Optimal Battery Dispatch and Real-Time State of Charge Tracking for Microgrid Applications

This work studies the grid-connected microgrid of a medical facility that is equipped with photovoltaic (PV) energy generation and a local battery energy storage system (BESS). Following a systematic approach in which power flow and state of charge (SoC) dynamics of the BESS is modeled and estimated from experiments, an optimal SoC reference profile is computed given electricity price, predicted solar generation, predicted load, and power and energy constraints. With SoC measurements subjected to errors, a Kalman filter is designed and used in a feedback controller that uses information on the Kalman filtered SoC, PV power and measured power flow at the PCC to compute the desired power demand signal for the DER to ensure the SoC of the BESS remains within operational conditions and tracks the optimal SoC reference profile. Experimental results on SoC scheduling and power control are provided to demonstrate the implementation of the approach.