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00925njm 22002777a 4500 dc Ananduta, Wayan Wicak author Ocampo-Martínez, Carlos author Nedic, Angelia author 2020 © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works We propose a distributed method to solve a multi-agent optimization problem with strongly convex cost function and equality coupling constraints. The method is based on Nesterov’s accelerated gradient approach and works over stochastically time-varying communication networks. We consider the standard assumptions of Nesterov’s method and show that the sequence of the expected dual values converge toward the optimal value with the rate of O(1/k²). Furthermore, we provide a simulation study of solving an optimal power flow problem with a well-known benchmark case. Peer Reviewed Postprint (author's final draft) Àrees temàtiques de la UPC::Informàtica Stochastic processes Data transmission systems Multi-agent optimization Distributed method Accelerated gradient method Distributed optimal power flow problem Processos estocàstics Dades -- Transmissió Accelerated Multi-agent optimization method over stochastic networks