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Integrating load reduction into wholesale energy market with application to wind power integration

Parvania, M ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1109/JSYST.2011.2162877
  3. Publisher: 2012
  4. Abstract:
  5. Renewable energy resources, notably wind power, are expected to provide considerable portion of the world energy requirements in the near future. Many system operators around the world are challenged by the problems associated with integrating these intermittent resources into the grid. As one of the potential solutions, demand response (DR) is expected to play a major role for mitigating integration issues of intermittent renewable energy resources. In this context, this paper proposes a DR program which helps to integrate wind power by reshaping the load of the system. The DR program provides a framework to procure load reduction from DR resources in the wholesale energy market. The participants in the program submit their offer packages to provide load reduction in the day-ahead energy market. A day-ahead network-constrained market clearing formulation is also proposed which considers the load reduction provided by the DR program participants as an energy market commodity. The proposed method, which is in the mixed-integer linear programming format, determines commitment state of generating units, schedules the energy and spinning reserve provided by generating units, and schedules the load reduction provided by the DR program participants. To reveal the features of the proposed method, several numerical studies are conducted on the IEEE-RTS. The results presented indicate that integrating load reduction in the energy market provides a powerful tool to selectively modify the system load to support wind power integration, while making significant economic and technical benefits for the system
  6. Keywords:
  7. Demand response (DR) ; Energy market ; Renewable energy ; Demand response ; Energy markets ; Load reduction ; Mixed integer linear programming ; Renewable energies ; wind power integration ; wind power variability ; Numerical methods ; Wind power
  8. Source: IEEE Systems Journal ; Volume 6, Issue 1 , 2012 , Pages 35-45 ; 19328184 (ISSN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6003741