An Analysis for Repowering Prediction of Jamgodarani Wind Farm Using MATLAB

  • Authors

    • Manoj Verma
    • Siraj Ahmed
    2018-08-24
    https://doi.org/10.14419/ijet.v7i3.31.18237
  • Renewable energy, repowering, MATLAB.

  • Abstract

    The development of megawatt class turbines has led to the improvement of wind turbine technology and design. Re-powering in wind energy is a concept to replace and reduce the number of installed old wind turbines of lower capacity by modern turbines of higher capacity. It intends to generate the highest possible constant output power under all wind speed conditions. This research paper portrays economic viewpoints of the repowering procedure for different wind farms. The availability of wind energy in many regions of India encouraged a developing interest in the field of renewable energy and as a consequence this procedure was generated. Before 1998 all the equipments used in relevant research sites were outdated and low powered. But now modern wind turbines with higher efficiency are available to generate more power using considerably reduced infrastructure. This research work proves that repowering is a productive attempt for such old wind farms by using MATLAB (Matrix Laboratory) programming. Wind energy technology is favored due to the benefits of environment friendliness, relativity less installation time and economic competitiveness. A detailed study of necessary performance indices to determine the reliability and performance of a particular wind farm for repowering is done in this research work. An old wind farm located at Jamgodrani Hills, which is in a central part of India, is selected to study the implementation of repowering.   This wind farm was commissioned in 1990 with a capacity of approximately 13.05 MW consisting of 58 wind turbines of 225 kW capacity each.

     

     

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  • How to Cite

    Verma, M., & Ahmed, S. (2018). An Analysis for Repowering Prediction of Jamgodarani Wind Farm Using MATLAB. International Journal of Engineering & Technology, 7(2.31), 255-258. https://doi.org/10.14419/ijet.v7i3.31.18237

    Received date: 2018-08-25

    Accepted date: 2018-08-25

    Published date: 2018-08-24