System identification techniques for obtaining linear models of large power systems with controllable devices from noisy measurements

QC 20110712
This paper deals with the use of system identification techniques for estimating low-order black-box state-space models formodal analysis. It presents a method to estimate state-space models for large power systems with many controllable devices from noisy measurements. To excite the system low-energy pulses generated by the controllable devices are used. The input signals are the controllable set-points of the devices, the output signals are the speed signals of some generators obtained from Phasor Measurement Units (PMU). The Subspace State-Space System Identification (N4SID) and Prediction Error Method (PEM) are compared in sense of robustness using measurement with different signal to noise ratios noisy measurements. The method is applied in an extended version of the Cigré Nordic 32-bus test system. This model approach can be used directly for the design of a centralized controller coordinating the controllable devices with the aim to increase the damping in the system.

TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Annan elektroteknik och elektronik hsv//swe
ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering hsv//eng
Black boxes
Extended versions
Input signal
Large power systems
Linear model
Low energies
Model approach
Noisy measurements
Output signal
Phasor measurement unit
Prediction error method
Setpoints
Speed signal
State space systems
State-space models
System identification techniques
Test systems
Error analysis
Signal to noise ratio
Stress analysis
System theory
Units of measurement
Identification (control systems)
Electric power engineering
Elkraftteknik

In:2010 IREP Symposium - Bulk Power System Dynamics and Control - VIII, IREP20109781424474677

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