Coherency Identification of Generators Using a PAM Algorithm for Dynamic Reduction of Power Systems

Abstract

This paper presents a new coherency identification method for dynamic reduction of a power system. To achieve dynamic reduction, coherency-based equivalence techniques divide generators into groups according to coherency, and then aggregate them. In order to minimize the changes in the dynamic response of the reduced equivalent system, coherency identification of the generators should be clearly defined. The objective of the proposed coherency identification method is to determine the optimal coherent groups of generators with respect to the dynamic response, using the Partitioning Around Medoids (PAM) algorithm. For this purpose, the coherency between generators is first evaluated from the dynamic simulation time response, and in the proposed method this result is then used to define a dissimilarity index. Based on the PAM algorithm, the coherent generator groups are then determined so that the sum of the index in each group is minimized. This approach ensures that the dynamic characteristics of the original system are preserved, by providing the optimized coherency identification. To validate the effectiveness of the technique, simulated cases with an IEEE 39-bus test system are evaluated using PSS/E. The proposed method is compared with an existing coherency identification method, which uses the K-means algorithm, and is found to provide a better estimate of the original system.

Taxonomy of coherency detection and coherency‐based methods for generators grouping and power system partitioning

“…These features include phase angle, normalised frequency and acceleration of each generator at a certain time instant. However, a more appropriate criterion for assessing the similarity of signals is the Euclidean distance between the samples in the signals [27, 78–85]. For example, Kamwa et al [27] have used a combination of Euclidean distance between the variation of bus angle and frequency signals as in the equation below: Another way for assessing the similarity between signals is to calculate the correlation between each pair of signals.…”

A Novel Bio-Inspired Technique for Rapid Real-Time Generator Coherency Identification

“…This can be dramatically reduced with dedicated and more advanced processors. The New England 39-Bus test system is widely used for studying the complex situations in multiarea power system [26], [27], such as generator coherency presented by inter and intraarea oscillations [9], [28], [29]. To demonstrate the performance of our technique on more complicated generator coherency scenario, in the last case study we implement the simulations on a modified IEEE 118-bus test system, which consists of C = 20 generators.…”