Neurogenetic approach for real-time damping of low-frequency oscillations in electric networks. (May 2020)

• Record Type: Journal Article
• Authors: Shahriar, Mohammad Shoaib; Shafiullah, Md; Rana, Md Juel; Ali, Amjad; Ahmed, Ashik; Rahman, Syed Masiur
• Is Part Of: Computers & electrical engineering. Volume 83(2020)
• Publication Date: 2020-05
• Subjects: Flexible alternating current (AC) transmission systems (FACTS) -- Low-frequency oscillations (LFO) -- Neurogenetic model -- Power system stability -- Static synchronous compensator (STATCOM) -- Unified power flow controller (UPFC); Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106600
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Proposed intelligent neuro-genetic approaches damp out LFO in electric networks. Standard statistical indices validate the efficacy of the proposed technique. Results comparison confirmed the superiority of the proposed approach over others. Abstract: Low-frequency oscillations should be dealt with extreme care for secure electric networks. This paper tunes the critical parameters of power system stabilizers in three different electric networks in real-time, employing the neurogenetic approach to damp out the low-frequency oscillations. The first network is a single machine infinite bus power system equipped with a power system stabilizer. Besides, the second and third networks are coordinated with second-generation flexible alternating current transmission system devices, namely a unified power flow controller and static synchronous compensator in coordination with power system stabilizers, respectively. The investigation of eigenvalue and minimum damping ratio analyses for different loading conditions proves the efficiency of the proposed approach. Additionally, the time-domain simulation comparison shows the superiority of the proposed approach over the conventional method. Besides, the satisfactory values of the statistical performance measures give confidence to the proposed approach in predicting power system stabilizer parameters and thus mitigating the low-frequency oscillations in real-time.