期刊
ALEXANDRIA ENGINEERING JOURNAL
卷 61, 期 4, 页码 2841-2850出版社
ELSEVIER
DOI: 10.1016/j.aej.2021.08.007
关键词
Fuzzy Logic Controller (FLC); Self-Adaptive Learning Bat Algorithm (SALBA); Fuzzy based PSS (FPSS); Fuzzy based STATCOM (FSTATCOM)
This article investigates the coordination and optimization of fuzzy controllers for designing PSS and STATCOM controllers to improve power system stability. By using Self-Adaptive Learning Bat Algorithm, coordination between FSTATCOM and FPSS is achieved, and the effectiveness of coordinated fuzzy controllers is demonstrated in comparison with conventional design methods.
The low frequency oscillations have always been the main problem of power system and can lead to power angle instability, limiting the maximum power to be transmitted on tie-lines and system separation. For boosting power system stability limits, the most effectiveness way is to install supplementary excitation control, power system stabilizer (PSS) to add a supplementary feedback stabilizing signal into the automatic voltage regulator (AVR). This article investigates the coordination and optimization of fuzzy controllers for designing PSS and STATCOM controllers for more attenuation of power system fluctuations. The designed fuzzy controller replaces the STATCOM AC voltage regulator. Moreover, for more damping a fuzzy power system stabilizer (FPSS) is placed on all machines. Coordination between Fuzzy Based STATCOM (FSTATCOM) and FPSS is achieved by Self-Adaptive Learning Bat Algorithm (SALBA) in two stages. At first, scaling factors and then fuzzy sets of membership functions (MFs) will be tuned based on a performance index. To indicate the effectiveness of the proposed scheme, the coordinated optimized FPSS and FSTATCOM are compared with conventional design approaches like conventional PSS (CPSS) and proportional-integral controller based STATCOM (PISTATCOM). The simulations clearly demonstrate the effectiveness of the coordinated fuzzy controllers in terms of transient and dynamic stability. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.
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