Summary:
In this paper, a novel approach to define the optimal bidding of Renewable-only Virtual Power Plants (RVPPs) in the day-ahead, secondary reserve, and intra-day markets is proposed. To this aim, a robust optimization algorithm is developed to account for the asymmetric nature of the uncertainties that characterize the market prices, as well as the energy production of the RVPP stochastic sources and flexible demand consumption. Simulation results show increased RVPP benefits compared to other existing solutions and demonstrate the potential of renewable sources to further increase their economic competitiveness. The simplicity of the implementation, the computational efficiency, and the flexible robustness are also verified.
Spanish layman's summary:
Este artículo propone un enfoque novedoso para definir la oferta óptima de las Centrales Virtuales de Energía compuestas únicamente por fuentes renovables (RVPP, por sus siglas en inglés) en los mercados secuenciales de energía y reservas. Se desarrolla un algoritmo de optimización robusta que considera la naturaleza asimétrica de las diferentes incertidumbres relacionadas con los precios del mercado, la producción de energía y el consumo de demanda.
English layman's summary:
This paper proposes a novel approach to define the optimal bidding of Renewable-only Virtual Power Plants (RVPPs) in the sequential energy and reserve markets. A robust optimization algorithm is developed to account for the asymmetric nature of the different uncertainties related to market prices, energy production, and demand consumption.
Keywords: Energy markets; renewable-only virtual power plant; reserve markets; robust optimization; stochastic sources
JCR-JIF Impact Factor and WoS quartile: 5,700 - Q1 (2025)
DOI reference:
https://doi.org/10.1016/j.segan.2025.101801
Published on paper: September 2025.
Published on-line: July 2025.
Citation:
H. Nemati, P. Sánchez, A. Ortega, L. Sigrist, E. Lobato, L. Rouco, "Flexible robust optimal bidding of renewable virtual power plants in sequential markets under asymmetric uncertainties", Sustainable Energy, Grids and Networks, Vol. 43, pp. 101801, September 2025. [Online: July 2025] doi: 10.1016/j.segan.2025.101801