Structured identification for network reconstruction of RC-models (Q826856)

The detailed physical models in various applications, including the state of the art electric and thermal grids integration, requires consistent computational resources in order to perform both the simulation and the optimization. Model simplification techniques, such as the resistance-capacitance (RC) networks provides the reasonable accuracy, number of parameters and computational effort. This paper adresses the inverse problem of recovering the network connection structure from measured input-output data. The computational experiments demonstrates the efficiency of proposed recovering method.