Abstract
In this paper, we formulate the distributed optimization of multi-building energy systems as a cost minimization problem with spatially and temporally coupled constraints. The problem is divided into subproblems of each building at each time slot via Lagrangian dual decomposition. The strong duality of the primal and dual problem is proved, and distributed algorithms are proposed based on the subgradient projection method to converge to the global optimum. Specifically, the local temperature control signals are designed for handling the temporally coupled constraints of each building, while an information sharing platform is designed to update and broadcast the congestion price to autonomous buildings to handle the spatially coupled constraints. Numerical results are provided to illustrate the convergence and effectiveness of the proposed method.
Original language | English |
---|---|
Title of host publication | 2017 American Control Conference, ACC 2017 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 2913-2918 |
Number of pages | 6 |
ISBN (Electronic) | 9781509059928 |
ISBN (Print) | 9781509045839 |
DOIs | |
Publication status | Published - 29 Jun 2017 |
Externally published | Yes |
Event | 2017 American Control Conference, ACC 2017 - Seattle, United States Duration: 24 May 2017 → 26 May 2017 |
Publication series
Name | Proceedings of the American Control Conference |
---|---|
Publisher | Institute of Electrical and Electronics Engineers |
ISSN (Print) | 0743-1619 |
ISSN (Electronic) | 2378-5861 |
Conference
Conference | 2017 American Control Conference, ACC 2017 |
---|---|
Country/Territory | United States |
City | Seattle |
Period | 24/05/17 → 26/05/17 |
Bibliographical note
Publisher Copyright:© 2017 American Automatic Control Council (AACC).
Keywords
- building energy control
- coupled constraints
- Distributed optimization
- multi-building systems