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Short-Term and Medium-Term Reliability Evaluation for Power Systems With High Penetration of Wind Power

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Authors:
  • Ding, Yi ;
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    Department of Electrical Engineering, Technical University of Denmark
  • Singh, Chanan ;
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    Texas A&M University
  • Goel, Lalit ;
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    Nanyang Technological University
  • Østergaard, Jacob ;
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    Orcid logo0000-0002-9416-2857
    Department of Electrical Engineering, Technical University of Denmark
  • Wang, Peng
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    Nanyang Technological University
DOI:
10.1109/TSTE.2014.2313017
Abstract:
The expanding share of the fluctuating and less predictable wind power generation can introduce complexities in power system reliability evaluation and management. This entails a need for the system operator to assess the system status more accurately for securing real-time balancing. The existing reliability evaluation techniques for power systems are well developed. These techniques are more focused on steady-state (time-independent) reliability evaluation and have been successfully applied in power system planning and expansion. In the operational phase, however, they may be too rough an approximation of the time-varying behavior of power systems with high penetration of wind power. This paper proposes a time-varying reliability assessment technique. Time-varying reliability models for wind farms, conventional generating units, and rapid start-up generating units are developed and represented as the corresponding universal generating functions (UGFs), respectively. A multistate model for a hybrid generation and reserve provider is also proposed based on the developed UGF representations of wind farms, conventional generating units, and rapid start-up generating units. The proposed technique provides a useful tool for the system operator to evaluate the reliability and arrange reserve for maintaining secure system operation in the short- as well as medium-terms.
Type:
Journal article
Language:
English
Published in:
Ieee Transactions on Sustainable Energy, 2014, Vol 5, Issue 3, p. 896-906
Keywords:
Power, Energy and Industry Applications; Markov processes; Medium-term; Power system reliability; random process; reliability; short-term; universal generating function (UGF); Wind farms; wind power; Wind power generation; Wind speed
Main Research Area:
Science/technology
Publication Status:
Published
Review type:
Peer Review
Submission year:
2014
Scientific Level:
Scientific
ID:
268467764

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