This research proposes a practical power coordi-nation approach for battery energy storage units (BESUs) via a leader-follower optimization methodology. The leader stage defines the BESUs' state of charge using the sine cosine algorithm (SCA). In the follower stage, a power flow tool based on the successive approximations method is implemented in order to determine the solution of the power balance equations. In addition, exploration and exploitation of the solution space are carried out using an equivalent fitness function. Considering the nonlinear non-convex optimization model for the optimal power coordination problem, the SCA is selected as the optimization approach. The main goal of this research is to minimize the equivalent carbon dioxide emissions of a distribution grid provided with BESUs and renewable energy resources. Numerical results in the IEEE 33-bus grid demonstrate the effectiveness of the proposed leader-follower optimizer when compared to the continuous genetic algorithm, the particle swarm optimizer, and the vortex search algorithm.