The purpose of this study is to create a method that can be used to produce decision supportdata for the climate goals of a municipality. The method should be able to demonstrate the potential for reducing energy use and greenhouse gas emissions for measures aimed at the stationary energy system in the municipality. It will be used to make long term projections of energy use and greenhouse gas emissions in order to be able to demonstrate the ability to reach climate goals. The aim was also to test the method's applicability by using the municipality of Uppsala and the Uppsala climate protocol project in a case study. Uppsala climate protocol is a project consisting of participants from business, government and organizations that voluntarily want to commit to reducing their carbon footprint by reducing their energy use and thus work to achieve the municipality's overall climate goal. Public reporting of energy use and climate impact has been studied in order to examine the nature of indicators and accounting figures that are commonly used in the field and how long-term forecasts are formulated. In connection to this, the type and sources for the kind of data needed was also examined. Tools that can be used as means for performing forecasts of energy systems development has been studied and evaluated. In the developed method the municipality’s geographical limit act as an overall system limit. The climate impact of the studied systems originates from fossil fuel combustion in the stationary energy system within the municipal boundaries, with the exception of electricity produced outsidethe municipality. At the case study of the municipality of Uppsala and the Uppsala climate protocol, most of the input data required for a baseline inventory and formulation of scenarios was retrieved from the Swedish Energy Agency, the Swedish Central Bureau of statistics and Vattenfall Heat Uppsala. Energy use and climate change forecasts was made using the simulation tool LEAP (Long-range Energy Alternatives Planning System). Two scenarios were modeled; a reference scenario describing the energy system's long-term development if no further measures is taken in addition to those already decided and an actor scenario describing an alternative development of the energy system based on additional measures to reduce climate impact. Results were reported for a base year, 2020 and 2030. For 2020 the results showed that greenhouse gas emissions from the stationary energysystems becomes 1.7 tonnes CO2-e per capita in the actor scenario, compared with 2.4 tonnes of CO2-e per capita in the reference scenario. The overall climate goal of the municipalityof Uppsala and Uppsala climate protocol is that total emissions should not exceed 4.8 tonnes CO2-e per capita by 2020. The case study shows how the method can be used to make projections of energy use and climate impact from the stationary energy system within a municipality. It also shows how the method can be used to compare measures for achieving climate goals.

When the low voltage electric grid is dimensioned electric loads are predicted by analyzing the area by certain factors such as geographical data, customer type, heating method etc. So far, the charging of Plugin Electric Vehicles (PEVs) is not considered as one of these factors. Approximately 30% of the distribution grid in Sweden is projected to need reinforcements due to the increased loads from PEVs during winters if the charging isn’t controlled. In addition to this Stockholm face the problem of capacity shortage from the transmission grid, limiting the flow of electricity into the city. This research is therefore conducted to analyze the impact that the increase of PEVs will have on the distribution grid in the future. This thesis simulates the electric grid for three substations located in Hammarby Sjöstad by using power flow analysis and electric grid data from 2016. To approach this problem a method to disaggregate the total power consumption per substation into power consumption responding to each building was developed. In addition to this the number of PEVs in the future was projected. Nine different scenarios were used to compare different outcomes for the future, namely the years of 2025 and 2040. In order to simulate the worst possible case for the electric grid all the PEVs were assumed to be charged at the same time, directly when arriving home on the Sunday when the power demand peaks in 2016. The results indicate that PEVs can have a considerable impact on the components of the low voltage distribution network and controlled charging should be implemented. By examining the impact on the simulated electric grid from the different scenarios the limit of PEV penetration is found. In the area of Hammarby this limit seems to be around 30 % of the total cars if there is no controlled charging. Without any controlled charging the peak power demand increases by 30% with a 30% share of PEVs, which is projected to happen in 2025. In 2040 when share of PEVs is projected to be about 95% the peak power is instead increased by more than 100% which shows the impact that PEVs can exert on the electric grid. Utilizing a simple method of controlled charging where the PEVs are instead charged during the night when the power demand is low, the peak power is not increased at all. This also results in the small cost benefit for PEV owners since the electricity is cheaper during the night and controlled charging can therefore save about 15% of the electricity charging cost. However, the main savings are for the grid owners since the need to reinforce the grid is heavily reduced. In addition to this the power losses are reduced heavily from about 14% down to 5% in the electric grid that is simulated. / När dimensioneringen av distributionsnätet utförs analyseras området genom att räkna med elektriska laster som till exempel kan bero på geografiska data, typ av konsument, uppvärmningsmetod etcetera. Än så länge har laddningen av elbilar (PEVs) inte varit en av dessa faktorer trots den förväntade tillväxten av elbilar. Ungefär 30% av Sveriges distributionsnät förväntas behöva förstärkningar på grund av den ökade elkonsumtionen från elbilar under vintrarna om laddningen inte kontrolleras. Utöver detta står Stockholm inför problemet med effektbrist från elöverföringsnätet. Denna uppsats genomförs således för att analysera påverkan från elbilar på fördelningsnätet i framtiden. Denna masteruppsats simulerar det elektriska nätet för tre nätstationer i Hammarby Sjöstad genom en analys av effektflödet. En metod för att disaggregera elkonsumtionen per nätstation ned till elkonsumtionen per byggnad utvecklades och antalet elbilar i framtiden uppskattades. För att utvärdera elbilars påverkan skapades nio olika scenarion för framtiden genom att undersöka hur det kommer att se ut år 2025 och år 2040. Genom att anta att laddningen av alla elbilar i området sker samtidigt, samma tid som den maximala förbrukningen av el sker under en söndag 2016, analyseras det värsta möjliga scenario för det elektriska nätet. Resultaten visar att elbilar kan ha enorm påverkan på de maximala lasterna för ett lågspänningsnät och därför kommer kontroll av laddningen behövas. Genom att undersöka elnätets påverkan i de olika scenariona uppskattades gränsen för hur många elbilar det modellerade elnätet klarar av. I Hammarby Sjöstad ligger denna gräns på ungefär 30% elbilar. Utan kontrollerad laddning ökar maxlasten med 30% år 2025 då antalet elbilar förväntas vara 30% av alla bilar i Hammarby Sjöstad. År 2040 då antalet elbilar uppnår ungefär 95 % av alla bilar ökar maxlasterna med mer än 100% vilket visar den enorma påverkan elbilar kan ha på elnätet. Genom att använda en simpel modell av kontrollerad laddning som består av att flytta laddningen från eftermiddagen till natten, då förbrukningen av elektricitet är låg, ökar inte maxlasten för dygnet alls jämfört med scenariot utan elbilar. Detta resulterar också i besparingen av elektricitetskostnad för elbilsägaren med cirka 15% eftersom elektriciteten ofta är billigare under natten jämfört med kvällens elpriser. Detta är dock små summor jämfört med besparingar elnätsägarna kan göra då elnätet inte behöver förstärkas lika mycket som skulle behövas utan kontroll av laddningen. Utöver detta så sänks även förlusterna av elektricitet i det simulerade nätet från 14% ned till 5% genom att utnyttja denna modell av kontrollerad laddning.