IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v36y2011i12p3394-3401.html
   My bibliography  Save this article

A flexible neural network-fuzzy data envelopment analysis approach for location optimization of solar plants with uncertainty and complexity

Author

Listed:
  • Azadeh, A.
  • Sheikhalishahi, M.
  • Asadzadeh, S.M.

Abstract

This study presents a flexible neuro-fuzzy approach for location optimization of solar plants with possible complexity and uncertainty. The flexible approach is composed of artificial neural network (ANN) and fuzzy data envelopment analysis (FDEA). The intelligent approach of this study is applied for location optimization of solar plants in Iran. First, FDEA is validated by DEA, and then it is used for ranking of solar plant units (SPUs) and the best α-cut is selected based on the test of Normality. Also, several ANNs are developed through multi layer perceptron (MLP) for ranking of solar plants and the best one with minimum mean absolute percentage of error (MAPE) is selected for further considerations. Finally, the preferred model (FDEA or ANN) is selected based on test of Normality. The implementation of the flexible approach for solar plants in Iran identifies the preferred FDEA at α = 0.3, where is the level of data uncertainty. This indicates that the data are collected from the uncertain and fuzzy environment. This is the first study that presents a flexible approach for identification of optimum location of solar plants with possible noise, non-linearity, complexity and environmental uncertainty. This would help policy makers to identify the preferred Strategy for location optimization problems associated with solar plant units.

Suggested Citation

  • Azadeh, A. & Sheikhalishahi, M. & Asadzadeh, S.M., 2011. "A flexible neural network-fuzzy data envelopment analysis approach for location optimization of solar plants with uncertainty and complexity," Renewable Energy, Elsevier, vol. 36(12), pages 3394-3401.
    • Handle: RePEc:eee:renene:v:36:y:2011:i:12:p:3394-3401
    DOI: 10.1016/j.renene.2011.05.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148111002461
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2011.05.018?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. Azadeh, A. & Ghaderi, S.F. & Maghsoudi, A., 2008. "Location optimization of solar plants by an integrated hierarchical DEA PCA approach," Energy Policy, Elsevier, vol. 36(10), pages 3993-4004, October.
    2. Özgür Özpeynirci & Murat Köksalan, 2007. "Performance evaluation using data envelopment analysis in the presence of time lags," Journal of Productivity Analysis, Springer, vol. 27(3), pages 221-229, June.
    3. Kalogirou, Soteris A., 2001. "Artificial neural networks in renewable energy systems applications: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 5(4), pages 373-401, December.
    4. Leduc, S. & Lundgren, J. & Franklin, O. & Dotzauer, E., 2010. "Location of a biomass based methanol production plant: A dynamic problem in northern Sweden," Applied Energy, Elsevier, vol. 87(1), pages 68-75, January.
    5. 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.
    6. 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.
    7. 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.
    8. Ramanathan, R, 2001. "Comparative Risk Assessment of energy supply technologies: a Data Envelopment Analysis approach," Energy, Elsevier, vol. 26(2), pages 197-203.
    9. Sözen, Adnan & Arcaklioglu, Erol, 2005. "Solar potential in Turkey," Applied Energy, Elsevier, vol. 80(1), pages 35-45, January.
    10. Bahel, V. & Srinivasan, R. & Bakhsh, H., 1986. "Solar radiation for Dhahran, Saudi Arabia," Energy, Elsevier, vol. 11(10), pages 985-989.
    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. Nakamoto, Yuya & Eguchi, Shogo, 2024. "How do seasonal and technical factors affect generation efficiency of photovoltaic power plants?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    2. Nili, Maryam & Seyedhosseini, Seyed Mohammad & Jabalameli, Mohammad Saeed & Dehghani, Ehsan, 2021. "A multi-objective optimization model to sustainable closed-loop solar photovoltaic supply chain network design: A case study in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    3. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Cheraghi, Sara, 2020. "Robust and stable flexible blood supply chain network design under motivational initiatives," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    4. Dehghani, Ehsan & Jabalameli, Mohammad Saeed & Jabbarzadeh, Armin, 2018. "Robust design and optimization of solar photovoltaic supply chain in an uncertain environment," Energy, Elsevier, vol. 142(C), pages 139-156.
    5. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    6. Chia-Nan Wang & Van Tran Hoang Viet & Thanh Phong Ho & Van Thanh Nguyen & Syed Tam Husain, 2020. "Optimal Site Selection for a Solar Power Plant in the Mekong Delta Region of Vietnam," Energies, MDPI, vol. 13(16), pages 1-20, August.
    7. Ibrahim Yilmaz, 2023. "A Hybrid DEA–Fuzzy COPRAS Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    8. Olanrewaju, O.A & Jimoh, A.A, 2014. "Review of energy models to the development of an efficient industrial energy model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 661-671.
    9. Marcochi de Melo, Diego & Lopes, Elaine Coelho & Motta, Juliana Gutierrez & Asano, Roberto & Valverde, María & Suyama, Ricardo & Benedito, Ricardo da Silva & Leite, Patricia Teixeira & Cardoso de Lima, 2021. "Integrated intelligent geoprocessing tool for screening candidate locations suitable for Distributed Generation Deployment," Renewable Energy, Elsevier, vol. 177(C), pages 797-806.
    10. Grigoroudis, Evangelos & Petridis, Konstantinos & Arabatzis, Garyfallos, 2014. "RDEA: A recursive DEA based algorithm for the optimal design of biomass supply chain networks," Renewable Energy, Elsevier, vol. 71(C), pages 113-122.

    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. Azadeh, A. & Ghaderi, S.F. & Maghsoudi, A., 2008. "Location optimization of solar plants by an integrated hierarchical DEA PCA approach," Energy Policy, Elsevier, vol. 36(10), pages 3993-4004, October.
    2. Azadeh, A. & Babazadeh, R. & Asadzadeh, S.M., 2013. "Optimum estimation and forecasting of renewable energy consumption by artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 605-612.
    3. Linares-Rodríguez, Alvaro & Ruiz-Arias, José Antonio & Pozo-Vázquez, David & Tovar-Pescador, Joaquín, 2011. "Generation of synthetic daily global solar radiation data based on ERA-Interim reanalysis and artificial neural networks," Energy, Elsevier, vol. 36(8), pages 5356-5365.
    4. Hejase, Hassan A.N. & Al-Shamisi, Maitha H. & Assi, Ali H., 2014. "Modeling of global horizontal irradiance in the United Arab Emirates with artificial neural networks," Energy, Elsevier, vol. 77(C), pages 542-552.
    5. Soyhan, Hakan S., 2009. "Sustainable energy production and consumption in Turkey: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1350-1360, August.
    6. Melikoglu, Mehmet, 2013. "Vision 2023: Forecasting Turkey's natural gas demand between 2013 and 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 393-400.
    7. Kisi, Ozgur, 2014. "Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach," Energy, Elsevier, vol. 64(C), pages 429-436.
    8. Batman, Alp & Bagriyanik, F. Gul & Aygen, Z. Elif & Gül, Ömer & Bagriyanik, Mustafa, 2012. "A feasibility study of grid-connected photovoltaic systems in Istanbul, Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5678-5686.
    9. Azadeh, A. & Ghaderi, S.F. & Nasrollahi, M.R., 2011. "Location optimization of wind plants in Iran by an integrated hierarchical Data Envelopment Analysis," Renewable Energy, Elsevier, vol. 36(5), pages 1621-1631.
    10. Chia-Nan Wang & Van Thanh Nguyen & Hoang Tuyet Nhi Thai & Duy Hung Duong, 2018. "Multi-Criteria Decision Making (MCDM) Approaches for Solar Power Plant Location Selection in Viet Nam," Energies, MDPI, vol. 11(6), pages 1-27, June.
    11. Nakamoto, Yuya & Eguchi, Shogo, 2024. "How do seasonal and technical factors affect generation efficiency of photovoltaic power plants?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    12. San Cristóbal, José Ramón, 2011. "A multi criteria data envelopment analysis model to evaluate the efficiency of the Renewable Energy technologies," Renewable Energy, Elsevier, vol. 36(10), pages 2742-2746.
    13. Bilgen, Selçuk & Keles, Sedat & Kaygusuz, Abdullah & SarI, Ahmet & Kaygusuz, Kamil, 2008. "Global warming and renewable energy sources for sustainable development: A case study in Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(2), pages 372-396, February.
    14. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Shadman, Foroogh, 2014. "Power industry restructuring and eco-efficiency changes: A new slacks-based model in Malmquist–Luenberger Index measurement," Energy Policy, Elsevier, vol. 68(C), pages 132-145.
    15. Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    16. Aquila, Giancarlo & Souza Rocha, Luiz Célio & Rotela Junior, Paulo & Saab Junior, Joseph Youssif & de Sá Brasil Lima, João & Balestrassi, Pedro Paulo, 2020. "Economic planning of wind farms from a NBI-RSM-DEA multiobjective programming," Renewable Energy, Elsevier, vol. 158(C), pages 628-641.
    17. Mostafavi, Elham Sadat & Ramiyani, Sara Saeidi & Sarvar, Rahim & Moud, Hashem Izadi & Mousavi, Seyyed Mohammad, 2013. "A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran," Energy, Elsevier, vol. 49(C), pages 204-210.
    18. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    19. Yilmaz, Saban & Ozcalik, Hasan Riza & Kesler, Selami & Dincer, Furkan & Yelmen, Bekir, 2015. "The analysis of different PV power systems for the determination of optimal PV panels and system installation—A case study in Kahramanmaras, Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1015-1024.
    20. Yanshuang Zhang & Byung Ho Jeong, 2016. "Development of a Multi-period Output Model for Considering Time Lag Effect," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(03), pages 1-18, June.

    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:renene:v:36:y:2011:i:12:p:3394-3401. 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/renewable-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.