ADMM-based Distributed OPF Problem Meets Stochastic Communication Delay

Jiangjiao Xu; Hongjian Sun; Christopher Dent

doi:10.1109/TSG.2018.2873650

ADMM-based Distributed OPF Problem Meets Stochastic Communication Delay

Jiangjiao Xu, Hongjian Sun, Christopher Dent

School of Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

An increasing number of distributed generators (DGs) will penetrate into the distribution power system in future smart grid, thus a centralized control strategy cannot effectively optimize the power loss problem in real-time. This paper examines the idea of a fully distributed Optimal Power Flow (OPF) approach, based on the alternating direction multiplier method (ADMM), to optimize the power loss. The objectives are not only to effectively obtain the minimization of power loss, but also to analyze the effect of communication time-delay on optimization performance. Both synchronous and asynchronous iterative algorithms are proposed to solve the OPF problem. In addition, four
different strategies are proposed to improve convergence speed when delay occurs. The proposed weighted autoregressive (AR) strategy can reduce the fluctuation effectively. In comparison with synchronous algorithm, simulation results show that the asynchronous algorithm has a better optimization result.

Original language	English
Pages (from-to)	5046-5056
Number of pages	11
Journal	IEEE Transactions on Smart Grid
Volume	10
Issue number	5
Early online date	3 Oct 2018
DOIs	https://doi.org/10.1109/TSG.2018.2873650
Publication status	Published - 30 Sep 2019

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title = "ADMM-based Distributed OPF Problem Meets Stochastic Communication Delay",

abstract = "An increasing number of distributed generators (DGs) will penetrate into the distribution power system in future smart grid, thus a centralized control strategy cannot effectively optimize the power loss problem in real-time. This paper examines the idea of a fully distributed Optimal Power Flow (OPF) approach, based on the alternating direction multiplier method (ADMM), to optimize the power loss. The objectives are not only to effectively obtain the minimization of power loss, but also to analyze the effect of communication time-delay on optimization performance. Both synchronous and asynchronous iterative algorithms are proposed to solve the OPF problem. In addition, fourdifferent strategies are proposed to improve convergence speed when delay occurs. The proposed weighted autoregressive (AR) strategy can reduce the fluctuation effectively. In comparison with synchronous algorithm, simulation results show that the asynchronous algorithm has a better optimization result.",

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N2 - An increasing number of distributed generators (DGs) will penetrate into the distribution power system in future smart grid, thus a centralized control strategy cannot effectively optimize the power loss problem in real-time. This paper examines the idea of a fully distributed Optimal Power Flow (OPF) approach, based on the alternating direction multiplier method (ADMM), to optimize the power loss. The objectives are not only to effectively obtain the minimization of power loss, but also to analyze the effect of communication time-delay on optimization performance. Both synchronous and asynchronous iterative algorithms are proposed to solve the OPF problem. In addition, fourdifferent strategies are proposed to improve convergence speed when delay occurs. The proposed weighted autoregressive (AR) strategy can reduce the fluctuation effectively. In comparison with synchronous algorithm, simulation results show that the asynchronous algorithm has a better optimization result.

AB - An increasing number of distributed generators (DGs) will penetrate into the distribution power system in future smart grid, thus a centralized control strategy cannot effectively optimize the power loss problem in real-time. This paper examines the idea of a fully distributed Optimal Power Flow (OPF) approach, based on the alternating direction multiplier method (ADMM), to optimize the power loss. The objectives are not only to effectively obtain the minimization of power loss, but also to analyze the effect of communication time-delay on optimization performance. Both synchronous and asynchronous iterative algorithms are proposed to solve the OPF problem. In addition, fourdifferent strategies are proposed to improve convergence speed when delay occurs. The proposed weighted autoregressive (AR) strategy can reduce the fluctuation effectively. In comparison with synchronous algorithm, simulation results show that the asynchronous algorithm has a better optimization result.

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JO - IEEE Transactions on Smart Grid

JF - IEEE Transactions on Smart Grid

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ADMM-based Distributed OPF Problem Meets Stochastic Communication Delay

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