Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulation
The complexity of most power grid simulation algorithms scales with the network size, which corresponds to the number of buses and branches in the grid. Parallel and distributed computing is one approach that can be used to achieve improved scalability. However, the efficiency of these algorithms re...
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| Published in: | IET generation, transmission & distribution Vol. 14; no. 25; pp. 6133 - 6141 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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The Institution of Engineering and Technology
22.12.2020
Wiley |
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| ISSN: | 1751-8687, 1751-8695 |
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| Abstract | The complexity of most power grid simulation algorithms scales with the network size, which corresponds to the number of buses and branches in the grid. Parallel and distributed computing is one approach that can be used to achieve improved scalability. However, the efficiency of these algorithms requires an optimal grid partitioning strategy. To obtain the requisite power grid partitionings, the authors first apply several graph theory based partitioning algorithms, such as the Karlsruhe fast flow partitioner (KaFFPa), spectral clustering, and METIS. The goal of this study is an examination and evaluation of the impact of grid partitioning on power system problems. To this end, the computational performance of AC optimal power flow (OPF) and dynamic power grid simulation are tested. The partitioned OPF-problem is solved using the augmented Lagrangian based alternating direction inexact Newton method, whose solution is the basis for the initialisation step in the partitioned dynamic simulation problem. The computational performance of the partitioned systems in the implemented parallel and distributed algorithms is tested using various IEEE standard benchmark test networks. KaFFPa not only outperforms other partitioning algorithms for the AC OPF problem, but also for dynamic power grid simulation with respect to computational speed and scalability. |
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| AbstractList | The complexity of most power grid simulation algorithms scales with the network size, which corresponds to the number of buses and branches in the grid. Parallel and distributed computing is one approach that can be used to achieve improved scalability. However, the efficiency of these algorithms requires an optimal grid partitioning strategy. To obtain the requisite power grid partitionings, the authors first apply several graph theory based partitioning algorithms, such as the Karlsruhe fast flow partitioner (KaFFPa), spectral clustering, and METIS. The goal of this study is an examination and evaluation of the impact of grid partitioning on power system problems. To this end, the computational performance of AC optimal power flow (OPF) and dynamic power grid simulation are tested. The partitioned OPF‐problem is solved using the augmented Lagrangian based alternating direction inexact Newton method, whose solution is the basis for the initialisation step in the partitioned dynamic simulation problem. The computational performance of the partitioned systems in the implemented parallel and distributed algorithms is tested using various IEEE standard benchmark test networks. KaFFPa not only outperforms other partitioning algorithms for the AC OPF problem, but also for dynamic power grid simulation with respect to computational speed and scalability. |
| Author | Schmurr, Philipp Hagenmeyer, Veit Çakmak, Hüseyin Murray, Alexander Kyesswa, Michael Kühnapfel, Uwe |
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| Cites_doi | 10.1007/s12667-012-0056-y 10.1109/TSG.2015.2490553 10.1090/conm/588 10.1109/ISGT.2015.7131881 10.1109/DS-RT50469.2020.9213602 10.7148/2018-0246 10.1007/978-3-319-49487-6_4 10.1016/j.ijepes.2009.02.002 10.1007/978-3-642-38527-8_16 10.1007/s10107-004-0559-y 10.1007/s12667-012-0057-x 10.1016/j.epsr.2015.01.001 10.1109/IPDPS.2010.5470485 10.1109/59.630443 10.1109/TCNS.2014.2323634 10.1109/TPWRS.1987.4335282 10.1137/140975991 10.1137/1.9781611974317.5 10.1016/j.ifacol.2018.11.730 10.1016/j.ifacol.2017.08.1095 10.1007/978-3-642-23719-5_40 10.1109/MCSI.2017.17 10.1109/ISGT-Europe47291.2020.9248824 10.1201/b11924 10.1137/141000671 10.1109/EMS.2017.36 10.1109/59.76717 10.1017/CBO9780511804441 10.1109/TPWRS.2010.2051168 |
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| Keywords | augmented Lagrangian based alternating direction inexact Newton method power grid partitionings partitioned OPF-problem parallel dynamic power grid simulation graph theory power grid simulation algorithms power system simulation parallel algorithm distributed computing optimisation grid partitioning algorithms partitioned dynamic simulation problem optimal grid partitioning strategy combined distributed AC optimal power flow IEEE standard benchmark test networks IEEE standards power grids Newton method parallel computing spectral clustering computational performance Karlsruhe fast flow partitioner parallel algorithms partitioned systems pattern clustering KaFFPa distributed algorithms power system problems AC OPF problem METIS load flow computational complexity |
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| SubjectTerms | AC OPF problem augmented Lagrangian based alternating direction inexact Newton method combined distributed AC optimal power flow computational complexity computational performance distributed algorithms distributed computing graph theory grid partitioning algorithms IEEE standard benchmark test networks IEEE standards KaFFPa Karlsruhe fast flow partitioner load flow METIS Newton method optimal grid partitioning strategy optimisation parallel algorithm parallel algorithms parallel computing parallel dynamic power grid simulation partitioned dynamic simulation problem partitioned OPF‐problem partitioned systems pattern clustering power grid partitionings power grid simulation algorithms power grids power system problems power system simulation Research Article spectral clustering |
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| Title | Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulation |
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