Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

Priyank Srivastava; Guido Cavraro; Jorge Cortes

doi:10.1109/LCSYS.2021.3135510

Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

Priyank Srivastava, Guido Cavraro, Jorge Cortes

Power Systems Engineering

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

Abstract

This letter proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions that combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination requirements. Each agent has information on its local cost and coordinates with the network supervisor for information about the coupling term of the cost. The proposed approach is feedback-based and asynchronous by design, guarantees anytime feasibility, and ensures the asymptotic convergence of the network state to the desired optimizer. Numerical simulations on a power system example illustrate our results.

Original language	American English
Pages (from-to)	1970-1975
Number of pages	6
Journal	IEEE Control Systems Letters
Volume	6
DOIs	https://doi.org/10.1109/LCSYS.2021.3135510 https://doi.org/10.1109/LCSYS.2021.3135510
State	Published - 2022

Bibliographical note

Publisher Copyright:
2475-1456 © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

NREL Publication Number

NREL/JA-5D00-81599

Keywords

Convergence
Costs
Couplings
Government
Heuristic algorithms
Linear programming
Power system dynamics

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abstract = "This letter proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions that combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination requirements. Each agent has information on its local cost and coordinates with the network supervisor for information about the coupling term of the cost. The proposed approach is feedback-based and asynchronous by design, guarantees anytime feasibility, and ensures the asymptotic convergence of the network state to the desired optimizer. Numerical simulations on a power system example illustrate our results.",

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Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

Abstract

Bibliographical note

NREL Publication Number

Keywords

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