Journal of Electrical Engineering and Technology

  • 제7권6호
  • /
  • Pages.852-858
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  • 2012
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  • 1975-0102(pISSN)
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  • 2093-7423(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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Evaluation of the Wind Power Penetration Limit and Wind Energy Penetration in the Mongolian Central Power System

  • Ulam-Orgil, Ch. (Dept. of Electrical Engineering, and Wind Energy Grid-Adaptive Technology Research Center, Chonbuk National University) ;
  • Lee, Hye-Won (Dept. of Electrical Engineering, and Wind Energy Grid-Adaptive Technology Research Center, Chonbuk National University) ;
  • Kang, Yong-Cheol (Dept. of Electrical Engineering, and Wind Energy Grid-Adaptive Technology Research Center and Smart Grid Research Center, Chonbuk National University)
  • 투고 : 2012.05.15
  • 심사 : 2012.09.03
  • 발행 : 2012.11.01
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초록

This paper describes evaluation results of the wind power penetration limit (WPPL) and the wind energy penetration (WEP) in the Mongolian central power system (MCPS). A wind power plant (WPP) in a power system possesses an output power limit because the power system must maintain a balance between the generation and consumption of electricity at all times in order to achieve an adequate level of quality. The instantaneous penetration limit (IPL) of wind generation at a load is determined as the minimum of the three technical constraints: the minimum output, the ramp rate capability, and the spinning reserve of the conventional generating units. In this paper, a WPPL is defined as the maximum IPL divided by the peak load. A maximal variation rate (VR) of wind power is a major factor in determining the IPL, WPPL, and WEP. This paper analyzes the effects of the maximal VR of wind power on the WPPL, WEP, and capacity factor (CF) in the MCPS. The results indicate that a small VR can facilitate a large amount of wind energy while maintaining a high CF with increased wind power penetration.

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참고문헌

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피인용 문헌

  1. Flexibility-Based Evaluation of Variable Generation Acceptability in Korean Power System vol.10, pp.6, 2017, https://doi.org/10.3390/en10060825
  2. Prediction of Wind Power by Chaos and BP Artificial Neural Networks Approach Based on Genetic Algorithm vol.10, pp.1, 2015, https://doi.org/10.5370/JEET.2015.10.1.041
  3. A new wind power prediction method based on chaotic theory and Bernstein Neural Network vol.117, 2016, https://doi.org/10.1016/j.energy.2016.10.041
  4. A source–grid–load coordinated power planning model considering the integration of wind power generation vol.168, 2016, https://doi.org/10.1016/j.apenergy.2016.01.086