Random Vector Functional Link Network Optimized by Jaya Algorithm for Transient Stability Assessment of Power Systems. (7th December 2020)

• Record Type: Journal Article
• Authors: Pan, Jianhong; Fan, Jiashu; Dong, Aidi; Li, Yang
• Other Names: Hong Ying-Yi Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2020(2020)
• Publication Date: 2020-12-07
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2020/8895022
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : A novel transient stability assessment (TSA) approach using random vector functional link (RVFL) network optimized by Jaya algorithm, called Jaya-RVFL, is proposed for power systems in this paper. First, by extracting system-level features from phasor measurement unit (PMU) measurements as predictors, an RVFL-based TSA model is proposed. In order to improve the performance of RVFL classifiers, a quantile scaling approach is utilized to optimize the randomization range of input weights via the Jaya algorithm. The simulation results on IEEE 39-bus system and a real-world power system show that the presented method outperforms other popular methods comprising multilayer perception, probabilistic neural network, and support vector machine.