With new smart power meters being installed in the households of Sweden an opportunity has presented itself. It allows the distribution companies to collect a variety of different measurements such as voltage in each phase and the total reactive and active power flowing to and from the customers. This thesis is written in collaboration with Öresundskraft AB, a distribution company in Helsingborg, Sweden. They wished to examine how the smart meter they install, the Kaifa MA304, could aid them in creating a power grid fit for the future. The thesis aims to achieve this goal by researching if PEV, plug-in electrical vehicles, can be identified utilizing data from the new power meters. It is also considered if district heating, and different types of electrical heating, can be identified using outside temperature measurements together with the data. Data has been collected and analyzed from 20 customers over a timespan of eight months in 2022. Here, the mean voltage for every ten minutes (in each phase) and active/reactive power accumulated during the last fifteen minutes is used. The raw data is transformed using a tool developed by the authors in python and is thereafter analyzed using the library pandas. Initial results showed a clear correlation between voltage drop and active power import during three phase charging. In the future, we will study the underlying mechanism of this correlation for devising algorithms to develop and use it as a reliable and effective means to identify PEV’s charging. Households with district heating had, as expected, a relatively even use of power consumption regardless of season or temperature. Electrically heated households used significantly more active power during lower temperature and cold months. The amount of imported reactive power greatly varies between customers, likely due to different technologies such as direct electrical heating and heating pumps. Future work should include knowledge of the utilized heating technologies to devise a method to identify these.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hh-49853 |
| Date | January 2023 |
| Creators | Spook, Albin, Söderlind, Tim |
| Publisher | Högskolan i Halmstad, Akademin för informationsteknologi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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