This paper presents a method for defining and managing complex power management behaviors in microgrids that incorporate renewable energy sources, storage devices with different characteristics, and a connection to the main grid. In particular, we focus on a smart railway station that integrates regenerative braking energy from trains. The challenge lies in coordinating diverse microgrid components while adhering to constraints across multiple control levels. We use signal temporal logic (STL) to precisely define these complex objectives and integrate them into a model predictive control (MPC) framework. We present numerical simulations using a mixed-integer strategy to demonstrate the approach's effectiveness.