A Smart Home Simulation Tool - The Development of a Simulation Tool for Measuring the Impact of a Smart Grid on a Private Home |
Michael Nysteen, Henrik Mynderup
|
| Abstract | The power grid today is highly affected by the variations in the use of energy during a day which peaks during the afternoon and evenings. Providing the energy required during peak hours is already a challenge and will become increasingly difficult with the increasing amount of unpredictable energy production from renewable energy sources. Therefore it is necessary to be able to shift the energy consumption to match the energy being produced in any given period. One way to control the energy consumption of private homes is to use energy prices that vary during the day based on the energy available. In order to motivate people to shift their consumption, initiatives must be taken to make them aware of which effects it has on their home.
This thesis focuses on how software simulation tools can be used to make consumers aware of these effects. Existing simulation tools of smart homes are examined and it is found that very little work has been done in the area of simulating the effects of varying energy prices in private homes. Therefore this thesis develops a prototype of a simulation tool that enables the users to create accurate models of their homes and simulate how the energy consumption can be scheduled based on energy prices and power generation from attached distributed energy resources such as wind turbines and solar panels.
The key focus areas of the developed simulation tool are usability to make it user-friendly and attractive to use for the consumer; customizability to make it easy to create accurate personalized models; and extensibility to let device manufacturers easily add their energy consuming devices to the application and to let future developers easily add new functionality.
Case studies of two real households are used to examine the accuracy of the simulation and to show how the application can be used to present the effects of using intelligent scheduling of the energy consumption in the home. |
| Type | Master's thesis [Academic thesis] |
| Year | 2012 |
| Publisher | Technical University of Denmark, DTU Informatics, E-mail: reception@imm.dtu.dk |
| Address | Asmussens Alle, Building 305, DK-2800 Kgs. Lyngby, Denmark |
| Series | IMM-M.Sc.-2012-117 |
| Note | DTU supervisor: Bjarne Poulsen, bjpo@imm.dtu.dk, DTU Informatics |
| Electronic version(s) | [pdf] |
| Publication link | http://www.imm.dtu.dk/English.aspx |
| BibTeX data | [bibtex] |
| IMM Group(s) | Computer Science & Engineering |