This paper uses the eigenvalue analysis approach to observe the impact of load models on an unstable low frequency oscillation damping, which recently occurred in the Taiwan power system. In order to enhance oscillation damping, the effect of load models on power system stabilizers is also investigated. Three kinds of the derived load models (a dynamic model, a composite model, and an exponential model) based on the component approach with the measured characteristics of power system loads are used in this paper. Time simulation results are extensively used to verify the eigenvalue analysis results with and without power system stabilizers. One set of field test data obtained from the Taiwan power nuclear plant with power system stabilizers is used to determine which load model provides a more accurate result in enhancement of oscillation damping. Depending on the results, the effect of load models on electromechanical oscillation damping with and without power system stabilizers is verified.

The effect of load models on unstable low-frequency oscillation damping in Taipower system experience w/wo power system stabilizers

In the developed artificial neural network, those system variables which play an important role in steady-state stability, such as generator outputs and power system stabilizer parameters, are used as the inputs. The output of the neural net provides the information on steady-state stability. Once the connection weights of the neural network have been learned using a set of training data derived offline, the neural net can be applied to analyze the steady-state stability of the system in real-time situations where the operating conditions change with time. To demonstrate the effectiveness of the proposed neural net, steady-state stability analysis is performed on a synchronous generator connected to a large power system. It is found that the proposed neural net requires much less training time than the multilayer feedforward network with back-propagation-momentum learning algorithm. It is also concluded from test results that correct stability assessment can be achieved by the neural network. >

Synchronous machine steady-state stability analysis using an artificial neural network

Application of static var system auxiliary controllers to improve the transient performance of series compensated long transmission lines

In this paper an attempt has been made to propose a new technique for selection of optimu m site of a power system stabilizer (PSS) to mitigate the small-signal stability problem in a mu ltimach ine power system. Study reveals that the PSS displaces the swing mode fro m its crit ical position to a more desirable position changing the response of the excitation system. Based on the change of the exciter transfer function with respect to the PSS transfer function, an Opt imu m PSS Location Index (OPLI) has been introduced and used to identify the best location of the PSS in a mu lt imachine system. The analysis of the effect of load on eigenvalues confirms that the prediction of best location of PSS by OPLI method is more effective in enhancing the small-signal stability of the system.

http://article.sapub.org/pdf/10.5923.j.eee.20120205.03.pdf

Selection of Optimum Location of Power System Stabilizer in a Multimachine Power System

In this paper an attempt has been made to propose a new technique for selection of optimum site of a power system stabilizer (PSS) to mitigate the small-signal stability problem in a multimachine power system. Study reveals that the PSS displaces the swing mode from its critical position to a more desirable position changing the response of the excitation system. Based on the change of the exciter transfer function with respect to the PSS transfer function, an optimum PSS location index (OPLI) has been introduced and used to identify the best location of the PSS in a multimachine system. The analysis of the effect of load on eigenvalues confirms that the prediction of best location of PSS by OPLI method is more effective in enhancing the small-signal stability of the system.

	 

	Key words: Critical swing mode, optimum PSS location index, sensitivity of PSS effect, small signal stability.

/pdf/selection-of-optimum-location-of-power-system-stabilizer-in-51k9787u53.pdf

Selection of optimum location of power system stabilizer in a multimachine power system

The dynamic stability improvement of a longitudinal power system using a power system stabilizer (PSS) and a static VAr (reactive volt-ampere) compensator (SVC) is reported. An analytical approach is developed for the determination of PSS parameters. The effect of static VAr compensators installed at several different locations along 345 kV trunk lines on system responses is examined. Results from time-domain simulations indicate that the PSS and the SVC are very effective in damping system oscillations. >

Liu Chuan-Sheng

Papers

Application of power system stabilizers and static VAr compensators on a longitudinal power system