Todays electricity consumer tend to become small businesses as they invest in their own decentralized electricity generation and stationary electricity storage as well as in information technology (IT) to connect and organize these new devices. Furthermore, the installed IT allows them at least technically to establish local markets. The variety of consumers and their characteristics implies numerous ways of how they optimize their individual unit commitment. This paper aims to analyze the impact of the individual consumers decisions on a future electricity demand and feed-in on low voltage network level. Therefore, in a first step the different unit commitment problems of the different small businesses have been modeled using linear programming (LP). In a second step these consumers are modeled as learning agents of a multi-agent system (MAS). The MAS comprises a local electricity market in which participants negotiate supply relationships. Finally, using scenarios with different input parameters the resulting impact is studied in detail. Amongst others, the simulations’ results show major changes in electricity demand and feed-in for scenarios with high market penetration of storages.