@article{34613,
  keywords = {demand response, Offering strategy, Wind power producer, Information gap decision theory, Day-ahead market},
  author = {Xuemei Dai and Yaping Li and Kaifeng Zhang and Wei Feng},
  title = {A robust offering strategy for wind producers considering uncertainties of demand response and wind power},
  abstract = {<p>This paper proposes a risk-constrained decision-making approach for a wind power producer participating in the day-ahead market. In the developed model, a flexible demand response trading scheme between the wind power producer and different customers is employed. Through the proposed demand response mechanism, the wind power producer is able to trade demand response resource internally with different customers, and then trade energy externally with the market to increase the expected profit and the wind energy utilization. The uncertainties in the wind power and demand response are modeled by using the information gap decision theory approach from risk averse (robust) and risk-seeking (opportunistic) perspectives. The objective of the robust model is to maximize the robust level while satisfying the desired profit, whereas the opportunistic model aims to evaluate the possibility of achieving windfall profits with favorable uncertainties. The overall offering strategy problem is modeled as a bi-objective mixed integer nonlinear programming, which is linearized by proper techniques and solved efficiently by using the normal boundary intersection technique. Simulation results show that utilizing demand response resource to mitigate wind power deviations can increase a wind power producer’s profit and reduce potential risks. In addition, the results demonstrate that the proposed bi-objective optimization approach enables the wind power producer to select appropriate offering decisions with respect to uncertainties.</p>},
  year = {2020},
  journal = {Applied Energy},
  volume = {279},
  pages = {115742},
  month = {01/2020},
  issn = {03062619},
  doi = {10.1016/j.apenergy.2020.115742},
  language = {eng},
}