Pallonetto, Fabiano, De Rosa, Mattia and Finn, Donal P. (2021) Impact of intelligent control algorithms on demand response flexibility and thermal comfort in a smart grid ready residential building. Smart Energy, 2 (100017). ISSN 26669552
Preview
FP_impact.pdf
Download (3MB) | Preview
Abstract
The present paper investigates the impact of advanced control algorithms on harnessing building energy flexibility in a smart-grid ready full-electric residential building. The impact on thermal comfort is also analysed. The building is located in Ireland and is equipped with a geothermal heat pump and a thermal energy storage system. Two Energy Management systems, based on rule-based and intelligent optimisation algorithm approaches, are developed which use real-time building smart meter and weather data. This data is utilised by various dynamic flexibility metrics within the respective control algorithms. Different time of use tariffs, based on data from the Irish Commission for Energy Regulation and structured on the basis of peak, off-peak and night periods, are also used. Results show that energy cost reductions of up to 21% and 43% can be achieved by the rule-based and intelligent algorithm, respectively, without compromising the thermal comfort within the building. Moreover, total shifting and forcing flexibility potential of up to 34 and 54 kWh, respectively, based on the month of January, can be achieved by the adoption of the intelligent control algorithm.
Item Type: | Article |
---|---|
Keywords: | Building flexibility; Optimisation; Control algorithms; Smart grids; Thermal comfort; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI Faculty of Social Sciences > School of Business |
Item ID: | 15604 |
Identification Number: | 10.1016/j.segy.2021.100017 |
Depositing User: | Fabiano Pallonetto |
Date Deposited: | 01 Mar 2022 16:23 |
Journal or Publication Title: | Smart Energy |
Publisher: | Elsevier |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/15604 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
Downloads
Downloads per month over past year