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Interrogating uncertainty in energy forecasts: the case of the shale gas boom
Energy Transitions Pub Date : 2019-09-05 , DOI: 10.1007/s41825-019-00015-9
Adam Reed , Sean Ericson , Morgan Bazilian , Jeffrey Logan , Kevin Doran , Chris Nelder

The energy sector relies on analytical results to inform decision-making—from policy to investment. Over the last decade the United States has undergone a “revolution” in its energy landscape, due primarily to natural gas production from shale plays, as well as other factors. Despite the enormity of this change, it was hardly, or not at all, predicted or projected by forecasters, analysts, or industry experts even a year or two before its emergence. We consider what the projections looked like, how changeable they still remain, and implications for refining the interaction between analysis and decision-making in the energy sector. More broadly, we use the shale gas boom to illuminate the more universal challenges that energy forecasters face—and the solutions they employ—in managing and explaining two significant types of uncertainty: epistemic (unknown unknowns) and stochastic (known unknowns). Epistemic and stochastic uncertainties affect both the production of forecasts as abstractions of reality and our meta-considerations of how accurately such abstractions represent reality. Compounding these difficulties, these two domains of prediction—the world of the model and the world the model attempts to simulate—are often unconsciously confused or conflated, especially by the consumers of energy forecasts who do not themselves deal directly with forecast intricacies: industry analysts, scientists, advocates, and policymakers, among others. We thus attempt to elucidate a simple typology of energy forecast uncertainties and delineate the domains of prediction for decision-makers in the private, public, and research sectors who may benefit from a better understanding of how modelers themselves conceptualize and manage uncertainty. We conclude with a call for new and innovative discourse modes for discussing uncertainty in energy forecasting, both within the modeling community itself and in its engagements with decision-makers.



中文翻译:

质疑能源预测的不确定性:页岩气繁荣的案例

能源行业依靠分析结果为从政策到投资的决策提供信息。在过去十年中,美国的能源格局经历了一场“革命”,这主要是由于页岩气生产以及其他因素。尽管这一变化规模巨大,但预测者、分析师或行业专家甚至在其出现前一两年都几乎没有或根本没有预测或预计到这一变化。我们考虑这些预测是什么样的,它们仍然存在多大的变化,以及对完善能源部门分析和决策之间的相互作用的影响。更广泛地说,我们利用页岩气的繁荣来阐明能源预测者在管理和解释两种重要类型的不确定性时所面临的更普遍的挑战以及他们所采用的解决方案:认知性(未知的未知数)和随机性(已知的未知数)。认知和随机不确定性既影响作为现实抽象的预测的产生,也影响我们对这种抽象如何准确地代表现实的元考虑。使这些困难更加复杂的是,这两个预测领域(模型的世界和模型试图模拟的世界)经常会无意识地混淆或混为一谈,特别是那些本身不直接处理预测复杂性的能源预测消费者:行业分析师、科学家、倡导者和政策制定者等。因此,我们试图阐明能源预测不确定性的简单类型,并为私营、公共和研究部门的决策者描绘预测领域,他们可能会受益于更好地理解建模者本身如何概念化和管理不确定性。最后,我们呼吁采用新的和创新的话语模式来讨论能源预测的不确定性,无论是在建模界本身还是在与决策者的接触中。

更新日期:2019-09-05
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