Robust optimal portfolio configuration of Renewable-based Virtual Power Plants for long-term planning

Abstract

This paper proposes a robust optimal algorithm to determine the best portfolio configuration of Renewable-based Virtual Power Plants (RVPPs) over medium to long-term horizons. In this work, modifications to state-of-the-art robust formulations for short-term RVPP operation are proposed, addressing a broader simulation horizon and supporting the decision-making behind RVPP configuration. The algorithm accounts for the different uncertainties that characterize the problem, which include those linked to renewable generation such as hourly solar and wind maximum productions, as well as electricity market prices. The advantages of resource coordination within an RVPP are demonstrated in the case study, highlighting the advantage of flexible RVPP configurations over fixed portfolios.

This paper proposes a robust optimal algorithm to determine the best portfolio configuration of Renewable-based Virtual Power Plants (RVPPs) over medium to long-term horizons. In this work, modifications to state-of-the-art robust formulations for short-term RVPP operation are proposed, addressing a broader simulation horizon and supporting the decision-making behind RVPP configuration. The algorithm accounts for the different uncertainties that characterize the problem, which include those linked to renewable generation such as hourly solar and wind maximum productions, as well as electricity market prices. The advantages of resource coordination within an RVPP are demonstrated in the case study, highlighting the advantage of flexible RVPP configurations over fixed portfolios.