Impacts of Inter-annual Wind and Solar Variations on the European Power System.
Impacts of Inter-annual Wind and Solar Variations on the European Power System.
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DOI：
10.1016/j.joule.2018.06.020
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发表时间：
2018-10-17
期刊：
影响因子：
39.8
通讯作者：
Staffell I
中科院分区：
文献类型：
--
作者：
Collins S;Deane P;Ó Gallachóir B;Pfenninger S;Staffell I
依赖天气的可再生能源在电力脱碳方面发挥着关键作用。越来越多的研究分析了风和太阳变化对电力系统运行的影响。现有的研究往往使用一个单一的或典型的一年的发电数据，忽略了大量的逐年波动的天气，或只考虑气象输入的变化，忽略了一个互联的电力系统的复杂响应。在这里，我们通过将欧洲未来电力系统的详细全大陆建模与30年的历史天气数据相结合来解决这些差距。最具代表性的单年是1989年和2012年，但使用多年显示，从2015年到2030年，欧洲二氧化碳排放量和总发电成本的年际变化增加了5倍。我们还发现，几个指标概括为可变的可再生能源渗透率的线性函数：二氧化碳排放量，可再生能源的削减，批发价格和总系统成本。天气模式对电力系统的影响随着脱碳而增加到2030年，欧洲的二氧化碳产量和发电成本的变化可能会增加5倍。几个指标可以从VRE渗透率水平合理地近似计算。可再生能源发电最具代表性的单年是1989年和2012年。我们对依赖天气的资源的依赖越来越大，这使得电力系统的规划必须认识到它们的长期变化。研究往往忽视这些资源的长期可变性，只使用一年或几年的数据，或没有考虑到短期国际电力流动的影响和对发电机灵活性的限制，而这对整合这些可变发电源至关重要。这项研究使用了一个大陆电力系统模型和30年的每小时风能和太阳能数据，以确定长期天气模式对欧洲电力系统运行的影响，以及这种影响如何随脱碳目标而变化。结果表明，到2030年，这个互联电力系统的二氧化碳排放量和总发电成本的变化可能比2015年增加5倍。这项研究揭示了长期天气变化对欧洲电力系统运行的影响，以及到2030年，这种影响如何与风能和太阳能的吸收相结合。我们发现，雄心勃勃的脱碳导致长期天气模式的影响更大，到2030年，运营可变性将增加5倍。几个相关的指标可以合理地近似变量可再生能源渗透率的线性函数，提供了一个快捷方式来估计的影响。
Weather-dependent renewable energy resources are playing a key role in decarbonizing electricity. There is a growing body of analysis on the impacts of wind and solar variability on power system operation. Existing studies tend to use a single or typical year of generation data, which overlooks the substantial year-to-year fluctuation in weather, or to only consider variation in the meteorological inputs, which overlooks the complex response of an interconnected power system. Here, we address these gaps by combining detailed continent-wide modeling of Europe's future power system with 30 years of historical weather data. The most representative single years are 1989 and 2012, but using multiple years reveals a 5-fold increase in Europe's inter-annual variability of CO2 emissions and total generation costs from 2015 to 2030. We also find that several metrics generalize to linear functions of variable renewable penetration: CO2 emissions, curtailment of renewables, wholesale prices, and total system costs. The impact of weather patterns on power system increases with decarbonization Europe's CO2 output and generation cost variability could increase 5-fold by 2030 Several metrics can be reasonably approximated from the level VRE penetration The most representative single years for renewable generation are 1989 and 2012 Wind and solar power have been driving the decarbonization of Europe's electricity over the last decade. Increasing our reliance on weather-dependent resources makes it imperative that planning of electricity systems becomes cognizant of their long-term variability. Studies often neglect the long-term variability of these resources by using only data from a single or a few years or fail to account for the impacts of short-term international electricity flows and limitations on generator flexibility, which are critical to the integration of these variable generation sources. This study uses a continental electricity system model and 30 years of hourly wind and solar data to determine the impact of long-term weather patterns on European electricity system operation and how this varies with decarbonization ambition. The results show that the variability of CO2 emissions and total generation costs for this interconnected electricity system could increase 5-fold by 2030 compared with 2015. This research sheds light on the impact of long-term weather variability on the operation of the European power system and how this scales with uptake of wind and solar power out to 2030. We find that ambitious decarbonization leads to much greater influence of long-term weather patterns, with a 5-fold increase in operational variability by 2030. Several relevant metrics can be reasonably approximated by linear functions of variable renewable penetration, providing a shortcut for estimating the impacts of intermittency.
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影响因子：
4.9
作者：
Gelaro, Ronald;McCarty, Will;Zhao, Bin
通讯作者：
Zhao, Bin
影响因子：
9
作者：
Deane, J. P.;Chiodi, Alessandro;Gallachoir, Brian P. O.
通讯作者：
Gallachoir, Brian P. O.
影响因子：
8.7
作者：
Hdidouan, Daniel;Staffell, Iain
通讯作者：
Staffell, Iain
影响因子：
6.6
作者：
Hyndman, Rob J.;Fan, Shu
通讯作者：
Fan, Shu
DOI：
10.1016/j.ijepes.2015.04.020
发表时间：
2015-12-01
影响因子：
5.2
作者：
Deane, J. P.;Gracceva, Francesco;Gallachoir, Brian P. O.
通讯作者：
Gallachoir, Brian P. O.