Distribution locational marginal price-based transactive day-ahead market with variable renewable generation

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