Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogate
Simulator fOr Wind Farm Applications (SOWFA) is a powerful wind farm simulation tool. It is widely used in wake effect research. However, the integration between AI and SOWFA is weak. Without AI, it is difficult for us to fully use SOWFA. The installation, parameter settings, and calculation procedu...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
|
| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723005176 |
| _version_ | 1797691973049516032 |
|---|---|
| author | Tannan Xiao Yuqi Cao Bingfeng Liang Yang Wang Jing Wang Ying Chen |
| author_facet | Tannan Xiao Yuqi Cao Bingfeng Liang Yang Wang Jing Wang Ying Chen |
| author_sort | Tannan Xiao |
| collection | DOAJ |
| description | Simulator fOr Wind Farm Applications (SOWFA) is a powerful wind farm simulation tool. It is widely used in wake effect research. However, the integration between AI and SOWFA is weak. Without AI, it is difficult for us to fully use SOWFA. The installation, parameter settings, and calculation procedures of SOWFA are complex, which hinders the application of SOWFA in practical power system engineering scenarios. To mitigate these issues, a batch simulation tool of SOWFA based on Docker and Python is designed and implemented. Firstly, the Docker engine is used to realize the virtualization container management of SOWFA. A SOWFA installation image is built to make it easy to migrate and deploy. Secondly, a Python application programming interface (API) of the SOWFA container is programmed to realize parameter editing, calculation process management, and batch simulations. Finally, a batch simulation post-processing Python API is constructed based on the ParaView library so that the SOWFA batch simulation results can be collated into data samples for downstream tasks. The above SOWFA image and Python API are tested in a simple single-turbine wake analysis scenario. With the samples generated by the batch simulations, an autoencoder-based single-turbine wake prediction surrogate model is trained, which verifies the effectiveness of the SOWFA batch simulation tool designed in this paper. |
| first_indexed | 2024-03-12T02:20:49Z |
| format | Article |
| id | doaj.art-0e966f0252a242c9ab4da36a1cf3d0f7 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-12T02:20:49Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-0e966f0252a242c9ab4da36a1cf3d0f72023-09-06T04:51:57ZengElsevierEnergy Reports2352-48472023-09-019419426Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogateTannan Xiao0Yuqi Cao1Bingfeng Liang2Yang Wang3Jing Wang4Ying Chen5Tsinghua University, Beijing 10084, ChinaTsinghua University, Beijing 10084, ChinaState Grid Jibei Zhangjiakou Wind and Solar Energy Storage and Transportation New Energy Co., Ltd., Zhangjiakou, 075000, ChinaState Grid Jibei Zhangjiakou Wind and Solar Energy Storage and Transportation New Energy Co., Ltd., Zhangjiakou, 075000, ChinaState Grid Jibei Zhangjiakou Wind and Solar Energy Storage and Transportation New Energy Co., Ltd., Zhangjiakou, 075000, ChinaTsinghua University, Beijing 10084, China; Corresponding author.Simulator fOr Wind Farm Applications (SOWFA) is a powerful wind farm simulation tool. It is widely used in wake effect research. However, the integration between AI and SOWFA is weak. Without AI, it is difficult for us to fully use SOWFA. The installation, parameter settings, and calculation procedures of SOWFA are complex, which hinders the application of SOWFA in practical power system engineering scenarios. To mitigate these issues, a batch simulation tool of SOWFA based on Docker and Python is designed and implemented. Firstly, the Docker engine is used to realize the virtualization container management of SOWFA. A SOWFA installation image is built to make it easy to migrate and deploy. Secondly, a Python application programming interface (API) of the SOWFA container is programmed to realize parameter editing, calculation process management, and batch simulations. Finally, a batch simulation post-processing Python API is constructed based on the ParaView library so that the SOWFA batch simulation results can be collated into data samples for downstream tasks. The above SOWFA image and Python API are tested in a simple single-turbine wake analysis scenario. With the samples generated by the batch simulations, an autoencoder-based single-turbine wake prediction surrogate model is trained, which verifies the effectiveness of the SOWFA batch simulation tool designed in this paper.http://www.sciencedirect.com/science/article/pii/S2352484723005176SOWFA simulationWake effectMachine learning |
| spellingShingle | Tannan Xiao Yuqi Cao Bingfeng Liang Yang Wang Jing Wang Ying Chen Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogate Energy Reports SOWFA simulation Wake effect Machine learning |
| title | Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogate |
| title_full | Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogate |
| title_fullStr | Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogate |
| title_full_unstemmed | Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogate |
| title_short | Design and implementation of a general batch simulation tool of SOWFA and its application in training a single-turbine surrogate |
| title_sort | design and implementation of a general batch simulation tool of sowfa and its application in training a single turbine surrogate |
| topic | SOWFA simulation Wake effect Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723005176 |
| work_keys_str_mv | AT tannanxiao designandimplementationofageneralbatchsimulationtoolofsowfaanditsapplicationintrainingasingleturbinesurrogate AT yuqicao designandimplementationofageneralbatchsimulationtoolofsowfaanditsapplicationintrainingasingleturbinesurrogate AT bingfengliang designandimplementationofageneralbatchsimulationtoolofsowfaanditsapplicationintrainingasingleturbinesurrogate AT yangwang designandimplementationofageneralbatchsimulationtoolofsowfaanditsapplicationintrainingasingleturbinesurrogate AT jingwang designandimplementationofageneralbatchsimulationtoolofsowfaanditsapplicationintrainingasingleturbinesurrogate AT yingchen designandimplementationofageneralbatchsimulationtoolofsowfaanditsapplicationintrainingasingleturbinesurrogate |