Publication details
Model Predictive Control Scheme for Investigating Demand Side Flexibility in Singapore
Publication data
Type:
Conference paper
Authors:
Sarmad Hanif, Dante Fernando Recalde Melo, Mehdi Maasoumy, Tobias Massier, Thomas Hamacher and Thomas Reindl
Published in:
Proceedings of the 2015 50th International Universities Power Engineering Conference (UPEC)
(Electronic ISBN: 978-1-4673-9682-0, USB ISBN: 978-1-4673-9683-7)
(Electronic ISBN: 978-1-4673-9682-0, USB ISBN: 978-1-4673-9683-7)
Publisher:
Institute of Electrical and Electronics Engineers (IEEE),
New York (New York, United States of America)
Publication date:
September 2015
Pages:
1–6
Conference:
2015 50th International Universities Power Engineering Conference (UPEC)
Conference location:
Staffordshire University,
Stoke-on-Trent (United Kingdom)
Conference dates:
01 September 2015
– 04 September 2015
Abstract:
Recently, power systems have experienced various changes, the most important one being the increase in the share of highly variable renewable energy supply (RES). To counteract the variability of RES, provision of flexibility from the demand side seems to be a viable option. In this paper, the heating, ventilation and air conditioning (HVAC) system, mostly installed in medium to large sized office buildings, is selected to provide demand side flexibility. A model predictive control (MPC) scheme in a receding horizon environment is deployed to provide an economic operation of the building, while respecting comfort constraints of dwellers. Furthermore, robustness is introduced in the MPC scheme to participate in both the energy and reserve market. Simulations are performed to demonstrate the performance of the developed controller under various price signals. In doing so, the controller is also evaluated with respect to its sensitivity towards economical and technical constraints. The National Electricity Market of Singapore (NEMS) is used as a case study and the most important parameters governing the challenges for integrating demand side flexibility in the grid are pointed out.
Keywords:
Demand side management, Energy market, Heating ventilation and air conditioning, Model predictive control, Smart grid
DOI:
Further information
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Format:
@inproceedings{Hanif_ModelPredictiveControl_2015,
author = {Hanif, Sarmad and Recalde Melo, Dante Fernando and Maasoumy, Mehdi and Massier, Tobias and Hamacher, Thomas and Reindl, Thomas},
title = {Model Predictive Control Scheme for Investigating Demand Side Flexibility in {Singapore}},
year = {2015},
month = sep,
booktitle = {Proceedings of the 2015 50th International Universities Power Engineering Conference (UPEC)},
isbn = {978-1-4673-9682-0},
publisher = {IEEE},
address = {Stoke-on-Trent, UK},
pages = {1--6},
doi = {10.1109/UPEC.2015.7339769},
keywords = {Demand side management, Energy market, Heating ventilation and air conditioning, Model predictive control, Smart grid},
}
@inproceedings{Hanif_ModelPredictiveControl_2015,
author = {Hanif, Sarmad and Recalde Melo, Dante Fernando and Maasoumy, Mehdi and Massier, Tobias and Hamacher, Thomas and Reindl, Thomas},
title = {Model Predictive Control Scheme for Investigating Demand Side Flexibility in {Singapore}},
date = {2015-09},
booktitle = {Proceedings of the 2015 50th International Universities Power Engineering Conference (UPEC)},
isbn = {978-1-4673-9682-0},
publisher = {IEEE},
location = {Stoke-on-Trent, UK},
pages = {1--6},
doi = {10.1109/UPEC.2015.7339769},
keywords = {Demand side management, Energy market, Heating ventilation and air conditioning, Model predictive control, Smart grid},
}
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