Distribution grid feasibility in near real-time markets: A comparative analysis of power flow models

The rapid decentralization of power systems has driven a paradigm shift, with Distribution System Operators (DSOs) actively managing distribution grids to address challenges posed by the high penetration of Distributed Energy Resources (DERs). Activation of DERs in external electricity markets by third-party actors can potentially violate distribution grid operational constraints. To prevent this, it is essential to incorporate the grid’s feasible region, representing its operational limits defined by the AC power flow model, into market clearing processes. Nonetheless, despite being exact, this model generates a nonlinear and non-convex feasible region for the market, making the problem challenging to solve and unsuitable for near real-time applications. Toward this direction, this work investigates the applicability of two linear, approximate power flow models designed to overcome the non-convexities of the exact model in near real-time market operations. Specifically, the performance of the approximate models is compared to the exact model in terms of aggregate flexibility, solution feasibility, and computational complexity. Simulation results from a case study using three different test feeders show that the approximate models have significantly lower computational complexity. However, their performance in aggregate flexibility and solution feasibility is highly influenced by the grid’s size and operating state.