Abstract
This paper investigates the use of a collection of dispatchable heating, ventilation and air conditioning (HVAC) loads to absorb the slow (low-frequency) fluctuations in solar photovoltaic (PV) generation. We first formulate the building's thermal dynamics and the associated optimization problem. An optimization formulation is then designed based on traditional model predictive control algorithm, which provides the baseline performance. We then develop an augmented optimal control strategy to improve the solar tracking performance. To guarantee quality of service, in a fleet of residential/commercial buildings, a quadratic optimization problem is formulated to compute the optimal schedule for a given set of HVAC loads, while maintaining occupants comfort and PV generation constraints. Finally, we demonstrate the performance of the present algorithms through simulation, which validates that the proposed mechanism is able to achieve good PV tracking performance as well as obtain a minimal capacity of the required energy storage devices.
| Original language | English |
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| Title of host publication | 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2158-2163 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509021826 |
| DOIs | |
| State | Published - Oct 6 2017 |
| Event | 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 - Kohala Coast, United States Duration: Aug 27 2017 → Aug 30 2017 |
Publication series
| Name | 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 |
|---|---|
| Volume | 2017-January |
Conference
| Conference | 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 |
|---|---|
| Country/Territory | United States |
| City | Kohala Coast |
| Period | 08/27/17 → 08/30/17 |
Funding
J. Dong is with the Building Technologies Research & Integration Center at Oak Ridge National Laboratory, Oak Ridge, TN 37831 USA, [email protected] S. M. Djouadi is with the Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, [email protected] T. Kuruganti and M. M. Olama are with the Modeling & Simulation Group at Oak Ridge National Laboratory, Oak Ridge, TN 37831 USA, {kurugantipv,olamahussemm}@ornl.gov This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
