DocumentCode
3578534
Title
A high-resolution smart home power demand model and future impact on load profile in Germany
Author
Alzate, Efrain Bernal ; Mallick, Nayeem H. ; Jian Xie
Author_Institution
Inst. of Energy Conversion & Storage, Univ. of Ulm, Ulm, Germany
fYear
2014
Firstpage
53
Lastpage
58
Abstract
The penetration level of both photovoltaic and home automation systems is expected to increase in the short-term future in Germany and their combination will undoubtedly have some effect on the low-voltage grid. This study outlines the development of a high-resolution smart home power demand model taking into account the activity patterns of individuals, based on non-homogeneous Markov chain that are tuned to a German time use survey. The projected change in population size of Germany for the next years with the trends in photovoltaic, some automation system and efficient appliances, in combination with a home energy management algorithm are considered to estimate the future potential impacts of the increasing smart home incursion on the residential load profiles. The results show highly realistic patterns that capture annual and daily variations, load fluctuations and diversity between households as a function of number of persons. It is found that there is a 29.8% decrease in annual energy consumption when the home automation system acts to manage the power consumption of the devices for a current German household and a significant decrease of 70.1% for a future smart home scenario. Besides, the analysis undertaken in this study reveals that relative penetration of smart homes can cause an elevated variation in the daily demand profile up to 56% with respect to the current demand profile pattern.
Keywords
Markov processes; buildings (structures); demand side management; domestic appliances; home automation; photovoltaic power systems; power consumption; power grids; German household; German time use survey; Germany; demand profile pattern; energy consumption; home automation systems; home energy management algorithm; load fluctuations; low-voltage grid; nonhomogeneous Markov chain; photovoltaic system; power consumption; residential load profiles; smart home power demand model; Automation; Brain modeling; Energy consumption; Home appliances; Load modeling; Power demand; Smart homes;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy (PECon), 2014 IEEE International Conference on
Print_ISBN
978-1-4799-7296-8
Type
conf
DOI
10.1109/PECON.2014.7062413
Filename
7062413
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