SwePub
Sök i LIBRIS databas

  Utökad sökning

id:"swepub:oai:DiVA.org:uu-442276"
 

Sökning: id:"swepub:oai:DiVA.org:uu-442276" > Comparing Different...

Comparing Different Approaches for Solving Large Scale Power-Flow Problems With the Newton-Raphson Method

D’Orto, Manolo (författare)
KTH,Skolan för elektroteknik och datavetenskap (EECS),PDC Center for High Performance Computer,KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, PDC Ctr High Performance Comp, S-10044 Stockholm, Sweden.
Sjöblom, Svante (författare)
Svenska Kraftnat, S-17224 Sundbyberg, Sweden.
Chien, Lung Sheng (författare)
NVIDIA Corp, Santa Clara, CA 95050 USA.
visa fler...
Axner, Lilit (författare)
Uppsala universitet,Institutionen för informationsteknologi,ENCCS, Uppsala University
Gong, Jing (författare)
KTH,Parallelldatorcentrum, PDC,PDC Center for High Performance Computer,KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, PDC Ctr High Performance Comp, S-10044 Stockholm, Sweden.
visa färre...
 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2021
2021
Engelska.
Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 9, s. 56604-56615
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • This paper focuses on using the Newton-Raphson method to solve the power-fiow problems. Since the most computationally demanding part of the Newton-Raphson method is to solve the linear equations at each iteration, this study investigates different approaches to solve the linear equations on both central processing unit (CPU) and graphical processing unit (GPU). Six different approaches have been developed and evaluated in this paper: two approaches of these run entirely on CPU while other two of these run entirely on GPU, and the remaining two are hybrid approaches that run on both CPU and GPU. All six direct linear solvers use either LU or QR factorization to solve the linear equations. Two different hardware platforms have been used to conduct the experiments. The performance results show that the CPU version with LU factorization gives better performance compared to the GPU version using standard library called cuSOLVER even for the larger power-fiow problems. Moreover, it has been proven that the best performance is achieved using a hybrid method where the Jacobian matrix is assembled on GPU, the preprocessing with a sparse high performance linear solver called KLU is performed on the CPU in the first iteration, and the linear equation is factorized on the GPU and solved on the CPU. Maximum speed up in this study is obtained on the largest case with 25000 buses. The hybrid version shows a speedup factor of 9:6 with a NVIDIA P100 GPU while 13:1 with a NVIDIA V100 GPU in comparison with baseline CPU version on an Intel Xeon Gold 6132 CPU.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
NATURVETENSKAP  -- Matematik -- Beräkningsmatematik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Computational Mathematics (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Nyckelord

High performance computing
Newton method
parallel algorithms
power engineering computing
power-flow
direct solver

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Sök utanför SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy