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The Impacts of Demand Response on the Efficiency of Energy Markets in the Presence of Wind Farms

  • Neda Hajibandeh
  • Miadreza Shafie-khah
  • Saber Talari
  • João P. S. CatalãoEmail author
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 499)

Abstract

In this paper, an optimal scheduling of thermal and wind power plants is presented by using a stochastic programming approach to cover the uncertainties of the forecasted generation of wind farms. Uncertainties related to wind forecast error, consequently wind generation outage power and also system load demand are modeled through scenario generation. Then, with regard to day-ahead and real-time energy markets and taking into account the relevant constraints, the thermal unit commitment problem is solved considering wind energy injection into the system. Besides, in order to assess impacts of Demand Response (DR) on the problem, a load reduction demand response model has been applied in the base model. In this approach, self and cross elasticity is used for modeling the customers’ behavior modeling. The results indicate that the DR Programs (DRPs) improves the market efficiency especially in peak hours when the thermal Gencos become critical suppliers and the combination of DRPs and wind farm can be so efficient.

Keywords

Demand response Electricity market Stochastic programming Wind production 

Notes

Acknowledgment

This work was supported by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under Projects SAICT-PAC/0004/2015 - POCI-01-0145-FEDER-016434, POCI-01-0145-FEDER-006961, UID/EEA/50014/2013, UID/CEC/50021/2013, and UID/EMS/00151/2013. Also, the research leading to these results has received funding from the EU Seventh Framework Programme FP7/2007-2013 under grant agreement no. 309048.

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Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  • Neda Hajibandeh
    • 1
  • Miadreza Shafie-khah
    • 1
  • Saber Talari
    • 1
  • João P. S. Catalão
    • 1
    • 2
    • 3
    Email author
  1. 1.C-MASTUniversity of Beira InteriorCovilhãPortugal
  2. 2.INESC TEC and the Faculty of Engineering of the University of PortoPortoPortugal
  3. 3.INESC-ID, Instituto Superior TécnicoUniversity of LisbonLisbonPortugal

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