The smart grid is envisioned as a reconfigurable energy exchange network that is resilient to failures. An expected feature of the future smart grid is optimal power distribution from energy producers to consumers, also referred to as network operation planning. This entails allocating finite energy resources to customers in order to optimally satisfy all customer demands, subject to constraints on the topology of the graph. We model this problem as the Capacitated Spanning Forest Problem (CSF), namely the optimization problem of creating a spanning forest with a capacity constraint on each tree limiting its total weight. We present a new heuristic algorithm for solving CSF based on computing the minimum-cost maximum flow on the graph. Our algorithm outperforms state of the art approaches with respect to solution quality and running time.