Strategic management of forecast uncertainties to mitigate power imbalances in virtual power plants

A Virtual Power Plant (VPP) model for optimising participation in single energy markets among different groups of power plants. An integrated architecture and nodal-based aggregation approach for analysis of a set of generation, load and storage unit models are presented in this research paper. The interactions with market participants and the associated communication patterns for day-ahead and intraday markets are defined. The forecast uncertainties of renewable energy generation are dealt with by an imbalance compensation algorithm and introduced to a three-stage multi-period optimization process. Operational constraints are properly handled through optimization problem formulation as a constrained mixed integer linear programming (MILP) problem. The model is validated through simulation studies to show how it can reduce power dynamics and improve operational effectiveness. Results indicate that control and the optimization of online bidding are essential to increase the dependability and cost efficiency of the VPP.