A new approach for system‐wide power system frequency model validation via measurement data

Abstract

Models are commonly used for various power system studies. This article presents a new framework to estimate and validate the parameters of the turbine-governor and also the load model in a multi-machine power system environment. The proposed method utilizes the center of inertia frequency and generating unit signals (especially active power) recorded by measurement devices to validate the parameters. The objective function is to minimize the total squared error between the simulated and the measured responses for some events. Particle swarm optimization is used to estimate the parameters. The accuracy of the estimated parameters is investigated through sensitivity analysis. Moreover, in order to improve the efficiency of the identification procedure for large-scale networks, a new scheme is proposed, which is based on the impact of each estimated parameter during the simulation time frames. The simulation results on the IEEE 9-bus and IEEE 118-bus systems show the validity and benefit of the proposed method.

Demand response planning in capacity market using microgrid

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