A Review of Parallel Heterogeneous Computing Algorithms in Power Systems
The power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-09-01
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| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/14/10/275 |
| _version_ | 1797515573392834560 |
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| author | Diego Rodriguez Diego Gomez David Alvarez Sergio Rivera |
| author_facet | Diego Rodriguez Diego Gomez David Alvarez Sergio Rivera |
| author_sort | Diego Rodriguez |
| collection | DOAJ |
| description | The power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operation, studies, visualization, and the analysis of power systems are reaching their operational limit since the complexity and size of modern power systems results in long simulation times and high computational demand. Time reductions in simulation and analysis lead to the better and further optimized performance of power systems. Heterogeneous computing—where different processing units interact—has shown that power system applications can take advantage of the unique strengths of each type of processing unit, such as central processing units, graphics processing units, and field-programmable gate arrays interacting in on-premise or cloud environments. Parallel Heterogeneous Computing appears as an alternative to reduce simulation times by optimizing multitask execution in parallel computing architectures with different processing units working together. This paper presents a review of Parallel Heterogeneous Computing techniques, how these techniques have been applied in a wide variety of power system applications, how they help reduce the computational time of modern power system simulation and analysis, and the current tendency regarding each application. We present a wide variety of approaches classified by technique and application. |
| first_indexed | 2024-03-10T06:47:19Z |
| format | Article |
| id | doaj.art-6e22f064387640a58bd6f37b3f4cce94 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T06:47:19Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-6e22f064387640a58bd6f37b3f4cce942023-11-22T17:08:10ZengMDPI AGAlgorithms1999-48932021-09-01141027510.3390/a14100275A Review of Parallel Heterogeneous Computing Algorithms in Power SystemsDiego Rodriguez0Diego Gomez1David Alvarez2Sergio Rivera3Electrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, ColombiaGERS USA, Weston, FL 33331, USAElectrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, ColombiaElectrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, ColombiaThe power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operation, studies, visualization, and the analysis of power systems are reaching their operational limit since the complexity and size of modern power systems results in long simulation times and high computational demand. Time reductions in simulation and analysis lead to the better and further optimized performance of power systems. Heterogeneous computing—where different processing units interact—has shown that power system applications can take advantage of the unique strengths of each type of processing unit, such as central processing units, graphics processing units, and field-programmable gate arrays interacting in on-premise or cloud environments. Parallel Heterogeneous Computing appears as an alternative to reduce simulation times by optimizing multitask execution in parallel computing architectures with different processing units working together. This paper presents a review of Parallel Heterogeneous Computing techniques, how these techniques have been applied in a wide variety of power system applications, how they help reduce the computational time of modern power system simulation and analysis, and the current tendency regarding each application. We present a wide variety of approaches classified by technique and application.https://www.mdpi.com/1999-4893/14/10/275parallel computingheterogeneous computingparallelism taxonomyGPUFPGAcloud computing |
| spellingShingle | Diego Rodriguez Diego Gomez David Alvarez Sergio Rivera A Review of Parallel Heterogeneous Computing Algorithms in Power Systems Algorithms parallel computing heterogeneous computing parallelism taxonomy GPU FPGA cloud computing |
| title | A Review of Parallel Heterogeneous Computing Algorithms in Power Systems |
| title_full | A Review of Parallel Heterogeneous Computing Algorithms in Power Systems |
| title_fullStr | A Review of Parallel Heterogeneous Computing Algorithms in Power Systems |
| title_full_unstemmed | A Review of Parallel Heterogeneous Computing Algorithms in Power Systems |
| title_short | A Review of Parallel Heterogeneous Computing Algorithms in Power Systems |
| title_sort | review of parallel heterogeneous computing algorithms in power systems |
| topic | parallel computing heterogeneous computing parallelism taxonomy GPU FPGA cloud computing |
| url | https://www.mdpi.com/1999-4893/14/10/275 |
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