A dynamic equivalent using modal coherency and frequency response

Oirsouw, P.M. van

doi:10.1109/59.49119

Cited by 18 publications

(2 citation statements)

References 7 publications

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“…However, since power systems are becoming increasingly complex, the demand for more accurate generator grouping algorithms is increasing. Compared with the existing methods of [12] and [13], the advantages and improvements of the proposed technique can be summarized as follows:…”

Section: Discussionmentioning

confidence: 99%

“…Existing algorithms are also subject to some limitations when applied to the dynamic reduction of modern power systems, since the complexity of power systems has recently increased with the number of generators. The grouping algorithm proposed by Van Oirsouw [12] has several drawbacks arising from its sequential procedure, despite its advantages of speed and simple application. When this algorithm is used, the first generator group becomes the largest group in the majority of cases, and a generator can be grouped with other generators with which it is hardly coherent, since the group in which a generator is placed is determined solely by comparison with the last generator assigned to that group.…”

Section: Introductionmentioning

confidence: 99%

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

2012

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%