水准点(测量)
环境科学
气象学
风力发电
气候学
地理
地质学
工程类
地图学
电气工程
作者
Cameron Bracken,Nathalie Voisin,Casey Burleyson,Allison Campbell,Zhangshuan Hou,Daniel Broman
标识
DOI:10.1016/j.renene.2023.119550
摘要
As we move towards a decarbonized grid, reliance on weather-dependent energy increases as does exposure to prolonged natural resource shortages known as energy droughts. Compound energy droughts occur when two or more predominant renewable energy sources simultaneously are in drought conditions. In this study we present a methodology and dataset for examining compound wind and solar energy droughts as well as the first standardized benchmark of energy droughts across the Continental United States (CONUS) for a 2020 infrastructure. Using a recently developed dataset of simulated hourly plant level generation which includes thousands of wind and solar plants, we examine the frequency, duration, magnitude, and seasonality of energy droughts at a variety of temporal and spatial scales. Results are presented for 15 Balancing Authorities (BAs), regions of the U.S. power grid where wind and solar are must-take resources by the power grid and must be balanced. Compound wind and solar droughts are shown to have distinct spatial and temporal patterns across the CONUS. BA-level load is also included in the drought analysis to quantify events where high load is coincident with wind and solar droughts. We find that energy drought characteristics are regional and the longest droughts can last from 16 to 37 continuous hours, and up to 6 days. The longest hourly energy droughts occur in Texas while the longest daily droughts occur in California. Compound energy drought events that include load are more severe on average compared to events that involve only wind and solar. In addition, we find that compound high load events occur more often during compound wind and solar droughts that would be expected due to chance. The insights obtained from these findings and the summarized characteristics of energy drought provide valuable guidance on grid planning and storage sizing at the regional scale.
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