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Kardos_2022_Else_segn
Journal article

Massively parallel data analytics for smart grid applications

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  • 2022
Published in:
  • Sustainable energy, grids and networks. - 2022, vol. 31, p. 100789
High-throughput scheduling
Massively parallel computing
Numerical optimization
Power grid
Optimal power flow
Unit commitment
English Complexity involved in operating modern power and energy systems is constantly increasing given the volatility induced by the rapid integration of intermittent renewable energy sources. In order to operate the power grid in secure and reliable way, a plethora of uncertain parameters need to be considered and hundreds of thousands of different power grid scenarios need to be rapidly evaluated. This works analyzes the computational aspects in massively parallel simulations from the perspective of efficient hardware utilization. A method for efficiently managing and processing the computational tasks is presented, carefully considering the level of parallelism in order to avoid computational bottlenecks and efficiently utilizing modern multicore architectures with deep memory hierarchies. An extensive set of numerical experiments is presented, considering multiple aspects of the computational pipeline. The numerical experiments are performed using mathematical models typically used in the power grid problems, including linear and quadratic programs as well as the models containing the discrete variables. The optimized high-throughput computation strategy has been shown to significantly reduce response times by preventing the memory bottlenecks for various computational models.
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Language
  • English
Classification
Economics of energy
License
CC BY
Open access status
hybrid
Identifiers
Persistent URL
https://n2t.net/ark:/12658/srd1322962
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