Global Wind-Power Generation Capacity in the Context of Climate Change
Establishing power systems with a high share of renewable energy sources is a pivotal step toward achieving a globally sustainable transition to green and low-carbon energy. This study focuses on low-output wind power that affects the generation capacity of power systems with a high share of renewable energy sources. Utilizing the Coupled Model Intercomparison Project Phase 6 datasets, a predictive model for low-output wind power was employed to investigate regional trends worldwide. The frequency and duration of low-output wind-power events exhibited increasing trends globally, particularly in East Asia and South America, but not in North America. By 2060, the annual total days with low-output wind power in East Asia and South America could rise to 13 and 5 d, and the maximum continuous duration of low-output wind power could reach 5 and 2 d, respectively. As wind power becomes a primary electricity source, such low output could lead to shortages in energy supply within the power system, triggering large-scale power outages. This issue calls for critical attention when establishing power systems with a high share of renewable energy sources. The conclusions provide a basis for analyzing power supply risks and configuring flexible power sources for scenarios with a high share of renewable energy.
Authors
- Zongpeng Song (ORCID: https://orcid.org/0000-0002-1331-002X)
- Zheng Wang (ORCID: https://orcid.org/0009-0008-0462-9291)
- Qing Yang (ORCID: https://orcid.org/0000-0003-1843-386X)
- Shuanglei Feng
- Weisheng Wang (ORCID: https://orcid.org/0000-0002-4289-4079)
- Bo Wang (ORCID: https://orcid.org/0009-0002-9278-190X)
Institutions
- National Laboratory of the Rockies (US)
- North China Electric Power University (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Engineering
- Published
- 2024-10-19
- DOI
- https://doi.org/10.1016/j.eng.2024.09.018
- Citations
- 14
- Primary Topic
- Integrated Energy Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 2.92
Funders
- National Natural Science Foundation of China
- State Grid Corporation of China