Pratyasa Bhui

Real-Time Prediction and Control of Transient Stability Using Transient Energy Function

Real-time prediction of transient stability after a fault can potentially prevent occurrence of grid blackouts. In this paper, the measurement data obtained from phasor measurement unit (PMU) located at generator buses are used to compute the transient stability margin after a fault has occurred. For evaluating various control actions to be taken to stabilize severely disturbed and unstable generators, the stability margin is estimated using the transient energy function (TEF) technique. A look-up table of various modes of disturbance (MOD) is built offline for different fault locations and post fault topology. Following an actual fault, the most probable MODs are ranked by matching the “normalized” kinetic energy with the look-up table. The correct MOD is then chosen based on the lowest normalized potential energy margin and the Controlling Unstable Equilibrium Point (CUEP) is calculated. This technique overcomes previously reported difficulties in finding the CUEP in real-time applications. With knowledge of prefault operating condition obtained from SCADA and the information of the tripped line by analyzing the PMU data, the first swing transient stability margin is computed. The amount of control action needed is subsequently calculated. The proposed method has been tested on the IEEE 39 Bus Test System.

Application of Recurrence Quantification Analysis to Power System Dynamic Studies

Recurrence quantification analysis (RQA) is a nonlinear data analysis technique that can quantify the number and duration of a dynamical system of being in nearly the same area in phase space trajectory. This paper proposes three applications of RQA to analyse power system dynamics. These are denoising of PMU data, localization of power system events, and transient stability contingency ranking of power system. All three applications have been demonstrated using a multimachine test system.

Online Identification of Tripped Line for Transient Stability Assessment

Identification of post-fault topology is critical to not only cascaded outage prevention but also prediction of post-fault dynamic behavior. Existing methods for identifying the tripped lines rely on steady state SCADA/PMU measurements, and therefore fail to accomplish their task within fractions of a second. This limits their application to online transient stability assessment. This paper presents a method for online identification of post-fault topology on the basis of information of the pre-fault operating conditions and synchronized measurements at all generator buses. The proposed technique identifies the tripped line with negligible delay, before the system reaches steady state. An innovative index, which represents the normalized kinetic energy gained by generators immediately after the fault, is used to minimize the search set of possible tripped lines. For every candidate line, the generator output powers are calculated considering the line as tripped, and the minimum error between the measured and the calculated generator powers is used to finally identify the tripped line. The IEEE 39-bus system and a 246-bus North Indian Grid representation are used to show the effectiveness of the method.

Estimation of Inherent Governor Dead-Band and Regulation Using Unscented Kalman Filter

The inclusion of the governor droop and dead-band in dynamic models helps to reproduce the measured frequency response accurately and is a key aspect of model validation. Often, accurate and detailed turbine-governor information are not available for various units in an area control centre. The uncertainty in the droop also arise from the nonlinearity due to the governor valves. The droop and dead-band are required to tune the secondary frequency bias factors, and to determine the primary frequency reserve. Earlier research on droop estimation did not adequately take into account the effect of dead-band and other nonlinearities. In this paper, unscented Kalman filter is used in conjunction with continuously available measurements to estimate the governor droop and the dead-band width. The effectiveness of the approach is demonstrated through simulations.

Feasibility study of applicability of recurrence quantification analysis for clustering of power system dynamic responses

A methodology based on Recurrence Quantification Analysis (RQA) for the clustering of generator dynamic behavior is presented. RQA is a nonlinear data analysis method, which is used in this paper to extract features from measured generator rotor angle responses that can be used to cluster generators in groups with similar oscillatory behavior. The possibility of extracting features relevant to damping and frequency of oscillations present in power systems is studied. The k-Means clustering algorithm is further used to cluster the generator responses in groups exhibiting well or poorly damped oscillations, based on the extracted features from RQA. The effectiveness of RQA is investigated using simulated responses from a modified version of the IEEE 68 bus network, including renewable energy resources.

A unified method for economic dispatch with valve point effects

This paper proposes a new deterministic approach to solve economic dispatch problem with non-convex cost function. Earlier, several meta heuristic approaches were applied to solve this problem but these technique does not guarantee the global solution, whereas the parameters of the methods need to be tuned before using and these parameters depend on the system operating condition. First, multiple minima are detected. Power in between two consecutive minima is taken as a step. Starting from minimum generation, power is increased in steps until demand is met. In case of last step, most efficient step is selected keeping the active power balance under consideration. Proposed method has been tested on 40 unit test system and compared with other methods.