Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm

Irnanda Priyadi; Novalio Daratha; Teddy Surya Gunawan; Kalamullah Ramli; Febrian Jalistio; Hazlie Mokhlis

doi:10.31436/iiumej.v26i1.3537

Authors

Irnanda Priyadi University of Indonesia
Novalio Daratha University of Bengkulu https://orcid.org/0000-0002-7714-4104
Teddy Surya Gunawan International Islamic University Malaysia https://orcid.org/0000-0003-3345-4669
Kalamullah Ramli University of Indonesia https://orcid.org/0000-0002-0374-4465
Febrian Jalistio University of Bengkulu
Hazlie Mokhlis University of Malaya https://orcid.org/0000-0002-1166-1934

DOI:

https://doi.org/10.31436/iiumej.v26i1.3537

Keywords:

contingency analysis, contingency ranking, sin cos algorithm, metaheuristic technique, nature inspired

Abstract

Ensuring the reliability and sustainability of power systems is essential for maintaining efficient and uninterrupted operations, especially under varying load conditions and potential faults. This study tackles the critical task of contingency ranking by evaluating the severity of disturbances caused by transmission line disconnections. Such evaluations enable power system operators to make informed and strategic decisions during real-time scenarios. A novel approach utilizing the Modified Sine Cosine Algorithm (MSCA), a nature-inspired metaheuristic optimization technique, is proposed to resolve (N-1) contingency rankings efficiently. The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. Results demonstrate that MSCA achieves a high capture ratio of 96.67%, explores only 8.33 × 10??% of the search space, and requires a processing time of 3.69 seconds. Compared with established methods such as Ant Colony Optimization (ACO) and Genetic Algorithm (GA), MSCA exhibits superior computational efficiency while maintaining competitive accuracy. These findings underline the potential of MSCA in real-time applications where speed and precision are critical. By closely matching manual contingency rankings, the proposed method integrates reliability assessment and optimization techniques, offering practical value for improving system resilience and reducing risks associated with disruptions. This research advances state-of-the-art power system reliability assessment and optimization approaches, providing operators and planners with a robust tool for addressing complex contingency challenges.

ABSTRAK: Memastikan keandalan dan kelestarian sistem tenaga elektrik adalah penting untuk mengekalkan operasi yang cekap dan tidak terganggu, terutamanya dalam menghadapi keadaan beban yang berubah-ubah dan kemungkinan kerosakan. Kajian ini menangani tugas kritikal dalam perangkingan kontingensi dengan menilai tahap keparahan gangguan yang disebabkan oleh pemutusan talian penghantaran. Penilaian sebegini membolehkan pengendali sistem tenaga membuat keputusan yang berinformasi dan strategik dalam senario masa nyata. Pendekatan baharu yang menggunakan Modified Sine Cosine Algorithm (MSCA), satu teknik pengoptimuman metaheuristik yang diilhamkan oleh alam, dicadangkan untuk menyelesaikan perangkingan kontingensi (N-1) dengan cekap. Kaedah MSCA ini disahkan menggunakan kes ujian IEEE 30-bus dengan memberi tumpuan kepada penalaan parameter optimum untuk saiz populasi, iterasi, dan pemboleh ubah utama. Keputusan menunjukkan bahawa MSCA mencapai nisbah tangkapan yang tinggi sebanyak 96.67%, hanya meneroka 8.33 × 10??% daripada ruang pencarian, dan memerlukan masa pemprosesan sebanyak 3.69 saat. Berbanding dengan kaedah sedia ada seperti Ant Colony Optimization (ACO) dan Genetic Algorithm (GA), MSCA menunjukkan kecekapan pengiraan yang unggul sambil mengekalkan ketepatan yang kompetitif. Penemuan ini menekankan potensi MSCA dalam aplikasi masa nyata di mana kelajuan dan ketepatan adalah kritikal. Dengan hasil yang hampir menyamai perangkingan kontingensi manual, kaedah yang dicadangkan ini mengintegrasikan penilaian keandalan dan teknik pengoptimuman, memberikan nilai praktikal untuk meningkatkan daya tahan sistem dan mengurangkan risiko yang berkaitan dengan gangguan. Penyelidikan ini memajukan pendekatan terkini dalam penilaian keandalan sistem tenaga dan pengoptimuman, menyediakan pengendali dan perancang dengan alat yang kukuh untuk menangani cabaran kontingensi yang kompleks.

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