Probabilistic power flow calculation using principal component analysis-based compressive sensing
文献类型：期刊论文
| 作者 | Wang, Tonghe2,3; Liang, Hong4; Cao, Junwei5; Zhao, Yuming1 |
| 刊名 | FRONTIERS IN ENERGY RESEARCH
 |
| 出版日期 | 2023-01-16 |
| 卷号 | 10页码:12 |
| 关键词 | probabilistic power flow principal component analysis compressive sensing renewable energy polynomial chaos expansion |
| ISSN号 | 2296-598X |
| DOI | 10.3389/fenrg.2022.1056077 |
| 通讯作者 | Zhao, Yuming(ymzhao@zqu.edu.cn) |
| 英文摘要 | The increasing scale of the injection of renewable energy has brought about great uncertainty to the operation of power grid. In this situation, probabilistic power flow (PPF) calculation has been introduced to mitigate the low accuracy of traditional deterministic power flow calculation in describing the operation status and power flow distribution of power systems. Polynomial chaotic expansion (PCE) method has become popular in PPF analysis due to its high efficiency and accuracy, and sparse PCE has increased its capability of tackling the issue of dimension disaster. In this paper, we propose a principal component analysis-based compressive sensing (PCA-CS) algorithm solve the PPF problem. The l(1)-optimization of CS is used to tackle the dimension disaster of sparse PCE, and PCA is included to further increase the sparsity of expansion coefficient matrix. Theoretical and numerical simulation results show that the proposed method can effectively improve the efficiency of PPF calculation in the case of random inputs with higher dimensions. |
| WOS关键词 | ENERGY INTERNET ; NETWORKS |
| 资助项目 | China National Key R&D Program intergovernmental international scientific and technological innovation cooperation project[2019YFE0120200] |
| WOS研究方向 | Energy & Fuels |
| 语种 | 英语 |
| WOS记录号 | WOS:000920561700001 |
| 出版者 | FRONTIERS MEDIA SA |
| 资助机构 | China National Key R&D Program intergovernmental international scientific and technological innovation cooperation project |
| 源URL | [http://ir.giec.ac.cn/handle/344007/38497]  |
| 专题 | 中国科学院广州能源研究所 |
| 通讯作者 | Zhao, Yuming |
| 作者单位 | 1.Zhaoqing Univ, Sch Comp Sci & Software, Zhaoqing, Peoples R China 2.Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou, Peoples R China 3.Changzhou Univ, Jiangsu Collaborat Innovat Ctr Photovolta Sci & En, Changzhou, Peoples R China 4.Meihua Holdings Grp Co Ltd, Langfang, Peoples R China 5.Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Tonghe,Liang, Hong,Cao, Junwei,et al. Probabilistic power flow calculation using principal component analysis-based compressive sensing[J]. FRONTIERS IN ENERGY RESEARCH,2023,10:12. |
| APA | Wang, Tonghe,Liang, Hong,Cao, Junwei,&Zhao, Yuming.(2023).Probabilistic power flow calculation using principal component analysis-based compressive sensing.FRONTIERS IN ENERGY RESEARCH,10,12. |
| MLA | Wang, Tonghe,et al."Probabilistic power flow calculation using principal component analysis-based compressive sensing".FRONTIERS IN ENERGY RESEARCH 10(2023):12. |
入库方式： OAI收割
来源：广州能源研究所
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