High-performance computing for static security assessment of large power systems
Contingency analysis (CA) is one of the essential tools for the optimal design and security assessment of a reliable power system. However, its computational requirements rise with the growth of distributed generations in the interconnected power system. As CA is a complex and computationally intens...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-12-01
|
| Series: | Connection Science |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09540091.2023.2264537 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850224205454376960 |
|---|---|
| author | Venkateswara Rao Kagita Sanjaya Kumar Panda Ram Krishan P. Deepak Reddy Jabba Aswanth |
| author_facet | Venkateswara Rao Kagita Sanjaya Kumar Panda Ram Krishan P. Deepak Reddy Jabba Aswanth |
| author_sort | Venkateswara Rao Kagita |
| collection | DOAJ |
| description | Contingency analysis (CA) is one of the essential tools for the optimal design and security assessment of a reliable power system. However, its computational requirements rise with the growth of distributed generations in the interconnected power system. As CA is a complex and computationally intensive problem, it requires a fast and accurate calculation to ensure the secure operation. Therefore, efficient mathematical modelling and parallel programming are key to efficient static security analysis. This paper proposes a parallel algorithm for static CA that uses both central processing units (CPUs) and graphical processing units (GPUs). To enhance the accuracy, AC load flow is used, and parallel computation of load flow is done simultaneously, with efficient screening and ranking of the critical contingencies. We perform extensive experiments to evaluate the efficacy of the proposed algorithm. As a result, we establish that the proposed parallel algorithm with high-performance computing (HPC) computing is much faster than the traditional algorithms. Furthermore, the HPC experiments were conducted using the national supercomputing facility, which demonstrates the proposed algorithm in the context of N−1 and N−2 static CA with immense power systems, such as the Indian northern regional power grid (NRPG) 246-bus and the polish 2383-bus networks. |
| format | Article |
| id | doaj-art-524271d9ec41487b8a96a8e899d4f032 |
| institution | OA Journals |
| issn | 0954-0091 1360-0494 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Connection Science |
| spelling | doaj-art-524271d9ec41487b8a96a8e899d4f0322025-08-20T02:05:42ZengTaylor & Francis GroupConnection Science0954-00911360-04942023-12-0135110.1080/09540091.2023.22645372264537High-performance computing for static security assessment of large power systemsVenkateswara Rao Kagita0Sanjaya Kumar Panda1Ram Krishan2P. Deepak Reddy3Jabba Aswanth4National Institute of Technology WarangalNational Institute of Technology WarangalNational Institute of Technology WarangalIndian Institute of Technology KharagpurNational Institute of Technology WarangalContingency analysis (CA) is one of the essential tools for the optimal design and security assessment of a reliable power system. However, its computational requirements rise with the growth of distributed generations in the interconnected power system. As CA is a complex and computationally intensive problem, it requires a fast and accurate calculation to ensure the secure operation. Therefore, efficient mathematical modelling and parallel programming are key to efficient static security analysis. This paper proposes a parallel algorithm for static CA that uses both central processing units (CPUs) and graphical processing units (GPUs). To enhance the accuracy, AC load flow is used, and parallel computation of load flow is done simultaneously, with efficient screening and ranking of the critical contingencies. We perform extensive experiments to evaluate the efficacy of the proposed algorithm. As a result, we establish that the proposed parallel algorithm with high-performance computing (HPC) computing is much faster than the traditional algorithms. Furthermore, the HPC experiments were conducted using the national supercomputing facility, which demonstrates the proposed algorithm in the context of N−1 and N−2 static CA with immense power systems, such as the Indian northern regional power grid (NRPG) 246-bus and the polish 2383-bus networks.http://dx.doi.org/10.1080/09540091.2023.2264537contingency analysishigh-performance computinglarge power systemsn−1 contingencyn−2 contingencysecurity assessment |
| spellingShingle | Venkateswara Rao Kagita Sanjaya Kumar Panda Ram Krishan P. Deepak Reddy Jabba Aswanth High-performance computing for static security assessment of large power systems Connection Science contingency analysis high-performance computing large power systems n−1 contingency n−2 contingency security assessment |
| title | High-performance computing for static security assessment of large power systems |
| title_full | High-performance computing for static security assessment of large power systems |
| title_fullStr | High-performance computing for static security assessment of large power systems |
| title_full_unstemmed | High-performance computing for static security assessment of large power systems |
| title_short | High-performance computing for static security assessment of large power systems |
| title_sort | high performance computing for static security assessment of large power systems |
| topic | contingency analysis high-performance computing large power systems n−1 contingency n−2 contingency security assessment |
| url | http://dx.doi.org/10.1080/09540091.2023.2264537 |
| work_keys_str_mv | AT venkateswararaokagita highperformancecomputingforstaticsecurityassessmentoflargepowersystems AT sanjayakumarpanda highperformancecomputingforstaticsecurityassessmentoflargepowersystems AT ramkrishan highperformancecomputingforstaticsecurityassessmentoflargepowersystems AT pdeepakreddy highperformancecomputingforstaticsecurityassessmentoflargepowersystems AT jabbaaswanth highperformancecomputingforstaticsecurityassessmentoflargepowersystems |