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Hybrid manta ray foraging and sine cosine algorithm for managing power transmission congestion influenced by wind energy.

Created on 06 Sep 2025

Authors

Susovan Dutta, Bishaljit Paul, Barnali Kundu, Chandan Kumar Chanda, Kaushik Paul, Pampa Sinha, Hassan Abdurrahman Shuaibu, Taha Selim Ustun

Published in

Scientific reports. Volume 15. Issue 1. Pages 32373. Sep 05, 2025. Epub Sep 05, 2025.

Abstract

This research work proposes a hybrid Manta ray Forging Optimization- Sine Cosine Algorithm (MRFO-SCA) for Congestion Management (CM) that addresses the power system transmission line congestion cost challenges with the integration of Wind Energy System (WES). The proposed method focuses on two key objectives: first, identifying the most influential bus within the power system using the Bus Sensitivity Factor (BSF) to optimally place a wind power source, thereby impacting the power flow in overloaded lines. Second, MRFO-SCA has been developed for optimal power rescheduling of the generators to alleviate congestion while minimizing the congestion cost. The hybrid MRFO-SCA has been formulated by integrating SCA into the MRFO that enhances the exploration and exploitation phases in MRFO leading to the rapid discovery of the global optima. MRFO-SCA has been verified on benchmark functions that have delivered appreciable results. The effectiveness of the proposed approach has been assessed and validated using the IEEE-30 bus system. Simulation results indicate that incorporating WES with MRFO-SCA has led to a reduction in congestion costs by 18.45%, 15.68%, 10.34%, 9.72%, 5.46%, and 1.57% as compared to several recent optimization techniques. A comparative evaluation demonstrates that MRFO-SCA outperforms other methods in terms of congestion cost reduction, system loss minimization, bus voltage improvement, faster convergence, and reduced computational time, making it a more efficient and accurate solution for CM.

PMID:
40913045
Bibliographic data and abstract were imported from PubMed on 06 Sep 2025.

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