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10.3390-en15134847 |
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|a 19961073 (ISSN)
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|a A Fuzzy-PSO-PID with UPFC-RFB Solution for an LFC of an Interlinked Hydro Power System
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|b MDPI
|c 2022
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|z View Fulltext in Publisher
|u https://doi.org/10.3390/en15134847
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|a An LFC plays a vital part in passing on quality electric energy to energy consumers. Furthermore, with cutting-edge designs to move to modern and pollution-free energy generation, it may be conceivable to have a major hydropower in the future. Hydro plants are not suitable for continuous load alteration due to the large response time of hydroturbines. Hence, this paper shows a novel control design for an LFC of a hydro-hydro interlinked system based on joint actions of fuzzy logic with PID effectively optimized through particle swarm optimization (PSO) resulting in a Fuzzy-PSO-PID. The outcome of Fuzzy-PSO-PID is evaluated for step load variation in one of the regions of hydropower, and the outcomes of Fuzzy-PSO-PID are compared with a recently published LFC with respect to integral time absolute error (ITAE) value, values of PID, and graphical outcomes to show the impact of the proposed LFC action. The numerical results show that the ITAE value (0.002725) obtained through the proposed design is minimum in comparison to error values achieved through other LFC actions, and the pickup values obtained on these error values are considered to achieve the desired LFC. However, there is still scope for LFC enhancement as responses of hydropower are sluggish with higher oscillations; hence the UPFC and RFB are integrated into the interlinked hydro-hydro system, and the application outcomes are evaluated again considering the non-linearity, standard load alteration, random load pattern, and in view of parametric alterations. It is seen that the ITAE value reduces to 0.002471 from 0.002725 when UPFC is connected to the tie-line, and it further reduces to 0.001103 when a UPFC-RFB combination is used with Fuzzy-PSO-PID for a hydro leading system. The positive impact of the UPFC-RFB for hydropower is also seen from the application results. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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|a ACE
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|a Computer circuits
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|a Electric control equipment
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|a Electric frequency control
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|a Error values
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|a Errors
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|a FACTS
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|a Free energy
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|a fuzzy logic
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|a Fuzzy logic
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|a Fuzzy particle swarm
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|a Fuzzy-Logic
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|a Hydroelectric power
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|a LFC
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|a Particle swarm
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|a Particle swarm optimization
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|a Particle swarm optimization (PSO)
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|a Proportional control systems
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|a PSO
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|a RFB
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|a Swarm optimization
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|a Three term control systems
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|a UPFC
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|a Bokoro, P.N.
|e author
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|a Joshi, M.
|e author
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|a Krishnan, N.
|e author
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|a Sharma, G.
|e author
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|t Energies
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