. Appl. Meteor. Climatol., 49, 954972.

    • Search Google Scholar
    • Export Citation
  • Heide, D., L. Von Bremen, M. Greiner, C. Hoffmann, M. Speckmann, and S. Bonger, 2010: Seasonal optimal mix of wind and solar power in a future, highly renewable Europe. Renewable Energy, 35, 24832489.

    • Search Google Scholar
    • Export Citation
  • Heide, D., M. Greiner, L. von Bremen, and C. Hoffmann, 2011: Reduced storage and balancing needs in a fully renewable European power system with excess wind and solar power generation. Renewable Energy, 36, 25152523.

    • Search Google Scholar
    • Export Citation
  • Hong, S., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J., Y. Kushnir, G. Ottersen, and M. Visbeck, 2003: An overview of the North Atlantic Oscillation. The North Atlantic Oscillation: Climatic Significance and Environmental Impact, Geophys. Monogr., Vol. 134, Amer. Geophys. Union, 1–36.

  • Hutchinson, M., J. Kalma, and M. Johnson, 1984: Monthly estimates of wind speed and wind run for Australia. Int. J. Climatol., 4, 311324.

    • Search Google Scholar
    • Export Citation
  • IEA, cited 2008: World energy outlook. International Energy Agency, OECD publication service, OECD, Paris, 578 pp. [Available online at http://www.worldenergyoutlook.org/media/weowebsite/2008-1994/WEO2008.pdf.]

  • IEA, cited 2009: Technology roadmap: Wind energy. International Energy Agency, OECD publication service, OECD, Paris, 52 pp. [Available online at http://www.iea.org/publications/freepublications/publication/Wind_Roadmap.pdf.]

  • IEA, cited 2010a: Technology roadmap: Concentrating solar power. International Energy Agency, OECD publication service, OECD, Paris, 52 pp. [Available online at http://www.iea.org/publications/freepublications/publication/csp_roadmap.pdf.]

  • IEA, cited 2010b: Technology roadmap: Solar photovoltaic energy. International Energy Agency, OECD publication service, OECD, Paris, 48 pp. [http://www.iea.org/publications/freepublications/publication/pv_roadmap.pdf.]

  • Jacobson, M., and M. Delucchi, 2009: A path to sustainable energy by 2030. Sci. Amer., 301, 5865.

  • Kahn, E., 1979: The reliability of distributed wind generators. Electr. Power Syst. Res., 2, 114.

  • Kain, J., and J. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47, 27842802.

    • Search Google Scholar
    • Export Citation
  • Kain, J., and J. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. Representation of Cumulus Convection in Numerical Models, K. Emanuel and D. J. Raymond, Eds., Amer. Meteor. Soc., 165–170.

  • Kariniotakis, G., and Coauthors, 2006: Next generation short-term forecasting of wind power: Overview of the ANEMOS project. Proc. EWEC 2006, Athens, Greece, European Wind Energy Association, 10 pp. [Available online at http://www.ewec2006proceedings.info/allfiles2/965_Ewec2006fullpaper.pdf.]

  • Kempton, W., F. Pimenta, D. Veron, and B. Colle, 2010: Electric power from offshore wind via synoptic-scale interconnection. Proc. Natl. Acad. Sci. USA, 107, 72407245.

    • Search Google Scholar
    • Export Citation
  • Landberg, L., 1997: The availability and variability of the European wind resource. Int. J. Sustainable Energy, 18, 313320.

  • Lara-Fanego, V., J. Ruiz-Arias, D. Pozo-Vázquez, F. Santos-Alamillos, and J. Tovar-Pescador, 2012: Evaluation of the WRF model solar irradiance forecasts in Andalusia (southern Spain). Sol. Energy, 86, 22002217.

    • Search Google Scholar
    • Export Citation
  • Lorenz, E., T. Scheidsteger, J. Hurka, D. Heinemann, and C. Kurz, 2011: Regional PV power prediction for improved grid integration. Prog. Photovoltaics Res. Appl., 19, 757771, doi:10.1002/pip.1033.

    • Search Google Scholar
    • Export Citation
  • McVicar, T., T. Van Niel, L. Li, M. Roderick, D. Rayner, L. Ricciardulli, and R. Donohue, 2008: Wind speed climatology and trends for Australia, 1975–2006: Capturing the stilling phenomenon and comparison with near-surface reanalysis output. Geophys. Res. Lett., 35, L20403, doi:10.1029/2008GL035627.

    • Search Google Scholar
    • Export Citation
  • Mills, A., and R. Wiser, 2010: Implications of wide-area geographic diversity for short-term variability of solar power. Lawrence Berkeley National Laboratory Tech. Rep. LBNL-3884E, 45 pp.

  • Mlawer, E., S. Taubman, P. Brown, M. Iacono, and S. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 (D14), 16 66316 682.

    • Search Google Scholar
    • Export Citation
  • Papadimas, C., A. Fotiadi, N. Hatzianastassiou, I. Vardavas, and A. Bartzokas, 2010: Regional co-variability and teleconnection patterns in surface solar radiation on a planetary scale. Int. J. Climatol., 30, 23142329.

    • Search Google Scholar
    • Export Citation
  • Pozo-Vázquez, D., M. Esteban-Parra, F. Rodrigo, and Y. Castro-Díez, 2000: An analysis of the variability of the North Atlantic Oscillation in the time and the frequency domains. Int. J. Climatol., 20, 16751692.

    • Search Google Scholar
    • Export Citation
  • Pozo-Vázquez, D., M. Esteban-Parra, F. Rodrigo, and Y. Castro-Díez, 2001: A study of NAO variability and its possible non-linear influences on European surface temperature. Climate Dyn., 17, 701715.

    • Search Google Scholar
    • Export Citation
  • Pozo-Vázquez, D., J. Tovar-Pescador, S. Gámiz-Fortis, M. Esteban-Parra, and Y. Castro-Díez, 2004: NAO and solar radiation variability in the European north Atlantic region. Geophys. Res. Lett., 31, L05201, doi:10.1029/2003GL018502.

    • Search Google Scholar
    • Export Citation
  • Pozo-Vázquez, D., F. Santos-Alamillos, V. Lara-Fanego, J. Ruiz-Arias, and J. Tovar-Pescador, 2011: The impact of the NAO on the solar and wind energy resources in the Mediterranean area. Hydrological, Socioeconomic and Ecological Impacts of the North Atlantic Oscillation in the Mediterranean Region, S. Vicente-Serrano and R. Trigo, Eds., Advances in Global Change Research, Vol. 46, Springer, 213–231.

  • Ramos-Calzado, P., J. Gómez-Camacho, F. Pérez-Bernal, and M. Pita-López, 2008: A novel approach to precipitation series completion in climatological datasets: Application to Andalusia. Int. J. Climatol., 28, 15251534.

    • Search Google Scholar
    • Export Citation
  • Romero, R., J. Guijarro, C. Ramis, and S. Alonso, 1998: A 30-year (1964-1993) daily rainfall data base for the Spanish Mediterranean regions: First exploratory study. Int. J. Climatol., 18, 541560.

    • Search Google Scholar
    • Export Citation
  • Ruiz-Arias, J., D. Pozo-Vázquez, N. Sánchez-Sánchez, J. Montávez, A. Hayas-Barrú, and J. Tovar-Pescador, 2008: Evaluation of two MM5-PBL parameterizations for solar radiation and temperature estimation in the South-Eastern area of the Iberian Peninsula. Nuovo Cimento, 31, 825842.

    • Search Google Scholar
    • Export Citation
  • Ruiz-Arias, J., D. Pozo-Vázquez, V. Lara-Fanego, F. J. Santos-Alamillos, and J. Tovar-Pescador, 2011: A high-resolution topographic correction method for clear-sky solar irradiance derived with a numerical weather prediction model. J. Appl. Meteor. Climatol., 50, 24602472.

    • Search Google Scholar
    • Export Citation
  • Ruiz-Arias, J., J. Terrados, D. Pozo-Vázquez, and G. Almonacid, 2012: An assessment of the renewable energies potential for intensive electricity production in the province of Jaen, southern Spain. Renewable Sustainable Energy Rev., 16, 29943001.

    • Search Google Scholar
    • Export Citation
  • Saintcross, J., R. Piwko, X. Bai, K. Clara, G. Jordan, N. Miller, and J. Zimberlin, 2005: The effects of integrating wind power on transmission system planning, reliability, and operations. The New York State Energy Research and Development Authority, 50 pp.

  • Skamarock, W. C., and Coauthors, 2008: A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 125 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3.pdf.]

  • Thompson, G., R. Rasmussen, and K. Manning, 2004: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon. Wea. Rev., 132, 519542.

    • Search Google Scholar
    • Export Citation
  • Trieb, F., and Coauthors, 2005: Concentrating solar power for the Mediterranean region. Tech. Rep., German Aerospace Center (DLR) Institute of Technical Thermodynamics, Section Systems Analysis and Technology Assessment, 25 pp.

  • Trigo, R., and C. DaCamara, 2000: Circulation weather types and their impact on the precipitation regime in Portugal. Int. J. Climatol., 20, 15591581.

    • Search Google Scholar
    • Export Citation
  • Trigo, R., T. Osborn, and J. Corte-Real, 2002: The North Atlantic oscillation influence on Europe: Climate impacts and associated physical mechanisms. Climate Res., 20, 917.

    • Search Google Scholar
    • Export Citation
  • Trigo, R., D. Pozo-Vázquez, T. Osborn, Y. Castro-Díez, S. Gámiz-Fortis, and M. Esteban-Parra, 2004: North Atlantic oscillation influence on precipitation, river flow and water resources in the Iberian Peninsula. Int. J. Climatol., 24, 925944.

    • Search Google Scholar
    • Export Citation
  • Tröster, E., R. Kuwahata, and T. Ackermann, cited 2011: European grid study 2030/2050. Tech. Rep., Energynautics GmbH, 63 pp. [Available online at http://www.energynautics.com/downloads/competences/energynautics_EUROPEAN-GRID-STUDY-2030-2050.pdf.]

  • UNESA, 2010: Annual Spanish electrical industry report. Spanish Electrical Industry Assoc. Rep., 303 pp. [Available online at http://www.unesa.es.]

  • Von Storch, H., 1999: Spatial patterns: EOFS and CCA. Analysis of Climate Variability: Applications of Statistical Technique, H. Von Storch and A. Navarra, Eds., Springer-Verlag, 227–257.

  • Von Storch, H., and F. Zwiers, 2001: Statistical Analysis in Climate Research. Cambridge University Press, 484 pp.

  • Weber, R., and M. Furger, 2001: Climatology of near-surface wind patterns over Switzerland. Int. J. Climatol., 21, 809827.

  • Widén, J., 2011: Correlations between large-scale solar and wind power in a future scenario for Sweden. IEEE Trans. Sustainable Energy, 2, 177184.

    • Search Google Scholar
    • Export Citation
  • Wiemken, E., H. Beyer, W. Heydenreich, and K. Kiefer, 2001: Power characteristics of PV ensembles: Experiences from the combined power production of 100 grid connected PV systems distributed over the area of Germany. Sol. Energy, 70, 513518.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 652 185 14
PDF Downloads 574 108 20