Energy and Reserve Scheduling of Distribution Network in Presence of Electric Vehicle Aggregators: A Decentralized Approach

Abstract

Bilateral energy transactions between electric vehicles (EVs) and the power grid are managed by entities called aggregators (AGGs) who work as private or network operator’s agents. The remarkable effects of the AGG’s behavior on network parameters entail the provision of coordinated schedules and consideration of network conditions and constraints. In this paper, a novel approach is presented for independent coordinated scheduling of EV charge/discharge via private AGGs, distributed generators (DGs), and the distribution network operator (DSO). The goal is the maximization of AGG profit from energy transactions along with the least network operation costs and improvement of network indices. The objective function of the proposed approach also includes AGG capability to provide the network with spinning reserve which brings incentive payments. For realistic addressing of the problem, the uncertainties related to EV arrival/departure times and their initial State of Charge (SOC) are simulated via different scenarios. The problem is solved using the fast alternating direction method of multipliers (FADMMs) which is well suited for independent-objective optimizations with a fast convergence rate. The proposed distributed algorithm is tested and evaluated on a standard distribution network consisting of AGG and DGs. The results indicate that ignoring network conditions and constraints leads to impractical decisions whereas consideration of DSO requirements by the distributed algorithm will deliver a profitable schedule for AGGs while protecting their privacy and fulfilling DSO’s economical and technical objectives.