Spider wasp optimizer-optimized cascaded fractional-order controller for load frequency control in a photovoltaic-integrated two-area system

The integration of photovoltaic (PV) systems into traditional power grids introduces significant challenges in maintaining system stability, particularly in multi-area power systems. This study proposes a novel approach to load frequency control (LFC) in a two-area power system, where one area is po...

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Bibliographic Details
Main Authors: Ekinci, Serdar, Izci, Davut, Turkeri, Cebrail, Mohd Ashraf, Ahmad
Format: Article
Language:English
Published: MDPI 2024
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/44144/
http://umpir.ump.edu.my/id/eprint/44144/1/Spider%20wasp%20optimizer-optimized%20cascaded%20fractional-order.pdf
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Summary:The integration of photovoltaic (PV) systems into traditional power grids introduces significant challenges in maintaining system stability, particularly in multi-area power systems. This study proposes a novel approach to load frequency control (LFC) in a two-area power system, where one area is powered by a PV grid and the other by a thermal generator. To enhance system performance, a cascaded control strategy combining a fractional-order proportional–integral (FOPI) controller and a proportional–derivative with filter (PDN) controller, FOPI(1+PDN), is introduced. The controller parameters are optimized using the spider wasp optimizer (SWO). Extensive simulations are conducted to validate the effectiveness of the SWO-tuned FOPI(1+PDN) controller. The proposed method demonstrates superior performance in reducing frequency deviations and tie-line power fluctuations under various disturbances. The results are compared against other advanced optimization algorithms, each applied to the FOPI(1+PDN) controller. Additionally, this study benchmarks the SWO-tuned controller against recently reported control strategies that were optimized using different algorithms. The SWO-tuned FOPI(1+PDN) controller demonstrates superior performance in terms of faster response, reduced overshoot and undershoot, and better error minimization.