As the world undertakes global climate goals to lower the emissions of greenhouse gases, more renewable energy sources are introduced in the electrical energy system, and fossil fuel driven combustion engines aims to be replaced by electric vehicles. New problems connected to the transition such as voltage fluctuations, production and consumption mismatch and high peak loads, requires new solutions. Such a solution could be to use smart charging algorithms and bidirectional charging for electrical vehicles in order to avoid further increased power demand during peak demand hours and to make the electric vehicle a resource more than solely as a mode of transportation. Such resource could be a battery storage for the home by using a vehicle to home strategy and for the electrical grid by using a vehicle to grid strategy. These strategies demand certain technology with only a few options available on the market today, but with a lot of recent and ongoing research on the way. In this thesis a smart charging algorithm is developed which aims to lower a households electricity cost by optimizing charging and discharging of an electric vehicle. The charging may come from the grid or the household’s photovoltaic system and the discharging may go to the house home appliances or back to the grid, utilizing vehicle to home and vehicle to grid strategies. The algorithm was tested in MATLAB for five different scenarios showcasing these possibilities and simulated in combination with five different user profiles. The results show that the charging peaks are moved to an area of less consumption and verify that the electricity costs can be lowered on daily and yearly basis.