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Future costs of key low-carbon energy technologies: Harmonization and aggregation of energy technology expert elicitation data

机译:关键低碳能源技术的未来成本:能源技术专家启发数据的协调和汇总

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In this paper we standardize, compare, and aggregate results from thirteen surveys of technology experts, performed over a period of five years using a range of different methodologies, but all aiming at eliciting expert judgment on the future cost of five key energy technologies and how future costs might be influenced by public R&D investments. To enable researchers and policy makers to use the wealth of collective knowledge obtained through these expert elicitations we develop and present a set of assumptions to harmonize them. We also aggregate expert estimates within each study and across studies to facilitate the comparison. The analysis showed that, as expected, technology costs are expected to go down by 2030 with increasing levels of R&D investments, but that there is not a high level of agreement between individual experts or between studies regarding the technology areas that would benefit the most from R&D investments. This indicates that further study of prospective cost data may be useful to further inform R&D investments. We also found that the contributions of additional studies to the variance of costs in one technology area differed by technology area, suggesting that (barring new information about the downsides of particular forms of elicitations) there may be value in not only including a diverse and relatively large group of experts, but also in using different methods to collect estimates. (C) 2014 Elsevier Ltd. All rights reserved.
机译:在本文中,我们对十三年来对技术专家的调查结果进行了标准化,比较和汇总,这些调查是在五年内使用一系列不同的方法进行的,但其目的都是要引起专家对五种关键能源技术的未来成本以及如何评估的判断。未来的成本可能会受到公共R&D投资的影响。为了使研究人员和政策制定者能够利用通过这些专家启发获得的大量集体知识,我们制定并提出了一系列假设以使它们协调一致。我们还汇总了每个研究以及各个研究中的专家估计,以促进比较。分析表明,正如预期的那样,随着R&D投资水平的提高,预计到2030年技术成本将下降,但是各个专家之间或研究之间不会从中受益最大的技术领域之间没有达成高水平的协议。研发投资。这表明,对预期成本数据的进一步研究可能对进一步告知R&D投资有用。我们还发现,附加研究对一个技术领域中成本差异的贡献因技术领域而异,这表明(除非提供有关特定形式诱因的不利方面的新信息),不仅仅包括多样化且相对庞大的专家组,而且在使用不同的方法来收集估算值。 (C)2014 Elsevier Ltd.保留所有权利。

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