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 Journal of Statistics and Management Systems cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0014·ISSN (Print): 0972-0510
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The Journal of Statistics and Management Systems (JSMS) is a world leading journal publishing high quality, rigorously peer-reviewed original research on theoretical and applied statistics and management systems since 1998. The scope is intentionally broad, but papers must make a novel contribution to the field to be considered for publication. Topics include, but are not limited to, the following: • Statistics • Applied Statistics • Industrial Statistics • Statistical Inference • Interdisciplinary role of Statistics • Actuarial Sciences • Decision Sciences • Managerial Aspects • Management Sciences • Management Information Systems

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Open Access Research Article

Optimal fractional SSSC damping action for variable wind penetrations

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pp. 43–52Vol. 26Issue 1December 2022DOI: 10.47974/JSMS-946XML
Published Online:
31 Dec 2022
Article type:
Research Article
Language:
EN
Article no.:
/JSMS-946
Pages:
43–52

Abstract

An optimal fractional SSSC based control action has been proposed in this work for enhancing small signal stability of power system pertaining to intermittent variations in wind penetrations. The parameters of controllers are tuned by sailfish algorithm and ITAE based objective function has been chosen for minimization problem. A three machine system has been considered in this work with different operating conditions and step with random variations in wind penetrations have been executed with different machines and subject to which the system response and eigen values are analyzed. Based on system response it is observed that subject to intermittent variations in wind source the small signal stability is hampered due to increased power system oscillations and by properly tuning the fractional lead-lag control action based on static synchronous series compensator. These oscillations can be damped efficiently. The performance of proposed sailfish algorithm (SFA) tuned SSSC controlled action has been compared with PSO and DE algorithms subject to different case studies.

Keywords

Subject Classifications

37N35

References

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