Robust reserve capacity provision and peak load reduction from buildings in smart grids

Sarmad Hanif; Dante Fernando Recalde Melo; Mehdi Maasoumy; Tobias Massier; Thomas Hamacher; Thomas Reindl

doi:10.1109/PESGM.2016.7741399

Robust reserve capacity provision and peak load reduction from buildings in smart grids

Sarmad Hanif, Dante Fernando Recalde Melo, Mehdi Maasoumy, Tobias Massier, Thomas Hamacher, Thomas Reindl

Chair of Renewable and Sustainable Energy Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper proposes a robust demand-side control algorithm in a smart grid environment for heating, ventilation and air conditioning (HVAC) systems. A robust model predictive control (RMPC) scheme in a receding horizon fashion is deployed, which optimizes electricity cost and capacity market participation of the HVAC system, while satisfying comfort and operational constraints of the building and utility, respectively. Thermal load uncertainties experienced by the HVAC system are included to perform a realistic assessment of the developed controller. The National Electricity Market of Singapore (NEMS) is used as a case study and the developed RMPC scheme is tested for various price signals and scenarios. Numerical simulation results show the effectiveness of the developed framework to be readily adopted by utilities - interested in realizing a grid-friendly and economically efficient demand response (DR) strategy.

Original language	English
Title of host publication	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Publisher	IEEE Computer Society
ISBN (Electronic)	9781509041688
DOIs	https://doi.org/10.1109/PESGM.2016.7741399
State	Published - 10 Nov 2016
Event	2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States Duration: 17 Jul 2016 → 21 Jul 2016

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2016-November
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Country/Territory	United States
City	Boston
Period	17/07/16 → 21/07/16

Keywords

Demand Response
Energy Market
Heating Ventilation Air-Conditioning (HVAC)
Reserve Market
Robust Model Predictive Control (RMPC)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/PESGM.2016.7741399

Cite this

Hanif, S., Melo, D. F. R., Maasoumy, M., Massier, T., Hamacher, T., & Reindl, T. (2016). Robust reserve capacity provision and peak load reduction from buildings in smart grids. In 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 Article 7741399 (IEEE Power and Energy Society General Meeting; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/PESGM.2016.7741399

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title = "Robust reserve capacity provision and peak load reduction from buildings in smart grids",

abstract = "This paper proposes a robust demand-side control algorithm in a smart grid environment for heating, ventilation and air conditioning (HVAC) systems. A robust model predictive control (RMPC) scheme in a receding horizon fashion is deployed, which optimizes electricity cost and capacity market participation of the HVAC system, while satisfying comfort and operational constraints of the building and utility, respectively. Thermal load uncertainties experienced by the HVAC system are included to perform a realistic assessment of the developed controller. The National Electricity Market of Singapore (NEMS) is used as a case study and the developed RMPC scheme is tested for various price signals and scenarios. Numerical simulation results show the effectiveness of the developed framework to be readily adopted by utilities - interested in realizing a grid-friendly and economically efficient demand response (DR) strategy.",

keywords = "Demand Response, Energy Market, Heating Ventilation Air-Conditioning (HVAC), Reserve Market, Robust Model Predictive Control (RMPC)",

author = "Sarmad Hanif and Melo, {Dante Fernando Recalde} and Mehdi Maasoumy and Tobias Massier and Thomas Hamacher and Thomas Reindl",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 ; Conference date: 17-07-2016 Through 21-07-2016",

year = "2016",

month = nov,

day = "10",

doi = "10.1109/PESGM.2016.7741399",

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Hanif, S, Melo, DFR, Maasoumy, M, Massier, T, Hamacher, T & Reindl, T 2016, Robust reserve capacity provision and peak load reduction from buildings in smart grids. in 2016 IEEE Power and Energy Society General Meeting, PESGM 2016., 7741399, IEEE Power and Energy Society General Meeting, vol. 2016-November, IEEE Computer Society, 2016 IEEE Power and Energy Society General Meeting, PESGM 2016, Boston, United States, 17/07/16. https://doi.org/10.1109/PESGM.2016.7741399

Robust reserve capacity provision and peak load reduction from buildings in smart grids. / Hanif, Sarmad; Melo, Dante Fernando Recalde; Maasoumy, Mehdi et al.
2016 IEEE Power and Energy Society General Meeting, PESGM 2016. IEEE Computer Society, 2016. 7741399 (IEEE Power and Energy Society General Meeting; Vol. 2016-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hanif, Sarmad

AU - Melo, Dante Fernando Recalde

AU - Maasoumy, Mehdi

AU - Massier, Tobias

AU - Hamacher, Thomas

AU - Reindl, Thomas

PY - 2016/11/10

Y1 - 2016/11/10

N2 - This paper proposes a robust demand-side control algorithm in a smart grid environment for heating, ventilation and air conditioning (HVAC) systems. A robust model predictive control (RMPC) scheme in a receding horizon fashion is deployed, which optimizes electricity cost and capacity market participation of the HVAC system, while satisfying comfort and operational constraints of the building and utility, respectively. Thermal load uncertainties experienced by the HVAC system are included to perform a realistic assessment of the developed controller. The National Electricity Market of Singapore (NEMS) is used as a case study and the developed RMPC scheme is tested for various price signals and scenarios. Numerical simulation results show the effectiveness of the developed framework to be readily adopted by utilities - interested in realizing a grid-friendly and economically efficient demand response (DR) strategy.

AB - This paper proposes a robust demand-side control algorithm in a smart grid environment for heating, ventilation and air conditioning (HVAC) systems. A robust model predictive control (RMPC) scheme in a receding horizon fashion is deployed, which optimizes electricity cost and capacity market participation of the HVAC system, while satisfying comfort and operational constraints of the building and utility, respectively. Thermal load uncertainties experienced by the HVAC system are included to perform a realistic assessment of the developed controller. The National Electricity Market of Singapore (NEMS) is used as a case study and the developed RMPC scheme is tested for various price signals and scenarios. Numerical simulation results show the effectiveness of the developed framework to be readily adopted by utilities - interested in realizing a grid-friendly and economically efficient demand response (DR) strategy.

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KW - Energy Market

KW - Heating Ventilation Air-Conditioning (HVAC)

KW - Reserve Market

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T3 - IEEE Power and Energy Society General Meeting

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PB - IEEE Computer Society

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Robust reserve capacity provision and peak load reduction from buildings in smart grids

Abstract

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Conference

Keywords

UN SDGs

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