Abstract: A computer-implemented method for solar energy disaggregation at a node of a distribution system includes obtaining first data including samples of averaged net power measured by a meter installed at the node and second data including samples of solar irradiation local to the node averaged over intervals temporally correlated with the first data. A physics-based model of the node is trained using the first and second data, to optimize a set of model parameters. The physics-based model is defined such that an average net power includes a composite of an average solar generation and an average power consumption at the node and the average solar generation is modeled as a function of an average solar irradiation. An aggregate solar generation at the node is estimated/predicted from actual irradiation data/irradiation forecast data local to the node using a model parameter optimized by the training.

Abstract: System and method simulate power distribution system reconfigurations for multiple contingencies. Decision tree model is instantiated as a graph with nodes and edges corresponding to simulated outage states of one or more buses in the power distribution system and simulated states of reconfigurable switches in the power distribution system, Edges related to each outage are disconnected. A reconfiguration path is determined with a plurality of switches reconfigured to a closed state by an iteration of tree search algorithms. A simulation estimates feeder cable and transformer loading and bus voltages on the reconfigured path for comparing against constraints including system capacity ratings and minimum voltage.