  Virtual power plant (VPP) provides a flexible solution to distributed energy
resources integration by aggregating renewable generation units, conventional
power plants, energy storages, and flexible demands. This paper proposes a
novel model for determining the optimal offering strategy in the day-ahead
energy-reserve market and the optimal self-scheduling plan. It considers
exogenous uncertainties (or called decision-independent uncertainties, DIUs)
associated with market clearing prices and available wind power generation, as
well as the endogenous uncertainties (or called decision-dependent
uncertainties, DDUs) pertaining to real-time reserve deployment requests. A
tractable solution method based on strong duality theory, McCormick relaxation,
and the Benders' decomposition to solve the proposed stochastic adaptive robust
optimization with DDUs formulation is developed. Simulation results demonstrate
the applicability of the proposed approach.
