Escuela Politécnica Nacional, Ladrón de Guevara, E11-253, Quito, Ecuador.
Center for Energy and Environmental Sciences, University of Groningen, 9747, AG, Groningen, the Netherlands.
Sci Total Environ. 2019 Dec 15;696:133959. doi: 10.1016/j.scitotenv.2019.133959. Epub 2019 Aug 17.
Freshwater has spatial and temporal constraints, affecting possibilities to generate electricity. Previous studies approached this from a water perspective quantifying water consumption of electricity to optimize water use, or from an electricity perspective using modeling methods to optimize electricity output. However, power plants consume different water volumes per unit of electricity, depending on the applied technology, and supply systems often include a mix of different technologies with a different water footprint (WF), an indicator of water consumption, per unit of electricity. When water availability varies in time, probably the contribution of different electricity generating technologies also varies in time, resulting in WF fluctuations. Focusing on electricity generation from the water perspective, we assessed how water availability affects an electricity mix's dynamics and its blue WF using Ecuador as a case study. We studied the Amazon and Pacific basins, which have different temporal and spatial water availability fluctuations, assessing monthly water availability, electricity production, and blue WFs per plant. The Amazon basin has smaller temporal and spatial availability fluctuations than the Pacific. The difference between the largest and smallest water availability in the Amazon basin is two-fold, in the Pacific four-fold. Hydropower generation in the Amazon basin contributes more than 60% to the electricity mix. However, hydropower is directly affected by water availability, and its production decreases in water-limited periods. For biomass plants, limited water availability affects the fuel source, sugarcane bagasse. As water availability decreases, other technologies in the mix take over, causing WF variation (from 4.8 to 8.6 10 m per month). Usually, less water-availability means more water-efficiency, implying fossil-fueled plants in the Pacific take over from hydropower in the Amazon. It is relevant to assess the water-electricity nexus in countries with electricity mixes dominated by hydropower because energy planning needs to consider water availability and electricity mix dynamics.
淡水具有时空约束,影响发电的可能性。以前的研究从水的角度出发,通过量化电力的耗水量来优化水的利用,或者从电的角度出发,使用建模方法来优化电力输出。然而,发电厂每单位电量消耗的水量不同,这取决于所采用的技术,而且供应系统通常包括不同技术的混合,每种技术的单位电量耗水量(WF)即水足迹不同。当水资源在时间上变得不可用时,不同的发电技术的贡献可能也会随时间而变化,从而导致 WF 的波动。从水的角度关注电力生产,我们评估了水资源的可获得性如何影响电力组合的动态及其蓝 WF,以厄瓜多尔为例进行了研究。我们研究了亚马逊河和太平洋流域,这两个流域的水资源可获得性具有不同的时间和空间波动,评估了每月的水资源可获得性、电力生产以及每个工厂的蓝 WF。亚马逊流域的时间和空间可获得性波动比太平洋小。亚马逊流域最大和最小水资源可获得性之间的差异是两倍,而在太平洋则是四倍。亚马逊流域的水力发电对电力组合的贡献超过 60%。然而,水力发电直接受到水资源可获得性的影响,在水资源有限的时期,其产量会下降。对于生物质能工厂,有限的水资源可获得性会影响燃料来源——甘蔗渣。随着水资源可获得性的降低,组合中的其他技术会接管,导致 WF 发生变化(每月从 4.8 到 8.6 10 m)。通常,水资源可获得性越低意味着水效率越高,这意味着在太平洋,化石燃料发电厂会取代亚马逊的水力发电厂。评估以水力发电为主的国家的水电关系具有重要意义,因为能源规划需要考虑水资源的可获得性和电力组合的动态。