IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

Location optimization of solar plants by an integrated hierarchical DEA PCA approach

  • Azadeh, A.
  • Ghaderi, S.F.
  • Maghsoudi, A.
Registered author(s):

    Unique features of renewable energies such as solar energy has caused increasing demands for such resources. In order to use solar energy as a natural resource, environmental circumstances and geographical location related to solar intensity must be considered. Different factors may affect on the selection of a suitable location for solar plants. These factors must be considered concurrently for optimum location identification of solar plants. This article presents an integrated hierarchical approach for location of solar plants by data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT). Furthermore, an integrated hierarchical DEA approach incorporating the most relevant parameters of solar plants is introduced. Moreover, 2 multivariable methods namely, PCA and NT are used to validate the results of DEA model. The prescribed approach is tested for 25 different cities in Iran with 6 different regions within each city. This is the first study that considers an integrated hierarchical DEA approach for geographical location optimization of solar plants. Implementation of the proposed approach would enable the energy policy makers to select the best-possible location for construction of a solar power plant with lowest possible costs.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 36 (2008)
    Issue (Month): 10 (October)
    Pages: 3993-4004

    in new window

    Handle: RePEc:eee:enepol:v:36:y:2008:i:10:p:3993-4004
    Contact details of provider: Web page:

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. Jacobsen, S. K. & Madsen, O. B. G., 1980. "A comparative study of heuristics for a two-level routing-location problem," European Journal of Operational Research, Elsevier, vol. 5(6), pages 378-387, December.
    2. Ramanathan, R, 2001. "Comparative Risk Assessment of energy supply technologies: a Data Envelopment Analysis approach," Energy, Elsevier, vol. 26(2), pages 197-203.
    3. Al-Alawi, S.M. & Al-Hinai, H.A., 1998. "An ANN-based approach for predicting global radiation in locations with no direct measurement instrumentation," Renewable Energy, Elsevier, vol. 14(1), pages 199-204.
    4. Olesen, O. B. & Petersen, N. C., 1995. "Incorporating quality into data envelopment analysis: a stochastic dominance approach," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 117-135, April.
    5. A. P. Thirlwall, 1983. "Introduction," Journal of Post Keynesian Economics, M.E. Sharpe, Inc., vol. 5(3), pages 341-344, April.
    6. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    7. Zhu, Joe, 1998. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities," European Journal of Operational Research, Elsevier, vol. 111(1), pages 50-61, November.
    8. Bahel, V. & Srinivasan, R. & Bakhsh, H., 1986. "Solar radiation for Dhahran, Saudi Arabia," Energy, Elsevier, vol. 11(10), pages 985-989.
    9. Sözen, Adnan & Arcaklıoğlu, Erol & Özalp, Mehmet & Çağlar, Naci, 2005. "Forecasting based on neural network approach of solar potential in Turkey," Renewable Energy, Elsevier, vol. 30(7), pages 1075-1090.
    10. Sözen, Adnan & Arcaklioglu, Erol & Özalp, Mehmet & Kanit, E. Galip, 2005. "Solar-energy potential in Turkey," Applied Energy, Elsevier, vol. 80(4), pages 367-381, April.
    11. Nozick, Linda K. & Borderas, Hector & Meyburg, Arnim H., 1998. "Evaluation of travel demand measures and programs: a data envelopment analysis approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(5), pages 331-343, September.
    12. Fare, Rolf & Grosskopf, Shawna & Tyteca, Daniel, 1996. "An activity analysis model of the environmental performance of firms--application to fossil-fuel-fired electric utilities," Ecological Economics, Elsevier, vol. 18(2), pages 161-175, August.
    13. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    14. Domschke, Wolfgang & Drexl, Andreas, 1985. "Location and layout planning – an international bibliography," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 36418, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    15. Mohandes, M. & Rehman, S. & Halawani, T.O., 1998. "Estimation of global solar radiation using artificial neural networks," Renewable Energy, Elsevier, vol. 14(1), pages 179-184.
    16. A. Meltzer & Peter Ordeshook & Thomas Romer, 1983. "Introduction," Public Choice, Springer, vol. 41(1), pages 1-5, January.
    17. Wirasinghe, S. C. & Waters, N. M., 1983. "An approximate procedure for determining the number, capacities and locations of solid waste transfer-stations in an urban region," European Journal of Operational Research, Elsevier, vol. 12(1), pages 105-111, January.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:36:y:2008:i:10:p:3993-4004. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.