Online optimization and tracking control strategy for battery energy storage in DC microgrids

This paper proposes a fast time-varying optimal power flow (OPF) command tracking control algorithm for DC microgrids based on measurement feedback. The algorithm establishes a model by adding power command tracking constraints and considering the power, voltage, and current constraints of the microgrid. A forward-back generation DC power flow sensitivity calculation method is designed to calculate the power output of the energy storage at each node, and charging and discharging decisions are made based on the state of charge (SOC) of the energy storage system, current voltage, and charging and discharging scenarios previous and subsequent. By continuously issuing control decisions, the DC microgrid OPF command tracking solution is achieved. The measurement feedback control scheme used in this algorithm reduces model error and non-iterative calculation error, thus improving calculation and tracking accuracy. The algorithm is tested in a modified 28-node arithmetic system and suppresses voltage fluctuations caused by unstable PV active output effectively, while accurately tracking the power command of the upper level and meeting the voltage safety operation requirements of the microgrid.