The European union is accelerating the energy transition to facilitate more renewable energy generation. New EU directives set out goals that member countries must achieve. One key activity is to allow energy sharing within energy communities. With local production, consumption, storage and energy sharing, more renewable energy production can be integrated in the electricity market and reduce the costs for its members. In this project the implementation of an energy community for the property Tenoren 3 in Eskilstuna municipality will be studied. The aim of the project is to investigate how the maximum power need, the amount of bought electricity from the local grid as well as the costs of the bought electricity is affected bythe installation of the energy community. A simulation model of an energy community containing solarpanels and battery storage is developed in Python. The model is based on real data for the property consumption and synthetic data for the solar power production, household consumption as well as the Electric Vehicle (EV) charging. Three scenarios with different battery management strategies are examined. In scenario 1 the battery is optimized for peak shaving. In scenario 2 the battery is optimized for the needs of Tenoren 3. In scenario 3 the resource is optimized for the local grid in Eskilstuna. The result implies that the scenario which decreases the maximal power need the most is scenario 1. Both scenario 2 and scenario 3 result in the highest decrease of bought electricity. The scenario with the highest cost reduction for the owners of the energy community is scenario 2. The difference in cost reduction toscenario 3 is however negligible. To promote the progress of energy communities in Sweden it will be important that both the distribution system operator (DSO) as well as the owners of the energy communityare satisfied. Such a conceivable solution that this study addresses is that the battery storage is managed according to the stress on the distribution grid. With a large-scale implementation of energy sharing according to scenario 3 this would result in a situation where the owners of the energy community save money at the same time as the DSO would profit from lower stress on the distribution grid.