In the development of society towards renewable energy sources, the target in Sweden is 100% energy supply from renewable energy sources by the year 2040. This requires increased energy production from renewable, but also energy optimization of existing buildings. The housing and service sector which includes households and the public services account for about 40 % of Sweden’s total energy use. It is estimated that preschools and schools have an area of 35 million m² which have an energy savings potentials of 0,7-1 TWh in the electricity consumption and 0,9 TWh in energy use for heating. With regard to energy optimization, it is not only interesting to investigate a buildings total energy use on an annual or monthly basis, but also on shorter time intervals such hourly energy use, because of the uneven energy production of some renewable energy sources such as solar and wind. The purpose of this work is to study the energy usage for some of Västerås preschools and schools, and on the basis of it propose some energy optimization actions. To achieve this a literature study has been carried out to get knowledge about how energy usage is at preschools and schools, as well as to gain insight into what actions are appropriate to perform and how they savings look like. Other than that four objects has been studied, two preschools and two schools, one of each kind were chosen amongst those with the highest energy usage among Västerås city’s preschools and schools and one of each kind amongst those with the lowest usage. The annual energy usage have been calculated and been compared to the actual usage, and the monthly and hourly energy usage for district heating have been studied as well as the electricity usage along the day for different periods. The studied periods and energy usage shows that the energy usage, both for the monthly and hourly,  for the district heating moves with regards to the outdoor temperature with some exceptions. As for the electricity usage it shows that the energy usage is even with some exceptions and there is a difference between different outdoor temperature intervals. Some conclusions could be drawn among others that the objects with higher energy usage where older buildings and the objects with lower energy usage where newer ones. There are some energy optimizations actions for the objects which would lower the energy consumption, both for district heating and electricity usage.