Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm
As demands on smoothing the output fluctuation of offshore wind power increase, this paper proposes an optimal configuration method for offshore wind power storage. The wavelet packet decomposition algorithm is used to process the output curve of the wind power, and an annual power response curve of...
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2022-12-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202201065 |
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| author | Jingui YI Ziwei ZHU Qing XIE |
| author_facet | Jingui YI Ziwei ZHU Qing XIE |
| author_sort | Jingui YI |
| collection | DOAJ |
| description | As demands on smoothing the output fluctuation of offshore wind power increase, this paper proposes an optimal configuration method for offshore wind power storage. The wavelet packet decomposition algorithm is used to process the output curve of the wind power, and an annual power response curve of the power storage system is obtained. In addition, the paper adopts an improved scene clustering algorithm combining a cloud model with a fuzzy c-means clustering algorithm to aggregate the annual power response curve and generate typical scenes of the power response. Furthermore, to minimize the annual comprehensive cost of the power storage, the paper constructs an optimal configuration model for offshore wind power storage and uses the particle swarm optimization algorithm to solve the optimal configuration model. Finally, the proposed method and model are analyzed and verified by typical examples. The results show that the proposed model and method can comprehensively consider the actual operating characteristics of the power storage system on the side of offshore wind farms and effectively guide the power storage configuration and construction planning of offshore wind farms. |
| format | Article |
| id | doaj-art-e9c4ef3ce20748ffa2d578d21c588c11 |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2022-12-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-e9c4ef3ce20748ffa2d578d21c588c112025-08-20T02:47:52ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492022-12-01551221010.11930/j.issn.1004-9649.202201065zgdl-55-10-yijinguiResearch on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering AlgorithmJingui YI0Ziwei ZHU1Qing XIE2School of Information Engineering, Nanchang University, Nanchang 330031, ChinaSchool of Information Engineering, Nanchang University, Nanchang 330031, ChinaSchool of Information Engineering, Nanchang University, Nanchang 330031, ChinaAs demands on smoothing the output fluctuation of offshore wind power increase, this paper proposes an optimal configuration method for offshore wind power storage. The wavelet packet decomposition algorithm is used to process the output curve of the wind power, and an annual power response curve of the power storage system is obtained. In addition, the paper adopts an improved scene clustering algorithm combining a cloud model with a fuzzy c-means clustering algorithm to aggregate the annual power response curve and generate typical scenes of the power response. Furthermore, to minimize the annual comprehensive cost of the power storage, the paper constructs an optimal configuration model for offshore wind power storage and uses the particle swarm optimization algorithm to solve the optimal configuration model. Finally, the proposed method and model are analyzed and verified by typical examples. The results show that the proposed model and method can comprehensively consider the actual operating characteristics of the power storage system on the side of offshore wind farms and effectively guide the power storage configuration and construction planning of offshore wind farms.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202201065offshore wind powerwavelet packet decompositionscene clusteringparticle swarm optimization algorithmenergy storage configuration |
| spellingShingle | Jingui YI Ziwei ZHU Qing XIE Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm Zhongguo dianli offshore wind power wavelet packet decomposition scene clustering particle swarm optimization algorithm energy storage configuration |
| title | Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm |
| title_full | Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm |
| title_fullStr | Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm |
| title_full_unstemmed | Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm |
| title_short | Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm |
| title_sort | research on optimal configuration of offshore wind power energy storage based on improved scene clustering algorithm |
| topic | offshore wind power wavelet packet decomposition scene clustering particle swarm optimization algorithm energy storage configuration |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202201065 |
| work_keys_str_mv | AT jinguiyi researchonoptimalconfigurationofoffshorewindpowerenergystoragebasedonimprovedsceneclusteringalgorithm AT ziweizhu researchonoptimalconfigurationofoffshorewindpowerenergystoragebasedonimprovedsceneclusteringalgorithm AT qingxie researchonoptimalconfigurationofoffshorewindpowerenergystoragebasedonimprovedsceneclusteringalgorithm |