PNNL

Abstract

Maintaining good quality of power plant stability models is of critical importance to ensure the secure and economic operation and planning of today’s power grid with its increasing stochastic and dynamic behavior. According to North American Electric Reliability (NERC) standards, all generators in North America with capacities larger than 10 MVA are required to validate their models every five years. Validation is quite costly and can significantly affect the revenue of generator owners, because the traditional staged testing requires generators to be taken offline. Over the past few years, validating and calibrating parameters using online measurements including phasor measurement units (PMUs) and digital fault recorders (DFRs) has been proven to be a cost-effective approach. In this paper, an innovative open-source tool suite is presented for validating power plant models using PPMV tool, identifying bad parameters with trajectory sensitivity analysis, and finally calibrating parameters using an ensemble Kalman filter (EnKF) based algorithm. The architectural design and the detailed procedures to run the tool suite are presented, with results of test on a realistic hydro power plant using PMU measurements for 12 different events. The calibrated parameters of machine, exciter, governor and PSS models demonstrate much better performance than the original models for all the events and show the robustness of the proposed calibration algorithm.