Heuristic approach for transactive energy management in active distribution systems

Abstract

The advent of distributed energy resources (DERs), which include small conventional and renewable generation units, energy storage, and flexible loads in distribution network needs distributed coordination for effective management. In this paper, a stochastic transactive management framework is proposed to minimize overall cost and avoid network constraints violation at the distribution network level. This framework includes day-ahead scheduling of electric vehicles and air conditioning loads under demand response aggregators (DRAs), and DERs under distributed generation owners (DGOs) into day-ahead wholesale market in a network managed by a distribution network operator (DNO). An agent called distribution independent system operator (DISO) is responsible for coordination among DRAs, DGOs, and DNO. A heuristic step-size update approach is proposed to calculate the Lagrange multiplier iteratively and improve the convergence speed. This framework is modeled as a quadratic constraint programming (QCP) problem and solved using the GAMS solver. Simulation results on a modified 33-bus system with considerable penetration of loads and DERs, shows that the suggested framework can efficiently reduce the iterations to converge and returns an optimal schedule. And demonstrate the effect of network congestion, demand, and generation uncertainties on the resulting objective values of the agents and magnitude of the Lagrange multiplier values.