IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v87y2010i6p1911-1918.html
   My bibliography  Save this article

Optimal placement and sizing from standpoint of the investor of Photovoltaics Grid-Connected Systems using Binary Particle Swarm Optimization

Author

Listed:
  • Gómez, M.
  • López, A.
  • Jurado, F.

Abstract

This paper introduces a Binary Particle Swarm Optimization based method to accomplish optimal location and size of a Photovoltaics Grid-Connected System (PVGCS) for distributed power generation. The main technical constraint is the maximum installed peak power, which is limited for utilities Power Distributor Company. The fitness function to be optimized is the profitability index. A fair comparison between the proposed algorithm and other methods is performed. For such goal, convergence curves of the average profitability index versus number of iterations are computed. The proposed algorithm reaches a better solution than genetic algorithms when considering similar computational cost (similar number of evaluations).

Suggested Citation

  • Gómez, M. & López, A. & Jurado, F., 2010. "Optimal placement and sizing from standpoint of the investor of Photovoltaics Grid-Connected Systems using Binary Particle Swarm Optimization," Applied Energy, Elsevier, vol. 87(6), pages 1911-1918, June.
    • Handle: RePEc:eee:appene:v:87:y:2010:i:6:p:1911-1918
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(10)00003-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Mellit, A. & Kalogirou, S.A. & Hontoria, L. & Shaari, S., 2009. "Artificial intelligence techniques for sizing photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(2), pages 406-419, February.
    2. Mondol, Jayanta Deb & Yohanis, Yigzaw G. & Norton, Brian, 2007. "The impact of array inclination and orientation on the performance of a grid-connected photovoltaic system," Renewable Energy, Elsevier, vol. 32(1), pages 118-140.
    3. Arán Carrión, J. & Espín Estrella, A. & Aznar Dols, F. & Zamorano Toro, M. & Rodríguez, M. & Ramos Ridao, A., 2008. "Environmental decision-support systems for evaluating the carrying capacity of land areas: Optimal site selection for grid-connected photovoltaic power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(9), pages 2358-2380, December.
    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. Sommerfeldt, Nelson & Madani, Hatef, 2017. "Revisiting the techno-economic analysis process for building-mounted, grid-connected solar photovoltaic systems: Part one – Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1379-1393.
    2. Kucuksari, Sadik & Khaleghi, Amirreza M. & Hamidi, Maryam & Zhang, Ye & Szidarovszky, Ferenc & Bayraksan, Guzin & Son, Young-Jun, 2014. "An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments," Applied Energy, Elsevier, vol. 113(C), pages 1601-1613.
    3. Yu, Shiwei & Wei, Yi-Ming & Fan, Jingli & Zhang, Xian & Wang, Ke, 2012. "Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization," Applied Energy, Elsevier, vol. 92(C), pages 552-562.
    4. Askarzadeh, Alireza & Rezazadeh, Alireza, 2013. "Artificial bee swarm optimization algorithm for parameters identification of solar cell models," Applied Energy, Elsevier, vol. 102(C), pages 943-949.
    5. Fu, Xueqian & Chen, Haoyong & Cai, Runqing & Yang, Ping, 2015. "Optimal allocation and adaptive VAR control of PV-DG in distribution networks," Applied Energy, Elsevier, vol. 137(C), pages 173-182.
    6. Ullah, Hayat & Kamal, Ijlal & Ali, Ayesha & Arshad, Naveed, 2018. "Investor focused placement and sizing of photovoltaic grid-connected systems in Pakistan," Renewable Energy, Elsevier, vol. 121(C), pages 460-473.
    7. Jung, Seunghoon & Jeoung, Jaewon & Kang, Hyuna & Hong, Taehoon, 2021. "Optimal planning of a rooftop PV system using GIS-based reinforcement learning," Applied Energy, Elsevier, vol. 298(C).
    8. Wu, Xiaomei & Feng, Qijin & Bai, Chenchen & Lai, Chun Sing & Jia, Youwei & Lai, Loi Lei, 2021. "A novel fast-charging stations locational planning model for electric bus transit system," Energy, Elsevier, vol. 224(C).

    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. Pérez-Alonso, J. & Pérez-García, M. & Pasamontes-Romera, M. & Callejón-Ferre, A.J., 2012. "Performance analysis and neural modelling of a greenhouse integrated photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4675-4685.
    2. Kornelakis, Aris & Marinakis, Yannis, 2010. "Contribution for optimal sizing of grid-connected PV-systems using PSO," Renewable Energy, Elsevier, vol. 35(6), pages 1333-1341.
    3. Perez-Gallardo, J.R. & Azzaro-Pantel, C. & Astier, S. & Domenech, S. & Aguilar-Lasserre, A., 2014. "Ecodesign of photovoltaic grid-connected systems," Renewable Energy, Elsevier, vol. 64(C), pages 82-97.
    4. Wang, H.X. & Muñoz-García, M.A. & Moreda, G.P. & Alonso-García, M.C., 2018. "Optimum inverter sizing of grid-connected photovoltaic systems based on energetic and economic considerations," Renewable Energy, Elsevier, vol. 118(C), pages 709-717.
    5. Finn, Thomas & McKenzie, Paul, 2020. "A high-resolution suitability index for solar farm location in complex landscapes," Renewable Energy, Elsevier, vol. 158(C), pages 520-533.
    6. Jani, D.B. & Mishra, Manish & Sahoo, P.K., 2017. "Application of artificial neural network for predicting performance of solid desiccant cooling systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 352-366.
    7. Toledo, Olga Moraes & Oliveira Filho, Delly & Diniz, Antônia Sônia Alves Cardoso, 2010. "Distributed photovoltaic generation and energy storage systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 506-511, January.
    8. Hou, Yali & Wang, Qunwei & Tan, Tao, 2023. "An ensemble learning framework for rooftop photovoltaic project site selection," Energy, Elsevier, vol. 285(C).
    9. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    10. Zarzo, Manuel & Martí, Pau, 2011. "Modeling the variability of solar radiation data among weather stations by means of principal components analysis," Applied Energy, Elsevier, vol. 88(8), pages 2775-2784, August.
    11. Rawat, Rahul & Kaushik, S.C. & Lamba, Ravita, 2016. "A review on modeling, design methodology and size optimization of photovoltaic based water pumping, standalone and grid connected system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1506-1519.
    12. Sueyoshi, Toshiyuki & Goto, Mika, 2017. "Measurement of returns to scale on large photovoltaic power stations in the United States and Germany," Energy Economics, Elsevier, vol. 64(C), pages 306-320.
    13. Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 433-446, June.
    14. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Photovoltaic power stations in Germany and the United States: A comparative study by data envelopment analysis," Energy Economics, Elsevier, vol. 42(C), pages 271-288.
    15. Defne, Zafer & Haas, Kevin A. & Fritz, Hermann M., 2011. "GIS based multi-criteria assessment of tidal stream power potential: A case study for Georgia, USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2310-2321, June.
    16. Kashyap, Yashwant & Bansal, Ankit & Sao, Anil K., 2015. "Solar radiation forecasting with multiple parameters neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 825-835.
    17. Aronescu, A. & Appelbaum, J., 2017. "Design optimization of photovoltaic solar fields-insight and methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 882-893.
    18. Calvert, K. & Pearce, J.M. & Mabee, W.E., 2013. "Toward renewable energy geo-information infrastructures: Applications of GIScience and remote sensing that build institutional capacity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 416-429.
    19. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    20. Sánchez-Lozano, J.M. & García-Cascales, M.S. & Lamata, M.T., 2014. "Identification and selection of potential sites for onshore wind farms development in Region of Murcia, Spain," Energy, Elsevier, vol. 73(C), pages 311-324.

    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:87:y:2010:i:6:p:1911-1918. 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.