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Convenience in a residence with demand response: A system dynamics simulation model
•Measures convenience.•Decision-making on preferences.•DR Simulation of a residence. Demand Side Management (DSM) is a means to gain more control over energy demand to address some of the challenges of power grids. Demand Response (DR) is an approach to DSM that aims to influence the operation times...
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Published in: | Applied energy 2022-05, Vol.314, p.118929, Article 118929 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Measures convenience.•Decision-making on preferences.•DR Simulation of a residence.
Demand Side Management (DSM) is a means to gain more control over energy demand to address some of the challenges of power grids. Demand Response (DR) is an approach to DSM that aims to influence the operation times of appliances; DR is often recommended for residences. Meanwhile, residents can undermine DR if it is not convenient. Therefore, there is need for tools to aid decision-making on the appropriate DR program for residences. Whilst models are used to explore DR programs, most do not measure, visualise or analyse the convenience of residents, although some models make assumptions about convenience. This paper explores convenience of a residence as timeliness by simulating four scenarios of DR programs in a single residence, using the System Dynamics (SD) methodology. In addition to delay in appliance-use that may result from DR, two indicators of convenience are proposed that consider preferences of the residence: Delay Duration Profile (DDP) and Delay Time Profile (DTP). When comparing convenience as delay, it was found that more hours of DR is better than less, earlier hours (from occupancy period) are better, and splitting or distributing DR hours during the day is better than being contiguous. Similar findings apply to DDP and DTP. Furthermore, it was found that DR leads to monetary savings and reduction in daily peak demand. This study represents the first attempt at a DR model from the bottom-up using SD, as well as using the model in decision-making analysis. |
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ISSN: | 0306-2619 1872-9118 |
DOI: | 10.1016/j.apenergy.2022.118929 |