Institute of Geography, University of Innsbruck, Innrain 52f, 6020 Innsbruck, Austria.
University of Padova, Dept. Land, Environment, Agriculture and Forestry, Padova, Italy.
Sci Total Environ. 2020 Nov 1;741:140179. doi: 10.1016/j.scitotenv.2020.140179. Epub 2020 Jun 15.
Variable renewable energy sources display different space-time variability driving the availability of energy generated from these sources. Complementarity among variable renewable energies in time and space allows reducing the variability of power supply and helps matching the electricity demand curve. This work investigates the temporal structure of complementarity along an alpine transect in North-East Italy, considering a 100% renewable energy mix scenario composed by photovoltaic and run-of-the-river energy. We analyze the dominant scales of variability of variable renewable energy sources and electricity demand. In addition, we introduce a new metric, the wavelet-based complementarity index, to quantify the potential complementarity between two different energy sources. We show that this index varies at different temporal scales and it helps explaining the discrepancy between demand and supply in the study area. Continuous and discrete wavelet analyses are applied to assess the energy balance variability at multiple temporal scales and to identify the optimal mix of renewable energies, respectively. This work describes therefore an effective approach to investigate the temporal-scale dependency of the variance in the energy balance and can be further extended to different and more complex situations.
译文： 可再生能源具有不同的时空可变性，这会影响这些能源的发电量。不同可再生能源在时间和空间上的互补性可以降低供电的可变性，有助于匹配电力需求曲线。本研究考察了意大利东北部高山横断面上的互补性的时间结构，考虑了由光伏和径流式水能组成的 100%可再生能源组合方案。我们分析了可变可再生能源和电力需求的主要变异性尺度。此外，我们引入了一种新的度量标准，基于小波的互补指数，来量化两种不同能源之间的互补潜力。我们表明，该指数在不同的时间尺度上变化，有助于解释研究区域内供需之间的差异。连续和离散小波分析分别应用于评估多个时间尺度上的能量平衡变异性，并确定可再生能源的最佳组合。因此，本工作描述了一种有效的方法来研究能量平衡方差的时间尺度依赖性，并且可以进一步扩展到不同和更复杂的情况。
