Resumen:
This paper proposes a novel approach for the offering strategy of a virtual power plant that participates in the day-ahead and the real-time energy markets. The virtual power plant comprises a conventional power plant, a wind-power unit, a storage facility, and flexible demands, which participate in the day-ahead and the real-time markets as a single entity in order to optimize their energy resources. We model the uncertainty in the wind-power production and in the market prices using confidence bounds and scenarios, respectively, which allows us to formul-ate the strategic offering problem as a stochastic adaptive robust optimization model. Results of a case study are provided to show the applicability of the proposed approach.
Palabras Clave: Robust optimization, stochastic programming, strategic offering, uncertainty, virtual power plant.
Índice de impacto JCR y cuartil WoS: 5,255 - Q1 (2017); 6,500 - Q1 (2023)
Referencia DOI:
https://doi.org/10.1109/TPWRS.2016.2633546
Publicado en papel: Septiembre 2017.
Publicado on-line: Diciembre 2016.
Cita:
A. Baringo, L. Baringo, A stochastic adaptive robust optimization approach for the offering strategy of a virtual power plant. IEEE Transactions on Power Systems. Vol. 32, nº. 5, pp. 3492 - 3504, Septiembre 2017. [Online: Diciembre 2016]
