An Open-Source Many-Scenario Approach for Power System Dynamic Simulation on HPC Clusters

Zhang, Junjie; Razik, Lukas; Jakobsen, Sigurd Hofsmo; D’Arco, Salvatore; Benigni, Andrea

doi:10.3390/electronics10111330

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…• Developing multi-threaded programs for systems with shared memory based on the OpenMP or other standards [8][9][10]. This approach uses high-level tools for developing and debugging parallel programs.…”

Section: High-performance Computing Implementationsmentioning

confidence: 99%

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An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

Feoktistov,

Edelev,

Tchernykh

et al. 2023

Computation

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Implementing high-performance computing (HPC) to solve problems in energy infrastructure resilience research in a heterogeneous environment based on an in-memory data grid (IMDG) presents a challenge to workflow management systems. Large-scale energy infrastructure research needs multi-variant planning and tools to allocate and dispatch distributed computing resources that pool together to let applications share data, taking into account the subject domain specificity, resource characteristics, and quotas for resource use. To that end, we propose an approach to implement HPC-based resilience analysis using our Orlando Tools (OT) framework. To dynamically scale computing resources, we provide their integration with the relevant software, identifying key application parameters that can have a significant impact on the amount of data processed and the amount of resources required. We automate the startup of the IMDG cluster to execute workflows. To demonstrate the advantage of our solution, we apply it to evaluate the resilience of the existing energy infrastructure model. Compared to similar approaches, our solution allows us to investigate large infrastructures by modeling multiple simultaneous failures of different types of elements down to the number of network elements. In terms of task and resource utilization efficiency, we achieve almost linear speedup as the number of nodes of each resource increases.

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Section: High-performance Computing Implementationsmentioning

confidence: 99%

“…Implementing MPI programs [9,10]. This approach focuses on homogeneous computing resources and allows us to solve problems of any complexity, depending on the number of resources.…”

mentioning

confidence: 99%

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

Feoktistov,

Edelev,

Tchernykh

et al. 2023

Computation

View full text Add to dashboard Cite

show abstract

“…High-performance computing (HPC) is another advanced and promising technique for handling computationally intensive power systems studies, such as contingency analysis, reliability analysis, state estimation, and transient stability simulation. With rich computing resources, multiple subtasks can be simultaneously processed with superior efficiency [27] [28].…”

Section: Introductionmentioning

confidence: 99%

ParaEMT: An Open Source, Parallelizable, and HPC-Compatible EMT Simulator for Large-Scale IBR-Rich Power Grids

Xiong,

Wang,

Vaidhynathan

et al. 2024

IEEE Trans. Power Delivery

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The electromagnetic transient (EMT) simulation is an essential tool for studying power grids dominated by inverterbased resources (IBRs). However, due to small simulation time steps and increasing problem sizes, performing EMT simulations for large-scale power grids becomes computational-intensive, and often impractical. To address this challenge, we developed Pa-raEMT, an open-source Python-based EMT simulator that is parallelizable and compatible with high-performance computing (HPC) systems for simulating large-scale power grids with a significant presence of IBRs. Its key features include: 1) utilizing parallel computation for network solution by decomposing the network conductance matrix into the bordered block diagonal form; 2) enabling parallel updates of device states and network historical currents; 3) leveraging HPC to further accelerate simulation through a developed generic interface. The accuracy of ParaEMT has been validated on the reduced 240-bus (720-node) Western Electricity Coordinating Council system by benchmarking the EMT dynamics against PSCAD. Furthermore, ParaEMT achieves a notable speedup of approximately 25 to 36 times on a synthetic 10,080-bus (30240-node) system by leveraging the HPC resource named Eagle at the National Renewable Energy Laboratory. A regional 100% renewable case of the reduced 240-bus system has been developed for simulating system-wide IBRs' interactions in large-scale power grids using ParaEMT.

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Modelica-based parallel computing framework for power system adaptive special protection schemes

Jakobsen

Zhang²,

Reigstad

et al. 2022

2022 Open Source Modelling and Simulation of Energy Systems (OSMSES)

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An Open-Source Many-Scenario Approach for Power System Dynamic Simulation on HPC Clusters

Cited by 4 publications

References 27 publications

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

ParaEMT: An Open Source, Parallelizable, and HPC-Compatible EMT Simulator for Large-Scale IBR-Rich Power Grids

Modelica-based parallel computing framework for power system adaptive special protection schemes

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