An Application of GPU Parallel Computing to Power Flow Calculation in HVDC Networks

Błaśkiewicz, Przemysław; Zawada, Marcin; Balcerek, P.; Dawidowski, Pawel

doi:10.1109/pdp.2015.110

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…While many papers limit their applications to NIVIDIA GPUs by using CUDA, OpenCL, a general parallel hardware API, has also been used occasionally [107]. Some experimented with and compared the performance of different CUDA routines on different NIVIDIA GPU models [108]. Similar experimentation on routines was conducted to solve ACOPF using FDPF [109].…”

Section: Developmentmentioning

confidence: 99%

“…Even very recently, within supposedly comparative work where four different parallel schemes were compared, each scheme was performed on a different supercomputer and a different test case [251]. The single study that provided a meaningful cross-hardware comparison was [108]. They experimented with different CUDA routines on different but closely related NIVIDIA GPU models, showing that their approach was not superior on every model proving the importance of hardware normalization.…”

Section: Challenges In the Literaturementioning

confidence: 99%

See 1 more Smart Citation

A Review of High-Performance Computing and Parallel Techniques Applied to Power Systems Optimization

Al-Shafei¹,

Zareipour²,

Cao³

2022

Preprint

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Section: Developmentmentioning

confidence: 99%

Section: Challenges In the Literaturementioning

confidence: 99%

A Review of High-Performance Computing and Parallel Techniques Applied to Power Systems Optimization

Al-Shafei¹,

Zareipour²,

Cao³

2022

Preprint

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show abstract

“…Power flow analysis is a fundamental calculation which is often used to evaluate the feasibility, reliability and efficiency of a power supply scheme, and in doing research on power system operation and regulating schemes [25][26][27][28]. It is also necessary for theoretical line loss analysis.…”

Section: Power Flow Calculation Model Of Power Systemmentioning

confidence: 99%

Cloud-based parallel power flow calculation using resilient distributed datasets and directed acyclic graph

Wang

Zhou

2018

J. Mod. Power Syst. Clean Energy

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With the integration of distributed generation and the construction of cross-regional long-distance power grids, power systems become larger and more complex. They require faster computing speed and better scalability for power flow calculations to support unit dispatch. Based on the analysis of a variety of parallelization methods, this paper deploys the large-scale power flow calculation task on a cloud computing platform using resilient distributed datasets (RDDs). It optimizes a directed acyclic graph that is stored in the RDDs to solve the low performance problem of the MapReduce model. This paper constructs and simulates a power flow calculation on a large-scale power system based on standard IEEE test data. Experiments are conducted on Spark cluster which is deployed as a cloud computing platform. They show that the advantages of this method are not obvious at small scale, but the performance is superior to the stand-alone model and the MapReduce model for large-scale calculations. In addition, running time will be reduced when adding cluster nodes. Although not tested under practical conditions, this paper provides a new way of thinking about parallel power flow calculations in large-scale power systems.

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“…Reference [8] used distributed computation technology to implement parallel power flow computation. Besides, GPU based parallel computing was introduced and applied to power flow calculation [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Graph Computing based Distributed Fast Decoupled Power Flow Analysis

Yuan

Liang

Feng

et al. 2019

2019 IEEE Power &Amp; Energy Society General Meeting (PESGM)

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Power flow analysis plays a fundamental and critical role in the energy management system (EMS). It is required to well accommodate large and complex power system. To achieve a high performance and accurate power flow analysis, a graph computing based distributed power flow analysis approach is proposed in this paper. Firstly, a power system network is divided into multiple areas. Slack buses are selected for each area and, at each SCADA sampling period, the inter-area transmission line power flows are equivalently allocated as extra load injections to corresponding buses. Then, the system network is converted into multiple independent areas. In this way, the power flow analysis could be conducted in parallel for each area and the solved system states could be guaranteed without compromise of accuracy. Besides, for each area, graph computing based fast decoupled power flow (FDPF) is employed to quickly analyze system states. IEEE 118-bus system and MP 10790-bus system are employed to verify the results accuracy and present the promising computation performance of the proposed approach.

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An Application of GPU Parallel Computing to Power Flow Calculation in HVDC Networks

Cited by 10 publications

References 10 publications

A Review of High-Performance Computing and Parallel Techniques Applied to Power Systems Optimization

A Review of High-Performance Computing and Parallel Techniques Applied to Power Systems Optimization

Cloud-based parallel power flow calculation using resilient distributed datasets and directed acyclic graph

Graph Computing based Distributed Fast Decoupled Power Flow Analysis

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