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Title: Bi-Level Dynamic Optimization with Feedback

Abstract

This paper considers a bi-level real-time algorithmic framework for networked systems, consisting of several local controllers and a central controller. The central controller issues setpoints to the local controllers to optimize their operational objectives while satisfying system-wide constraints. In this context, the paper develops an online algorithm for tracking the optimal solution of the underlying dynamic optimization problem. The design of the algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements (i.e., feedback). Optimality claims are established in terms of the dynamic regret of the algorithm; the latter is a natural performance criterion in nonstationary environments associated with real-time control problems. Finally, the application of the algorithm to real-time control of power setpoints in an electrical grid is illustrated.

Authors:
 [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1457656
Report Number(s):
NREL/CP-5D00-71825
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 14-16 November 2017, Montreal, Canada
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; heuristic algorithms; optimization; real-time systems; signal processing algorithms; power system dynamics; linear programming; government

Citation Formats

Bernstein, Andrey, and Dall-Anese, Emiliano. Bi-Level Dynamic Optimization with Feedback. United States: N. p., 2018. Web. doi:10.1109/GlobalSIP.2017.8308704.
Bernstein, Andrey, & Dall-Anese, Emiliano. Bi-Level Dynamic Optimization with Feedback. United States. doi:10.1109/GlobalSIP.2017.8308704.
Bernstein, Andrey, and Dall-Anese, Emiliano. Thu . "Bi-Level Dynamic Optimization with Feedback". United States. doi:10.1109/GlobalSIP.2017.8308704.
@article{osti_1457656,
title = {Bi-Level Dynamic Optimization with Feedback},
author = {Bernstein, Andrey and Dall-Anese, Emiliano},
abstractNote = {This paper considers a bi-level real-time algorithmic framework for networked systems, consisting of several local controllers and a central controller. The central controller issues setpoints to the local controllers to optimize their operational objectives while satisfying system-wide constraints. In this context, the paper develops an online algorithm for tracking the optimal solution of the underlying dynamic optimization problem. The design of the algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements (i.e., feedback). Optimality claims are established in terms of the dynamic regret of the algorithm; the latter is a natural performance criterion in nonstationary environments associated with real-time control problems. Finally, the application of the algorithm to real-time control of power setpoints in an electrical grid is illustrated.},
doi = {10.1109/GlobalSIP.2017.8308704},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Mar 08 00:00:00 EST 2018},
month = {Thu Mar 08 00:00:00 EST 2018}
}

Conference:
Other availability
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