Energy sustainability is a necessary goal for human flourishing. One way to tackle this is by making good management of electrical equipment and maximizing the efficiency and performance of it. In this paper, an energy storage management system capable of managing stationary batteries from individual households by making use of information about other energy resources. These resources available to the community are photovoltaic panels, electric vehicles, stationary batteries and other domestic devices. This is done by integrating a mixed integer linear programming algorithm for day-ahead scheduling and a genetic algorithm for real-time scheduling in a multi-agent system for managing individually and collectively homes from an energy community. The data comes from a published dataset where real houses were used to extract the data. This system was tested in a hybrid environment where part of the simulation interacts and acts on real batteries. The results show the system is capable of scheduling the battery usage throughout the day and how that impacts the real battery.