A Morphing-Based Future Scenario Generation Method for Stochastic Power System Analysis
文献类型：期刊论文
| 作者 | Gao, Yanna1; Dong, Hong1; Hu, Liujun1; Lin, Zihan1; Zeng, Fanhong1; Ye, Cantao2; Zhang, Jixiang2 |
| 刊名 | SUSTAINABILITY
 |
| 出版日期 | 2024-04-01 |
| 卷号 | 16期号:7页码:21 |
| 关键词 | future scenario weather morphing climate change cluster analysis uncertainties |
| DOI | 10.3390/su16072762 |
| 通讯作者 | Ye, Cantao(yect@ms.giec.ac.cn) |
| 英文摘要 | As multiple wind and solar photovoltaic farms are integrated into power systems, precise scenario generation becomes challenging due to the interdependence of power generation and future climate change. Future climate data derived from obsolete climate models, featuring diminished accuracy, less-refined spatial resolution, and a limited range of climate scenarios compared to more recent models, are still in use. In this paper, a morphing-based approach is proposed for generating future scenarios, incorporating the interdependence of power generation among multiple wind and photovoltaic farms using copula theory. The K-means method was employed for scenario generation. The results of our study indicate that the average annual variations in dry-bulb temperature (DBT), global horizontal irradiance (GHI), and wind speed (WS) are projected to increase by approximately 0.4 to 1.9 degrees C, 7.5 to 20.4 W/m2, and 0.3 to 1.7 m/s, respectively, in the forthcoming scenarios of the four considered Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). It seems that accumulated maximum wind electricity output (WEO) and solar electricity output (SEO) will increase from 0.9% to 7.3% and 1.1% to 6.8%, respectively, in 2050. |
| WOS关键词 | CLUSTERING-ALGORITHM ; WIND-SPEED ; ENERGY ; MODEL ; UNCERTAINTY ; INTEGRATION ; DEPENDENCE ; CLIMATE |
| 资助项目 | Science and Technology Project of Guangzhou Power Supply Bureau of Guangdong Power Grid |
| WOS研究方向 | Science & Technology - Other Topics ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001200888600001 |
| 出版者 | MDPI |
| 资助机构 | Science and Technology Project of Guangzhou Power Supply Bureau of Guangdong Power Grid |
| 源URL | [http://ir.giec.ac.cn/handle/344007/41400]  |
| 专题 | 中国科学院广州能源研究所 |
| 通讯作者 | Ye, Cantao |
| 作者单位 | 1.Guangdong Power Grid Co Ltd, Guangzhou Power Supply Bur, Guangzhou 510620, Peoples R China 2.Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou 510640, Peoples R China |
| 推荐引用方式 GB/T 7714 | Gao, Yanna,Dong, Hong,Hu, Liujun,et al. A Morphing-Based Future Scenario Generation Method for Stochastic Power System Analysis[J]. SUSTAINABILITY,2024,16(7):21. |
| APA | Gao, Yanna.,Dong, Hong.,Hu, Liujun.,Lin, Zihan.,Zeng, Fanhong.,...&Zhang, Jixiang.(2024).A Morphing-Based Future Scenario Generation Method for Stochastic Power System Analysis.SUSTAINABILITY,16(7),21. |
| MLA | Gao, Yanna,et al."A Morphing-Based Future Scenario Generation Method for Stochastic Power System Analysis".SUSTAINABILITY 16.7(2024):21. |
入库方式： OAI收割
来源：广州能源研究所
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