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Open AccessArticle

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

1
Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, Canada
2
CanmetENERGY, Natural Resources Canada, Varennes, QC J3X 1P7, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: Chi-Ming Lai
Energies 2021, 14(5), 1387; https://doi.org/10.3390/en14051387
Received: 11 January 2021 / Revised: 24 February 2021 / Accepted: 24 February 2021 / Published: 3 March 2021
(This article belongs to the Section Energy and Buildings)
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 2C 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. View Full-Text
Keywords: energy flexibility; predictive control; thermal storage; active storage; passive storage; contingency reserve; BEFI; model-based control energy flexibility; predictive control; thermal storage; active storage; passive storage; contingency reserve; BEFI; model-based control
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MDPI and ACS Style

Date, J.; Candanedo, J.A.; Athienitis, A.K. A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building through Predictive Control of Passive and Active Storage. Energies 2021, 14, 1387. https://doi.org/10.3390/en14051387

AMA Style

Date J, Candanedo JA, Athienitis AK. A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building through Predictive Control of Passive and Active Storage. Energies. 2021; 14(5):1387. https://doi.org/10.3390/en14051387

Chicago/Turabian Style

Date, Jennifer; Candanedo, José A.; Athienitis, Andreas K. 2021. "A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building through Predictive Control of Passive and Active Storage" Energies 14, no. 5: 1387. https://doi.org/10.3390/en14051387

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