Advanced Performance Metrics and Sensitivity Analysis for Model Validation and Calibration

Abstract

<pre>High quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMU measurements, measurement-based approach for model validation has gained significant prominence. Currently, the model validation results are analyzed by visually comparing real--world PMU measurements with the model-based response measurements, and parameter adjustments rely mostly on engineering experience. This paper proposes advanced performance metrics to systematically quantify the generator dynamic model validation results by separately taking into consideration slow governor response and comparatively fast oscillatory response. The performance metric for governor response is based on the step response characteristics of a system and the metric for oscillatory response is based on the response of generator to each system mode calculated using modal analysis. The proposed metrics in this paper is aimed at providing critical information to help with the selection of parameters to be tuned for model calibration by performing enhanced sensitivity analysis, and also help with rule-based model calibration. Results obtained using both simulated and real-world measurements validate the effectiveness of the proposed performance metrics and sensitivity analysis for model validation and calibration.</pre>

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

“…The incremental error of each time frame, according to (11), is given in Table 6 and Figure 11. Based on experiences, 5% incremental error is considered as the threshold.…”

“…Based on experiences, 5% incremental error is considered as the threshold. Equation (11) represents the incremental error value in percent for adding the nth time frame. To determine the effective time frames for the ramp rate constraints and dead-bands, the incremental error is calculated from the first simulation time frame and for the droops, the incremental error is calculated from the last one.…”

“…Based on the results, the first 20 seconds of the simulation time are selected as the effective time frames for the ramp rate constraints. Similar to the ramp rate, the effective time frames of dead bands and droops are also determined through (11).…”

“…In these studies, the whole system is considered in the simulation, and system elements are validated simultaneously while taking into account their mutual effects. 11 However, in such studies, only the most influential components models and parameters (usually based on a generic model for all components) 12 should be taken into consideration due to the complexity of the problem. The turbine-governor model is the most influential component of a generating unit affecting the power system dynamic frequency studies.…”