  The largescale penetration of variable renewable energy (VRE) and their
generation uncertainties poses a major challenge for the distribution system
operator (DSO) to efficiently determine the day-ahead real and reactive power
distribution locational marginal prices (DLMPs) and their underlying
components. In this paper, we propose a DLMP-based transactive day-ahead market
(DAM) model, that in addition to energy and losses, determines prices for
creating congestions and voltage violations under peak-load and large-scale
stochastic VRE penetration conditions. To account for the VRE uncertainties and
the effect of their large-scale penetration on the DLMP components and
distributed energy resources' (DERs) schedules, we propose a novel data-driven
probability efficient point (PEP) method that computes the optimal total VRE
generation at different confidence (risk) levels to incorporate in the proposed
transactive DAM model. We perform a wide range of simulation studies on a
modified IEEE 69-node system to validate the proposed methods and demonstrate
the effect of peak load conditions, large-scale VRE penetration, and inclusion
of battery energy storage systems (BESS) on the resulting positive or negative
real and reactive power DLMPs and their components.
