DLMP calculation and congestion minimization with EV aggregator loading in a distribution network using bilevel program

Abstract

This article develops a distributional locational marginal pricing (DLMP) based electric vehicle (EV) aggregator scheduling framework minimizing the congestion in the network. The article has two parts: 1) calculation of DLMPs by solving actual DistFlow equations; and 2) EV aggregator scheduling in a distribution network formulated as a bilevel problem considering EV aggregator as a leader and distribution system operator (DSO) as a follower. The upper level problem is the cost minimization of EV aggregator, whereas the lower level problem is the social welfare maximization of DSO while satisfying the network constraints. The nonlinear bilevel problem is reformulated into the single-level problem using Karush�Kuhn�Tucker conditions and duality theorem. The framework considers the uncertainty of the EV aggregator by using robust programming and tested with the 15-bus radial distribution network for congested and uncongested cases.