According to the 20-20-20 targets set by the European Union, 50 percent of the Swedish electricity share is to be provided by renewable energy sources by 2020. The Smart Grid Gotland (SGG) project has emerged as a response to this target. The project aims at demonstrating a proof of concept on how smart grid solutions can be used to integrate large quantities of renewable energy sources in an existing network. The outcomes of the project are intended to pave the way for future renewable energy integration projects in Sweden. The Thesis focuses on one of the technical objectives of the SGG project, i.e. to increase the hosting capacity of wind power on Gotland from 195 MW to 200 MW by using Demand-Response (DR) from households and industries. DR consist of shifting peak-loads to peakproduction hours. The integration of additional wind power causes a risk of exceeding the transmission capacity of the power export cable between Gotland and the Swedish mainland. The approach considered for this Thesis is to use an Ancillary Service (AS) toolbox scheme based on multi-agent systems. The AS toolbox consist of flexibility tools such as DR on long-term, short-term, a battery energy storage system and a wind curtailment scheme. The DR activity includes space heating and domestic hot water consumption from detached houses on Gotland. The simulation results indicate that 1900 household participants are sufficient to balance the additional 5 MW for worst case scenarios. Furthermore, it is shown that the DR participation from industries contributes in some cases to a reduction of 700 household participants. The findings helped conclude that using an AS toolbox solution on Gotland is fully possible from a technical perspective. However, barriers that stand against its realisation are of economical nature and need to be investigated in future studies.

The increase in electric vehicles and photovoltaic power production may introduce problems to the low-voltage distribution grid. With a higher number of electric vehicles, their accumulated charging power might breach the lowest allowed voltage level of the grid. Photovoltaic-modules can on the other hand exceed the highest allowed voltage level, by producing high accumulated power when the solar irradiance is high. Normally, electric distribution companies in Sweden reinforce the existing grid with more resilient infrastructure, such as stronger and larger cables or transformer stations. This is however a costly and time-consuming solution, which could be solved by using alternative means such as already existing resources. This Master's Thesis investigates how smart charging of batteries can support the low-voltage electrical grid with the increase in electric vehicles and photovoltaic power production. To do this, an optimization tool has been developed in Matlab. An existing model of a low-voltage grid is combined with the developed tool, where controllable batteries and photovoltaic-modules can be placed at specific households in the grid. The controllable batteries belong to either electric vehicles or stationary battery systems, and are intended to support the grid by the means of either reducing peak load powers, voltage variations, or a trade-off between them. Furthermore, this thesis investigates the maximum electric vehicle capability for a specific low-voltage electrical grid in Sweden. From the results, it can be concluded that smart charging of batteries can reduce the peak loads as well as voltage variations. The reduction of voltage variations for the entire low-voltage grid is greatest during the summer, when photovoltaic production generally is at its highest. The results also show that a stationary battery system can reduce the voltage variations to a greater extent, compared to an electric vehicle. Also, the introduction of multiple controllable batteries allows further support of the low-voltage grid. Regarding the maximum electric vehicle capability, the results show that the placement of the vehicles and the charging power strongly affect the maximum number of electric vehicles the low-voltage grid can manage. / Ökningen av elbilar och elproduktion från solceller kan ge problem i lågspänningsnätet. Med ett ökat antal elbilar kan den sammanlagrade effekten vid laddning underskrida den minsta tillåtna spänningsnivån i nätet. Solpaneler kan däremot leda till att den högsta tillåtna spänningsnivån överskrids, genom att producera en hög sammanlagrad effekt när solstrålningen är som högst. Vanligtvis förstärker elnätsbolag i Sverige det befintliga nätet med motståndskraftigare infrastruktur, såsom kraftigare och större kablar eller transformatorstationer. Detta är dock en kostsam och tidskrävande lösning, som skulle kunna lösas med alternativa medel, till exempel redan existerande resurser. Detta examensarbete undersöker hur smart laddning av batterier kan ge stöd till lågspänningsnätet, med en ökning av elbilar samt solcellsproduktion. För att undersöka detta har ett optimeringsverktyg utvecklats i Matlab. En befintlig modell av ett lågspänningsnät har kombinerats med det utvecklade optimeringsverktyget, där styrbara batterier samt solcellsproduktion kan placeras vid specifika hushåll i elnätet. De styrbara batterierna är antingen elbilar eller stationära batterisystem, och är ämnade till att stödja lågspänningsnätet genom att antingen reducera effekttoppar, spänningsvariationer eller en kompromiss av båda. Vidare undersöker detta examensarbete det maximala antalet elbilar som ett specifikt lågspänningsnät i Sverige kan hantera. Resultaten visar att smart laddning av batterier kan reducera effekttoppar samt spänningsvariationer. Reduceringen av spänningsvariationerna för hela lågspänningsnätet visar sig vara högst under sommaren, vilket är då solcellsproduktionen generellt är som högst. Resultaten visar även att stationära batterisystem kan reducera spänningsvariationer ytterligare, jämfört med en elbil. Att introducera flera styrbara batterier tillåter ett ännu större stöd till lågspänningsnätet. Angående det maximala antalet av elbilar som ett lågspänningsnät kan hantera visade resultaten att placeringen av elbilarna samt laddningseffekten har en stor påverkan.