The influence of weather regimes on European renewable energy production and demand
The influence of weather regimes on European renewable energy production and demand
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DOI：
10.1088/1748-9326/ab38d3
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发表时间：
2019-09
影响因子：
6.7
通讯作者：
Karin van der Wiel;H. Bloomfield;R. Lee;L. Stoop;R. Blackport;J. Screen;F. Selten
中科院分区：
文献类型：
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作者：
Karin van der Wiel;H. Bloomfield;R. Lee;L. Stoop;R. Blackport;J. Screen;F. Selten
可变可再生能源的份额越来越大，增加了电力系统的气象敏感度。这项研究调查了大范围天气制度是否捕捉到了气象可变性对欧洲能源部门的影响。对于每种天气状况，探讨了冬季平均和极端风能和太阳能发电量、温度驱动的能源需求和能源短缺(剩余负荷)的相关变化。环流模式受阻的日子，即‘斯堪的纳维亚阻塞’和‘北大西洋涛动负’制度，平均而言，低于正常的可再生电力生产，高于正常的能源需求，因此高于正常的能源短缺。这些平均效应隐藏了每个天气机制内能量参数的巨大变异性。虽然极高能量短缺事件的风险在两个被封锁的地区增加(分别为1.5倍和2.0倍)，但研究表明，这种事件在所有地区都会发生。极高能量短缺事件是罕见环流类型和小尺度特征的结果，而不是常见大尺度环流类型的极端量级。事实上，这些事件彼此之间的相似性比它们各自的天气状况平均模式更强烈。对于(次)季节性预报应用，天气状况可能对能源部门有用。在较短的准备时间或更详细的系统分析中，它们在表征极端事件方面的无效限制了它们的潜力。
The growing share of variable renewable energy increases the meteorological sensitivity of power systems. This study investigates if large-scale weather regimes capture the influence of meteorological variability on the European energy sector. For each weather regime, the associated changes to wintertime—mean and extreme—wind and solar power production, temperature-driven energy demand and energy shortfall (residual load) are explored. Days with a blocked circulation pattern, i.e. the ‘Scandinavian Blocking’ and ‘North Atlantic Oscillation negative’ regimes, on average have lower than normal renewable power production, higher than normal energy demand and therefore, higher than normal energy shortfall. These average effects hide large variability of energy parameters within each weather regime. Though the risk of extreme high energy shortfall events increases in the two blocked regimes (by a factor of 1.5 and 2.0, respectively), it is shown that such events occur in all regimes. Extreme high energy shortfall events are the result of rare circulation types and smaller-scale features, rather than extreme magnitudes of common large-scale circulation types. In fact, these events resemble each other more strongly than their respective weather regime mean pattern. For (sub-)seasonal forecasting applications weather regimes may be of use for the energy sector. At shorter lead times or for more detailed system analyses, their ineffectiveness at characterising extreme events limits their potential.