Michael Kyesswa, Philipp Schmurr, H. Çakmak, U. Kühnapfel, V. Hagenmeyer
{"title":"一种新的基于julia的电力系统动力学分析并行时域仿真算法","authors":"Michael Kyesswa, Philipp Schmurr, H. Çakmak, U. Kühnapfel, V. Hagenmeyer","doi":"10.1109/DS-RT50469.2020.9213602","DOIUrl":null,"url":null,"abstract":"The present paper describes a new parallel time-domain simulation algorithm using a high performance computing environment - Julia - for the analysis of power system dynamics in large networks. The parallel algorithm adapts a parallel-in-space decomposition scheme to a previously sequential algorithm in order to develop a new parallelizable numerical solution of the power system equations. The parallel-in-space decomposition is based on the block bordered diagonal form, which reformulates the network admittance matrix into sub-blocks that can be solved in parallel. For the optimal spatial decomposition of the network, a new extended graph partitioning strategy is developed for load balancing and minimizing the communication between subnetworks. The new parallel simulation algorithm is tested using standard test networks of varying complexity. The simulation results are compared to those obtained from a sequential implementation in order to validate the solution accuracy and to determine the performance improvement in terms of computational speedup. Test simulations are conducted using the ForHLR II supercomputing cluster and show a huge potential in computational speedup with increasing network complexity.","PeriodicalId":149260,"journal":{"name":"2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A New Julia-Based Parallel Time-Domain Simulation Algorithm for Analysis of Power System Dynamics\",\"authors\":\"Michael Kyesswa, Philipp Schmurr, H. Çakmak, U. Kühnapfel, V. Hagenmeyer\",\"doi\":\"10.1109/DS-RT50469.2020.9213602\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present paper describes a new parallel time-domain simulation algorithm using a high performance computing environment - Julia - for the analysis of power system dynamics in large networks. The parallel algorithm adapts a parallel-in-space decomposition scheme to a previously sequential algorithm in order to develop a new parallelizable numerical solution of the power system equations. The parallel-in-space decomposition is based on the block bordered diagonal form, which reformulates the network admittance matrix into sub-blocks that can be solved in parallel. For the optimal spatial decomposition of the network, a new extended graph partitioning strategy is developed for load balancing and minimizing the communication between subnetworks. The new parallel simulation algorithm is tested using standard test networks of varying complexity. The simulation results are compared to those obtained from a sequential implementation in order to validate the solution accuracy and to determine the performance improvement in terms of computational speedup. Test simulations are conducted using the ForHLR II supercomputing cluster and show a huge potential in computational speedup with increasing network complexity.\",\"PeriodicalId\":149260,\"journal\":{\"name\":\"2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DS-RT50469.2020.9213602\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DS-RT50469.2020.9213602","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Julia-Based Parallel Time-Domain Simulation Algorithm for Analysis of Power System Dynamics
The present paper describes a new parallel time-domain simulation algorithm using a high performance computing environment - Julia - for the analysis of power system dynamics in large networks. The parallel algorithm adapts a parallel-in-space decomposition scheme to a previously sequential algorithm in order to develop a new parallelizable numerical solution of the power system equations. The parallel-in-space decomposition is based on the block bordered diagonal form, which reformulates the network admittance matrix into sub-blocks that can be solved in parallel. For the optimal spatial decomposition of the network, a new extended graph partitioning strategy is developed for load balancing and minimizing the communication between subnetworks. The new parallel simulation algorithm is tested using standard test networks of varying complexity. The simulation results are compared to those obtained from a sequential implementation in order to validate the solution accuracy and to determine the performance improvement in terms of computational speedup. Test simulations are conducted using the ForHLR II supercomputing cluster and show a huge potential in computational speedup with increasing network complexity.