Journal
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 28, Issue 6, Pages 2416-2431Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2019.2944328
Keywords
Buildings; Real-time systems; Uncertainty; Scheduling; Prediction algorithms; Batteries; Convex functions; Ancillary services; flexibility; multi-energy systems (MESs); online convex optimization (OCO); time-varying constraints
Funding
- Fonds de recherche du Quebec Nature et technologies
- Ontario Ministry of Research, Innovation and Science
- Natural Sciences and Engineering Research Council of Canada
Ask authors/readers for more resources
In this article, buildings with several sources of flexibility, subject to multiple energy requirements, and having access to different electricity markets are considered. A two-level algorithm for optimizing the building's energy management under uncertainty and limited information is presented in this article. A mixed-integer linear program scheduling level is first used to set an energy management objective for every hour using only averaged data. Then, an online convex optimization (OCO) algorithm is used to track in real time the objective set by the scheduling level. For this purpose, a novel penalty-based OCO algorithm for time-varying constraints is developed. The regret of the algorithm is shown to be sublinearly bounded above. This ensures, at least on average, the feasibility of the decisions made by the algorithm. A case study in which the two-level approach is used on a building located in Melbourne, Australia, is presented. The approach is shown to satisfy all constraints 97.32% of the time while attaining a positive net revenue at the end of the day by providing ancillary services to the power grid.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available