A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage

Optimal management of thermal energy storage in a building is essential to provide predictable energy flexibility to a smart grid. Active technologies such as Electric Thermal Storage (ETS) can assist in building heating load management and can complement the building’s passive thermal storage capac...

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Main Authors: Jennifer Date, José A. Candanedo, Andreas K. Athienitis
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/5/1387
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spelling doaj-395b312d678b417aa226f5b822daaeaf2021-03-04T00:05:28ZengMDPI AGEnergies1996-10732021-03-01141387138710.3390/en14051387A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active StorageJennifer Date0José A. Candanedo1Andreas K. Athienitis2Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, CanadaDepartment of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, CanadaDepartment of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, CanadaOptimal management of thermal energy storage in a building is essential to provide predictable energy flexibility to a smart grid. Active technologies such as Electric Thermal Storage (ETS) can assist in building heating load management and can complement the building’s passive thermal storage capacity. The presented paper outlines a methodology that utilizes the concept of Building Energy Flexibility Index (BEFI) and shows that implementing Model Predictive Control (MPC) with dedicated thermal storage can provide predictable energy flexibility to the grid during critical times. When the utility notifies the customer 12 h before a Demand Response (DR) event, a BEFI up to 65 kW (100% reduction) can be achieved. A dynamic rate structure as the objective function is shown to be successful in reducing the peak demand, while a greater reduction in energy consumption in a 24-hour period is seen with a rate structure with a demand charge. Contingency reserve participation was also studied and strategies included reducing the zone temperature setpoint by 2<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mo>∘</mo></msup></semantics></math></inline-formula>C for 3 h or using the stored thermal energy by discharging the device for 3 h. Favourable results were found for both options, where a BEFI of up to 47 kW (96%) is achieved. The proposed methodology for modeling and evaluation of control strategies is suitable for other similar convectively conditioned buildings equipped with active and passive storage.https://www.mdpi.com/1996-1073/14/5/1387energy flexibilitypredictive controlthermal storageactive storagepassive storagecontingency reserve
collection DOAJ
language English
format Article
sources DOAJ
author Jennifer Date
José A. Candanedo
Andreas K. Athienitis
spellingShingle Jennifer Date
José A. Candanedo
Andreas K. Athienitis
A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage
Energies
energy flexibility
predictive control
thermal storage
active storage
passive storage
contingency reserve
author_facet Jennifer Date
José A. Candanedo
Andreas K. Athienitis
author_sort Jennifer Date
title A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage
title_short A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage
title_full A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage
title_fullStr A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage
title_full_unstemmed A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage
title_sort methodology for the enhancement of the energy flexibility and contingency response of a building through predictive control of passive and active storage
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-03-01
description Optimal management of thermal energy storage in a building is essential to provide predictable energy flexibility to a smart grid. Active technologies such as Electric Thermal Storage (ETS) can assist in building heating load management and can complement the building’s passive thermal storage capacity. The presented paper outlines a methodology that utilizes the concept of Building Energy Flexibility Index (BEFI) and shows that implementing Model Predictive Control (MPC) with dedicated thermal storage can provide predictable energy flexibility to the grid during critical times. When the utility notifies the customer 12 h before a Demand Response (DR) event, a BEFI up to 65 kW (100% reduction) can be achieved. A dynamic rate structure as the objective function is shown to be successful in reducing the peak demand, while a greater reduction in energy consumption in a 24-hour period is seen with a rate structure with a demand charge. Contingency reserve participation was also studied and strategies included reducing the zone temperature setpoint by 2<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mo>∘</mo></msup></semantics></math></inline-formula>C for 3 h or using the stored thermal energy by discharging the device for 3 h. Favourable results were found for both options, where a BEFI of up to 47 kW (96%) is achieved. The proposed methodology for modeling and evaluation of control strategies is suitable for other similar convectively conditioned buildings equipped with active and passive storage.
topic energy flexibility
predictive control
thermal storage
active storage
passive storage
contingency reserve
url https://www.mdpi.com/1996-1073/14/5/1387
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