Science Journal of Energy Engineering

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A Predictive Numerical Model for Analyzing Performance of Solar Photovoltaic, Geothermal Hybrid System for Electricity Generation and District Heating

Received: 26 September 2016    Accepted: 03 November 2016    Published: 17 February 2017
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Abstract

A simulation and analysis of the energy conversion equations describing the behavior of a hybrid system composed of solar photovoltaic PV, and geothermal subsystems for power generation and district heating are presented in this paper. A numerical model based upon the aforementioned energy conversion equations was developed, coded and results were compared to experimental data. The model is intended to be used as an optimization and design tool for such hybrid systems. The model predicted results compared fairly with experimental data under various conditions.

DOI 10.11648/j.sjee.20170501.12
Published in Science Journal of Energy Engineering (Volume 5, Issue 1, February 2017)
Page(s) 13-30
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Hybrid System, Solar Photovoltaic, Geothermal, Modeling, Simulation, Validation, Experimental Data

References
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Author Information
  • Research Center for Renewable Energy, Catholic University of Cuenca, Cuenca, Ecuador

  • Research Center for Renewable Energy, Catholic University of Cuenca, Cuenca, Ecuador

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  • APA Style

    Samuel Sami, Jorge Rivera. (2017). A Predictive Numerical Model for Analyzing Performance of Solar Photovoltaic, Geothermal Hybrid System for Electricity Generation and District Heating. Science Journal of Energy Engineering, 5(1), 13-30. https://doi.org/10.11648/j.sjee.20170501.12

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    ACS Style

    Samuel Sami; Jorge Rivera. A Predictive Numerical Model for Analyzing Performance of Solar Photovoltaic, Geothermal Hybrid System for Electricity Generation and District Heating. Sci. J. Energy Eng. 2017, 5(1), 13-30. doi: 10.11648/j.sjee.20170501.12

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    AMA Style

    Samuel Sami, Jorge Rivera. A Predictive Numerical Model for Analyzing Performance of Solar Photovoltaic, Geothermal Hybrid System for Electricity Generation and District Heating. Sci J Energy Eng. 2017;5(1):13-30. doi: 10.11648/j.sjee.20170501.12

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  • @article{10.11648/j.sjee.20170501.12,
      author = {Samuel Sami and Jorge Rivera},
      title = {A Predictive Numerical Model for Analyzing Performance of Solar Photovoltaic, Geothermal Hybrid System for Electricity Generation and District Heating},
      journal = {Science Journal of Energy Engineering},
      volume = {5},
      number = {1},
      pages = {13-30},
      doi = {10.11648/j.sjee.20170501.12},
      url = {https://doi.org/10.11648/j.sjee.20170501.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.sjee.20170501.12},
      abstract = {A simulation and analysis of the energy conversion equations describing the behavior of a hybrid system composed of solar photovoltaic PV, and geothermal subsystems for power generation and district heating are presented in this paper. A numerical model based upon the aforementioned energy conversion equations was developed, coded and results were compared to experimental data. The model is intended to be used as an optimization and design tool for such hybrid systems. The model predicted results compared fairly with experimental data under various conditions.},
     year = {2017}
    }
    

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    AB  - A simulation and analysis of the energy conversion equations describing the behavior of a hybrid system composed of solar photovoltaic PV, and geothermal subsystems for power generation and district heating are presented in this paper. A numerical model based upon the aforementioned energy conversion equations was developed, coded and results were compared to experimental data. The model is intended to be used as an optimization and design tool for such hybrid systems. The model predicted results compared fairly with experimental data under various conditions.
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