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Distributed optimization for energy resource coordination

Published on:

25 September 2023

Primary Category:

Optimization and Control

Paper Authors:

Xin Cai,

Feng Xiao,

Bo Wei,

Aiping Wang


Key Details

Proposes continuous-time distributed algorithm for optimizing networked systems

Agents optimize local objectives relying on local and shared aggregate data

Dynamic consensus estimator tracks aggregate network information

Event-triggered communication reduces network loads

Exponential convergence to global optima proven

AI generated summary

Distributed optimization for energy resource coordination

This paper proposes a distributed optimization algorithm that allows networked energy resources to coordinate their power generation while minimizing total cost. The algorithm enables each resource to optimize its local objective, which depends on its own generation and the total network generation. This avoids sharing private cost information. Convergence to global optima is proven using singular perturbation theory.

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