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Toward a comprehensive model of large-scale dfig-based wind farms in adequacy assessment of power systems

Ghaedi, A ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/TSTE.2013.2272947
  3. Abstract:
  4. With the current focus on energy and environment, efficient integration of renewable energies, especially wind energy into power systems, is becoming essential. Furthermore, to fully capture wind potentials and to recognize the unique characteristics associated with wind energy in power systems adequacy analysis, a profound inquiry is required. In this way, this paper tries to establish a comprehensive analytical approach for reliability modeling of doubly-fed induction generator (DFIG)-based wind farms. First, the most impressive components of wind turbines are introduced. It then continues with integrating developed state space model of wind turbines and their production uncertainties, thereby allowing a wind farm to be represented as a multistate model in analytical studies. To this end, a well-known clustering method, fuzzy c-means clustering, is employed to find the optimal states. The model priorities are then put under investigation via two various case studies, the RBTS and the IEEE-RTS. A wind farm in the northern region of Iran with its historical data is utilized to validate the main features of the proposed analytical model more efficiently. The adequacy studies at Hierarchical Level one (HLI) of the modified test systems are presented and general conclusions are then drawn
  5. Keywords:
  6. Adequacy assessment ; Doubly-fed induction generator (DFIG) ; Multistate model ; Wind speed intermittency ; Energy and environment ; Fuzzy C means clustering ; Integration of renewable energies ; Intermittency ; Multi-state model ; Production uncertainty ; Electric utilities ; State space methods ; Wind turbines ; Wind power
  7. Source: IEEE Transactions on Sustainable Energy ; Vol. 5, issue. 1 , 2014 , p. 55-63 ; ISSN: 19493029
  8. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6576915