Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm
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 cau...
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IIUM Press, International Islamic University Malaysia
2025-01-01
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| Series: | International Islamic University Malaysia Engineering Journal |
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| Online Access: | https://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/3537 |
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| author | Irnanda Priyadi Novalio Daratha Teddy Surya Gunawan Kalamullah Ramli Febrian Jalistio Hazlie Mokhlis |
| author_facet | Irnanda Priyadi Novalio Daratha Teddy Surya Gunawan Kalamullah Ramli Febrian Jalistio Hazlie Mokhlis |
| author_sort | Irnanda Priyadi |
| collection | DOAJ |
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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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| format | Article |
| id | doaj-art-1cac6ccda4d54980a791ad02d72e5144 |
| institution | Kabale University |
| issn | 1511-788X 2289-7860 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IIUM Press, International Islamic University Malaysia |
| record_format | Article |
| series | International Islamic University Malaysia Engineering Journal |
| spelling | doaj-art-1cac6ccda4d54980a791ad02d72e51442025-01-10T12:40:35ZengIIUM Press, International Islamic University MalaysiaInternational Islamic University Malaysia Engineering Journal1511-788X2289-78602025-01-0126110.31436/iiumej.v26i1.3537Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine AlgorithmIrnanda Priyadi0Novalio Daratha1https://orcid.org/0000-0002-7714-4104Teddy Surya Gunawan2https://orcid.org/0000-0003-3345-4669Kalamullah Ramli3https://orcid.org/0000-0002-0374-4465Febrian Jalistio4Hazlie Mokhlis5https://orcid.org/0000-0002-1166-1934University of IndonesiaUniversity of Bengkulu International Islamic University Malaysia University of Indonesia University of BengkuluUniversity of Malaya 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. https://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/3537contingency analysiscontingency rankingsin cos algorithmmetaheuristic techniquenature inspired |
| spellingShingle | Irnanda Priyadi Novalio Daratha Teddy Surya Gunawan Kalamullah Ramli Febrian Jalistio Hazlie Mokhlis Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm International Islamic University Malaysia Engineering Journal contingency analysis contingency ranking sin cos algorithm metaheuristic technique nature inspired |
| title | Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm |
| title_full | Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm |
| title_fullStr | Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm |
| title_full_unstemmed | Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm |
| title_short | Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm |
| title_sort | optimizing n 1 contingency rankings using a nature inspired modified sine cosine algorithm |
| topic | contingency analysis contingency ranking sin cos algorithm metaheuristic technique nature inspired |
| url | https://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/3537 |
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