This study has explored the potential for lowering the subscripted power of 25 MW for one of the connection points between the local power grid and its overhead power grid for a local grid owner. The potential for doing so through hard, direct load control of electrical domestic heating and domestic water heating for detached houses with a fuse size of 16-25 A is evaluated for 12 different scenarios. The scenarios are found by combining a customer participation of 25, 50, 75 and 100 percent with a maximum allowed duration for load control of two, three and four hours respectively. A function describing the need for electrical power for domestic heating as dependent of the outdoor temperature is developed and combined with a model that is used for simulating hot water usage and a model that describes the power demand of a domestic water heater. Furthermore, a control function is incorporated to ensure that households are not subjected to load control for a longer period than allowed and that all households bear the same burden in this respect.  The results show that a power of 1,0-4,1 MWh/h can be redistributed, but that the potential is heavily limited by the returning load that occurs. Due to the long duration of the critical peaks that are being redistributed, up to 5-10 hours, returning load occurs even though load control has not yet been finalized. The returning load leads to a bigger amount of power having to be redistributed and therefore limits the potential for the new subscripted power that can be achieved. Furthermore, the maximum aggregated power for the investigated year amounts to 25,9 MW. Still, a new subscripted power of 21,8–24,9 MW is theoretically deemed to be achievable. The most likely outcome however is thought to be a lowering of the subscripted power to at least 23,4–24,4 MW, having taken the composition of type of heating systems as well as the most likely customer participation into account.

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.