Optimal bidding of a group of wind farms in day-ahead markets through an external agent

V. Guerrero-Mestre, A.A. Sanchez de la Nieta, J. Contreras, J.P.S. Catalao

Research output: Contribution to journalArticleAcademicpeer-review

52 Citations (Scopus)


In deregulated electricity markets, producers offer their energy to the day-ahead market. As the subsidies for renewable producers are becoming lower and lower, they have to adapt to market prices. This paper models the energy trading in the day-ahead market for wind power producers. Different strategies are proposed for this purpose: 1) several wind farms offering their energy separately to the day-ahead market; 2) the same strategy as in 1) but compensating the imbalance among different wind farms; and 3) a joint offer involving several wind farms through an external agent in order to minimize the imbalances between the offer and the final power generation. The strategies are modeled with stochastic mixed integer linear programming and Conditional Value at Risk is used to consider the risk assessment. The expected profit including risk aversion is maximized for each wind power producer and for the set of wind power producers in the case of a joint offer. A comparison of the different cases is described in detail in a case study and relevant conclusions are provided.

Original languageEnglish
Article number7276961
Pages (from-to)2688-2700
Number of pages13
JournalIEEE Transactions on Power Systems
Issue number4
Publication statusPublished - 1 Jul 2016
Externally publishedYes


  • Conditional Value at Risk (CVaR)
  • day-ahead market
  • energy trading
  • external agent
  • imbalances
  • stochastic mixed integer linear programming
  • wind power


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