Distributed Optimization Design of Multi-Agent Systems With Packet Losses

Chen, Shenghuan; Lan, Weiyao; Ma, Ji; Yu, Xiao

doi:10.1109/icca51439.2020.9264572

Cited by 1 publication

(2 citation statements)

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“…Communications between the agents may occasionally fail entirely for multiple iterations. For instance, communication transmission collisions or instability of the communication link can cause packet loss preventing the agents from sharing data [16], [17]. To model communication loss, we consider an exponential failure distribution with a constant failure rate.…”

Section: Intermittent Communication Lossmentioning

confidence: 99%

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Assessing the Impacts of Nonideal Communications on Distributed Optimal Power Flow Algorithms

Alkhraijah¹,

Menendez²,

Molzahn³

2021

Preprint

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Power system operators are increasingly looking toward distributed optimization to address various challenges facing electric power systems. To assess their capabilities in environments with nonideal communications, this paper investigates the impacts of data quality on the performance of distributed optimization algorithms. Specifically, this paper compares the performance of the Alternating Direction Method of Multipliers (ADMM), Analytic Target Cascading (ATC), and Auxiliary Principal Problem (APP) algorithms in the context of DC Optimal Power Flow (DC OPF) problems. Using several test cases, this paper characterizes the performance of these algorithms in terms of their convergence rates and solution quality under three data quality nonidealities: (1) additive Gaussian noise, (2) false data, and (3) intermittent communication failure.

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Section: Intermittent Communication Lossmentioning

confidence: 99%

“…Packet loss is another communication issue that has been discussed in the literature. The impact of packet loss on unconstrained convex distributed optimization is investigated in [16]. A relaxed ADMM algorithm is proposed in [17] to optimize integrated electrical and heating systems considering communication packet loss.…”

Section: Introductionmentioning

confidence: 99%