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The largescale penetration of variable renewable energy (VRE) and theirgeneration uncertainties poses a major challenge for the distribution systemoperator (DSO) to efficiently determine the day-ahead real and reactive powerdistribution locational marginal prices (DLMPs) and their underlyingcomponents. In this paper, we propose a DLMP-based transactive day-ahead market(DAM) model, that in addition to energy and losses, determines prices forcreating congestions and voltage violations under peak-load and large-scalestochastic VRE penetration conditions. To account for the VRE uncertainties andthe effect of their large-scale penetration on the DLMP components anddistributed energy resources' (DERs) schedules, we propose a novel data-drivenprobability efficient point (PEP) method that computes the optimal total VREgeneration at different confidence (risk) levels to incorporate in the proposedtransactive DAM model. We perform a wide range of simulation studies on amodified IEEE 69-node system to validate the proposed methods and demonstratethe effect of peak load conditions, large-scale VRE penetration, and inclusionof battery energy storage systems (BESS) on the resulting positive or negativereal and reactive power DLMPs and their components.

Distribution LMP-based Transactive Day-ahead Market with Variable Renewable Generation