Investigation of the effect of the envelope on building thermal storage performance under model predictive control by dynamic pricing

Dynamic pricing is designed for the load shaping to help match the amount of the energy demand to the energy supply capacity. Since the buildings’ characteristics influence the performance of the energy shifting, renovation of the building towards a higher energy flexibility is worth investigating....

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Bibliographic Details
Main Authors: Calautit, J. (Author), Wei, Z. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 01970nam a2200193Ia 4500
001 10.1016-j.segy.2022.100068
008 220517s2022 CNT 000 0 und d
020 |a 26669552 (ISSN) 
245 1 0 |a Investigation of the effect of the envelope on building thermal storage performance under model predictive control by dynamic pricing 
260 0 |b Elsevier Ltd  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1016/j.segy.2022.100068 
520 3 |a Dynamic pricing is designed for the load shaping to help match the amount of the energy demand to the energy supply capacity. Since the buildings’ characteristics influence the performance of the energy shifting, renovation of the building towards a higher energy flexibility is worth investigating. This study evaluated the effect of the envelope on building thermal storage performance. A model predictive control (MPC) was developed to achieve a multi-objective control i.e., indoor comfort temperature and minimise the total energy cost. MPC automatically triggered the energy storage during the low price periods and used the stored energy during the high price periods. The results confirmed the ability of MPC on peak demand reduction up to 45% electricity cost. Besides, the results also demonstrated the ability of heavyweight thermal mass in terms of reducing energy consumption and shifting a greater high price energy to the low price times. Therefore, adding insulation layers into the lightweight thermal mass is highly recommended, especially for the places experiencing the significant mismatch between the demand and supply during daily peaks or the areas scheduling a large amount of intermittent renewable energy source in the energy production. © 2022 The Authors 
650 0 4 |a Building renovation 
650 0 4 |a Demand response 
650 0 4 |a Model predictive control (MPC) 
650 0 4 |a Thermal storage 
700 1 |a Calautit, J.  |e author 
700 1 |a Wei, Z.  |e author 
773 |t Smart Energy