Flexible Robust Optimal Bidding of Renewable Virtual Power Plants in Sequential Markets

TL;DR

This paper introduces a robust optimization method for renewable virtual power plants to optimize bidding across multiple markets, enhancing economic benefits and operational flexibility.

Contribution

It presents a novel robust optimization framework for RVPP bidding in multiple markets, considering asymmetric uncertainties in prices, production, and demand.

Findings

Increased economic benefits for RVPPs compared to existing methods.

Demonstrated computational efficiency and implementation simplicity.

Showed potential for renewable sources to improve competitiveness.

Abstract

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.