Araştırma Makalesi
BibTex RIS Kaynak Göster

Assesment of soft error sensitivity of power flow analysis

Yıl 2023, Cilt: 38 Sayı: 1, 579 - 590, 21.06.2022
https://doi.org/10.17341/gazimmfd.913867

Öz

Today’s power systems are large and interconnected to each other with many buses, lines, loads, and generators. Even the solution of a single snapshot of the system for specific conditions requires the solution of systems of equations with large sizes. Thus, to obtain the results in a reasonable time for large problems like electrical power flow simulations, modern large computational environments should be employed. However, because of the increasing number of components in the modern computational environment, the possibility of soft errors also increases. Soft errors can be defined as failures arising from several fluctuations due to x-rays, cosmic particle effects, etc. These types of errors usually appear at any time of computation as a bit-flip in any floating-point operations. In this paper, we will investigate the soft-error effects on large-scale power flow simulations. Generally, power flow calculations are performed by using Newton Raphson Method. The system is modeled by nonlinear equations and the solution process requires a linear solver is employed to take the inverse of the Jacobian matrix at each iteration. In this study, the soft-error sensitivity of the numerical methods used in load flow was examined, and the problems that may be encountered were revealed.

Kaynakça

  • Benacchio T., Bonaventura L., Altenbernd M., Cantwell C., Düben P., vd. Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction. International Journal of High Performance Computing Applications, SAGE Publications, 2021.
  • May T.C., Woods M. H., Alpha-Particle-Induced Soft Errors in Dynamic Memories, IEEE Trans. Elect. Dev., 26, 2, 1979.
  • Binder D., Smith E.C, Holman A.B, Satellite Anomalies from Galactic Cosmic Rays, IEEE Trans. Nucl. Sci., 22, 1166, 1975.
  • Van Gils, W., A Triple Modular Redundancy Technique Providing Multiple-Bit Error Protection Without Using Extra Redundancy, IEEE Transactions on Computers, vol. 35, no. 07, pp. 623-631, 1986.
  • Agullo E., Cools S., Yetkin, E. F., Giraud L., Schenkels N., Vanroose W., On Soft Errors in the Conjugate Gradient Method: Sensitivity and Robust Numerical Detection. SIAM J. Sci. Comput. 42(6): C335-C358, 2020.
  • Klenke A., Probability Theory, Springer, Londra, Birleşik Krallık, 2014.
  • Top 500 The List, http://top500.org, Erişim Tarihi: Nisan 11, 2021.
  • Cappello F, Geist A, Gropp W, Kale S, Kramer B., Toward Exascale Resilience : 2014 Update. The Exascale Resilience Problem. Tech. Rep., 2014.
  • Snir M, Wisniewski RW, Abraham Ja, Adve SV, Bagchi S, Balaji P, Belak J, Bose P, Cappello F, Carlson B, Chien Aa, Coteus P, DeBardeleben Na, Diniz PC, Engelmann C, Erez M, Fazzari S, Geist A, Gupta R, Johnson F, Addressing failures in exascale computing. International Journal of High Performance Computing Applications 28:129–173, 2014.
  • Powell, L. Power System Load Flow Analysis, McGraw-Hill, 2005.
  • H. Dag and A. Semlyen, "A new preconditioned conjugate gradient power flow," in IEEE Transactions on Power Systems, vol. 18, no. 4, pp. 1248-1255, Nov. 2003
  • Vorst HA, Iterative Krylov Methods for Large Linear Systems, Cambridge University Press, 2009.
  • Grama A., Sameh A., Parallel Algorithms in Computational Science and Engineering, Springer-Nature, Cham, İsviçre, 2020.
  • Elliott J, Hoemmen M, Mueller F., Exploiting data representation for fault tolerance. Journal of Computational Science 14:51 – 60, 2016.
  • Fiala D, Mueller F, Engelmann C, Riesen R, Ferreira K, Brightwell R. Detection and correction of silent data corruption for large-scale high-performance computing. In: SC ’12: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, pp 1–12, 2012.
  • Agullo E. et al., Hard Faults and Soft-Errors: Possible Numerical Remedies in Linear Algebra Solvers. In: Dutra I., Camacho R., Barbosa J., Marques O. (eds) High Performance Computing for Computational Science – VECPAR 2016. VECPAR 2016. Lecture Notes in Computer Science, vol 10150, 2017.
  • Yetkin E. F., Pişkin Ş., Soft error sensitivity of large scale CFD applications, 10th International Workshop on Parallel Matrix Algorithms and Applications, June, 2018, Zürih, İsviçre, 2018.
  • Adiga NR, Almasi G, etal, An overview of the bluegene/l super- computer. In: SC ’02: Proceedings of the 2002 ACM/IEEE Conference on Supercomputing, pp 60–60, 2002.
  • Lienig J, Bruemmer H, Reliability Analysis, Springer International Publishing, Cham, pp 45–73, 2017.
  • Carson E, Strakos Z, On the cost of iterative computations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020.
  • Saad, Y. Iterative Methods for Sparse Linear Systems Second Edition, SIAM, 2003.
  • Golub, G., Van Loan, C. F., Matrix Computations, The John Hopkins Univ. Press, 2013.
  • Du, P., Luszczek P., Dongarra, J., High Performance Dense Linear System Solver with Soft Error Resilience," 2011 IEEE International Conference on Cluster Computing, Austin, TX, pp. 272-280, 2011.
  • Yao, E., Zhang, J., Chen, M., Tan, G., Sun, N., Detection of soft-errors in LU decomposition with partial pivoting using algorithmic-based fault tolerance, Int. Journal of High Performance Comp. App., Vol:29, Issue:4, pp: 422-436, 2015.
  • Yetkin E. F., Ceylan O., Soft-error resiliency of power flow calculations, 52nd International Universities Power Engineering Conference (UPEC), Heraklion, Greece, 2017.
  • Cools S., Analyzing and improving maximal attainable accuracy in the communication hiding pipelined bicgstab method, Parallel Computing, 86:16 – 35, 2019.
  • Agullo, E., Cools, S., Yetkin, E. F., Giraud, L., Schenkels N., Vanroose, W., A complementary note on soft errors in the Conjugate Gradient method: the persistent error case. [Research Report] RR-9360, Inria Bordeaux Sud-Ouest. 2020.

Güç akışı analizinin geçici hata duyarlılığının değerlendirilmesi

Yıl 2023, Cilt: 38 Sayı: 1, 579 - 590, 21.06.2022
https://doi.org/10.17341/gazimmfd.913867

Öz

Günümüzün güç sistemleri detaylı modelleme ihtiyaçları nedeniyle çok büyük boyutlara ulaşabilmektedir ve belirli koşullar için sistemin tek bir anlık görüntüsünün çözümü bile büyük boyutlu denklem sistemlerinin çözümünü gerektirir. Bu nedenle de makul bir sürede sonuçları elde etmek için modern yüksek başarımlı hesaplama ortamları kullanılmalıdır. Bununla birlikte, yüksek başarımlı hesaplama ortamlarında artan bileşen sayısı nedeniyle, sessiz hata olasılığı da artar. Sessiz hatalar, x-ışınları, kozmik parçacık etkileri gibi nedenlerle cihaz bileşenlerinde oluşabilen çeşitli dalgalanmalardan kaynaklı arızalar olarak tanımlanabilir. Bu tür hatalar genellikle herhangi bir hesaplama anında herhangi bir kayan nokta işleminde yaşanan bir bit-kayması ile modellenebilir. Bu makalede, büyük ölçekli güç akışı simülasyonları üzerindeki sessiz hata etkileri incelenmektedir. Genel olarak yük akışı hesaplamaları, sistem doğrusal olmayan denklemlerle modellendiği için, Newton-Raphson yöntemi kullanılarak yapılır ve çözüm süreci, her yinelemede Jakobiyen matrisinin tersini almak için doğrusal bir çözücünün kullanılmasını gerektirir. Bu çalışmada, özellikle yenilenebilir enerji kaynaklarının sistemlere eklenmesi ile çok büyük boyutlara ulaşılabilen elektrik yük akış problemlerinde kullanılan matematiksel yöntemlerin sessiz-hatalara karşı hassasiyetleri incelenerek, karşılaşılabilecek sorunlar ortaya konulmuştur.

Kaynakça

  • Benacchio T., Bonaventura L., Altenbernd M., Cantwell C., Düben P., vd. Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction. International Journal of High Performance Computing Applications, SAGE Publications, 2021.
  • May T.C., Woods M. H., Alpha-Particle-Induced Soft Errors in Dynamic Memories, IEEE Trans. Elect. Dev., 26, 2, 1979.
  • Binder D., Smith E.C, Holman A.B, Satellite Anomalies from Galactic Cosmic Rays, IEEE Trans. Nucl. Sci., 22, 1166, 1975.
  • Van Gils, W., A Triple Modular Redundancy Technique Providing Multiple-Bit Error Protection Without Using Extra Redundancy, IEEE Transactions on Computers, vol. 35, no. 07, pp. 623-631, 1986.
  • Agullo E., Cools S., Yetkin, E. F., Giraud L., Schenkels N., Vanroose W., On Soft Errors in the Conjugate Gradient Method: Sensitivity and Robust Numerical Detection. SIAM J. Sci. Comput. 42(6): C335-C358, 2020.
  • Klenke A., Probability Theory, Springer, Londra, Birleşik Krallık, 2014.
  • Top 500 The List, http://top500.org, Erişim Tarihi: Nisan 11, 2021.
  • Cappello F, Geist A, Gropp W, Kale S, Kramer B., Toward Exascale Resilience : 2014 Update. The Exascale Resilience Problem. Tech. Rep., 2014.
  • Snir M, Wisniewski RW, Abraham Ja, Adve SV, Bagchi S, Balaji P, Belak J, Bose P, Cappello F, Carlson B, Chien Aa, Coteus P, DeBardeleben Na, Diniz PC, Engelmann C, Erez M, Fazzari S, Geist A, Gupta R, Johnson F, Addressing failures in exascale computing. International Journal of High Performance Computing Applications 28:129–173, 2014.
  • Powell, L. Power System Load Flow Analysis, McGraw-Hill, 2005.
  • H. Dag and A. Semlyen, "A new preconditioned conjugate gradient power flow," in IEEE Transactions on Power Systems, vol. 18, no. 4, pp. 1248-1255, Nov. 2003
  • Vorst HA, Iterative Krylov Methods for Large Linear Systems, Cambridge University Press, 2009.
  • Grama A., Sameh A., Parallel Algorithms in Computational Science and Engineering, Springer-Nature, Cham, İsviçre, 2020.
  • Elliott J, Hoemmen M, Mueller F., Exploiting data representation for fault tolerance. Journal of Computational Science 14:51 – 60, 2016.
  • Fiala D, Mueller F, Engelmann C, Riesen R, Ferreira K, Brightwell R. Detection and correction of silent data corruption for large-scale high-performance computing. In: SC ’12: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, pp 1–12, 2012.
  • Agullo E. et al., Hard Faults and Soft-Errors: Possible Numerical Remedies in Linear Algebra Solvers. In: Dutra I., Camacho R., Barbosa J., Marques O. (eds) High Performance Computing for Computational Science – VECPAR 2016. VECPAR 2016. Lecture Notes in Computer Science, vol 10150, 2017.
  • Yetkin E. F., Pişkin Ş., Soft error sensitivity of large scale CFD applications, 10th International Workshop on Parallel Matrix Algorithms and Applications, June, 2018, Zürih, İsviçre, 2018.
  • Adiga NR, Almasi G, etal, An overview of the bluegene/l super- computer. In: SC ’02: Proceedings of the 2002 ACM/IEEE Conference on Supercomputing, pp 60–60, 2002.
  • Lienig J, Bruemmer H, Reliability Analysis, Springer International Publishing, Cham, pp 45–73, 2017.
  • Carson E, Strakos Z, On the cost of iterative computations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020.
  • Saad, Y. Iterative Methods for Sparse Linear Systems Second Edition, SIAM, 2003.
  • Golub, G., Van Loan, C. F., Matrix Computations, The John Hopkins Univ. Press, 2013.
  • Du, P., Luszczek P., Dongarra, J., High Performance Dense Linear System Solver with Soft Error Resilience," 2011 IEEE International Conference on Cluster Computing, Austin, TX, pp. 272-280, 2011.
  • Yao, E., Zhang, J., Chen, M., Tan, G., Sun, N., Detection of soft-errors in LU decomposition with partial pivoting using algorithmic-based fault tolerance, Int. Journal of High Performance Comp. App., Vol:29, Issue:4, pp: 422-436, 2015.
  • Yetkin E. F., Ceylan O., Soft-error resiliency of power flow calculations, 52nd International Universities Power Engineering Conference (UPEC), Heraklion, Greece, 2017.
  • Cools S., Analyzing and improving maximal attainable accuracy in the communication hiding pipelined bicgstab method, Parallel Computing, 86:16 – 35, 2019.
  • Agullo, E., Cools, S., Yetkin, E. F., Giraud, L., Schenkels N., Vanroose, W., A complementary note on soft errors in the Conjugate Gradient method: the persistent error case. [Research Report] RR-9360, Inria Bordeaux Sud-Ouest. 2020.
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Emrullah Fatih Yetkin 0000-0003-1115-4454

Yayımlanma Tarihi 21 Haziran 2022
Gönderilme Tarihi 13 Nisan 2021
Kabul Tarihi 27 Şubat 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 38 Sayı: 1

Kaynak Göster

APA Yetkin, E. F. (2022). Güç akışı analizinin geçici hata duyarlılığının değerlendirilmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 38(1), 579-590. https://doi.org/10.17341/gazimmfd.913867
AMA Yetkin EF. Güç akışı analizinin geçici hata duyarlılığının değerlendirilmesi. GUMMFD. Haziran 2022;38(1):579-590. doi:10.17341/gazimmfd.913867
Chicago Yetkin, Emrullah Fatih. “Güç akışı Analizinin geçici Hata duyarlılığının değerlendirilmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 38, sy. 1 (Haziran 2022): 579-90. https://doi.org/10.17341/gazimmfd.913867.
EndNote Yetkin EF (01 Haziran 2022) Güç akışı analizinin geçici hata duyarlılığının değerlendirilmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 38 1 579–590.
IEEE E. F. Yetkin, “Güç akışı analizinin geçici hata duyarlılığının değerlendirilmesi”, GUMMFD, c. 38, sy. 1, ss. 579–590, 2022, doi: 10.17341/gazimmfd.913867.
ISNAD Yetkin, Emrullah Fatih. “Güç akışı Analizinin geçici Hata duyarlılığının değerlendirilmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 38/1 (Haziran 2022), 579-590. https://doi.org/10.17341/gazimmfd.913867.
JAMA Yetkin EF. Güç akışı analizinin geçici hata duyarlılığının değerlendirilmesi. GUMMFD. 2022;38:579–590.
MLA Yetkin, Emrullah Fatih. “Güç akışı Analizinin geçici Hata duyarlılığının değerlendirilmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, c. 38, sy. 1, 2022, ss. 579-90, doi:10.17341/gazimmfd.913867.
Vancouver Yetkin EF. Güç akışı analizinin geçici hata duyarlılığının değerlendirilmesi. GUMMFD. 2022;38(1):579-90.