Online calibration of power system model using time series measurement data

A power system comprising:

• one or more active generator subsystems connected to a power network,
• a number of measurement devices installed in the power network to dynamically measure electrical quantities associated with each of the active generator subsystems, and
• an online model calibration system for calibrating a power system model against the power system, the online model calibration system comprising:
• one or more processors, and
• a memory storing algorithmic modules executable by the one or more processors, the algorithmic modules comprising:
• a model approximator configured to, at each iteration in a series of iterations, generate a time-domain system model that at least locally approximates the power system model around a specified operating point, based on initial parameter values and current parameter values of a set of system parameters, wherein a model output of the time-domain system model is a function of a system state and an input signal and the system state is a function of the input signal,
• an objective evaluator configured to, at each iteration, to measure an error between a time series of the model output in response to the dynamic input signal and a time series of measurement signals obtained from the measurement devices that defines a response of the power system to the dynamic input signal, summed over a number of discretized points in time with a defined sampling interval, and
• a sequential optimizer configured to, at each iteration, adjust parameter values of at least a subset of the system parameters and the system state in a direction to minimize the measured error, wherein the sequential optimizer is constrained based on a discretization of the time-domain system model using the defined sampling interval,
• whereby, the power system model is calibrated against the power system based on final values of the system parameters after the series of iterations.