A global analysis of the progress and failure of electric utilities to adapt their portfolios of power-generation assets to the energy transition
A global analysis of the progress and failure of electric utilities to adapt their portfolios of power-generation assets to the energy transition
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DOI：
10.1038/s41560-020-00686-5
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发表时间：
2020-08-31
期刊：
影响因子：
56.7
通讯作者：
Alova, Galina
中科院分区：
文献类型：
--
作者：
Alova, Galina
低碳技术在发电领域的渗透对以化石燃料为重点的电力公司提出了挑战。虽然现有的，主要是定性的，文献强调多样化到可再生能源的可能的适应战略，全面的定量了解公用事业的投资组合脱碳一直缺失。这项研究弥合了这一差距，系统地量化了过去二十年来全球3,000多家公用事业公司从化石燃料发电向可再生能源的转变。它将基于机器学习的聚类算法应用于历史全球资产级数据集，提取其中的四个宏观行为和子模式。四分之三的公用事业公司没有扩大投资组合。在剩下的公司中，少数几家公司在其他资产之前种植煤炭，而一半的公司青睐天然气，其余的公司则优先考虑可再生能源增长。引人注目的是，60%的可再生能源优先公用事业公司没有停止同时扩大化石燃料组合，而减少化石燃料组合的只有15%。这些发现表明电力系统惯性以及公用事业驱动的碳锁定和资产搁浅风险。为了实现气候目标，电力公司应该减少其电力生产的碳化，但这一过程的历史分析很少。Galina Alova利用机器学习和来自全球3,000多家公用事业公司的数据表明，即使是优先考虑可再生能源的公用事业公司也在继续增加其化石燃料发电能力。
The penetration of low-carbon technologies in power generation has challenged fossil-fuel-focused electric utilities. While the extant, predominantly qualitative, literature highlights diversification into renewables among possible adaptation strategies, comprehensive quantitative understanding of utilities' portfolio decarbonization has been missing. This study bridges this gap, systematically quantifying the transitions of over 3,000 utilities worldwide from fossil-fuelled capacity to renewables over the past two decades. It applies a machine-learning-based clustering algorithm to a historical global asset-level dataset, distilling four macro-behaviours and sub-patterns within them. Three-quarters of the utilities did not expand their portfolios. Of the remaining companies, a handful grew coal ahead of other assets, while half favoured gas and the rest prioritized renewables growth. Strikingly, 60% of the renewables-prioritizing utilities had not ceased concurrently expanding their fossil-fuel portfolio, compared to 15% reducing it. These findings point to electricity system inertia and the utility-driven risk of carbon lock-in and asset stranding.To meet climate goals, electric utilities should be decarbonizing their power production, but historical analyses of this process are scarce. Using machine learning and data from more than 3,000 utilities globally, Galina Alova shows that even utilities that prioritize renewable energy continue to grow their fossil fuelled generation capacity.