向可持续能源生产过渡的概率预测

Victor E. Gluzberg , Yuri A. Katz
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引用次数: 0

摘要

可以观察到,可再生能源技术的累计发电量随时间呈指数增长,而单位成本呈指数下降。然而,由于全球市场的饱和,即使采用可持续技术,年产量的指数级增长最终也会趋于平缓。这将导致累积产量随着时间的推移呈线性增长。为了捕捉这一定性图像,我们引入了一种新的累积生产模型,该模型采用了一种与传统物流模型不同形式的负反馈可持续技术。为了解释技术进步的不规则性,我们利用累积扩展的方法,可以对单位成本进行概率预测,而不依赖于潜在随机过程的特定模型和未来生产增长的情景。推导结果表明,在初始生产指数增长时期,单位成本的有效降低率略低于其平均值。各自的置信区间随预测范围的平方根线性增长。从长期来看,可持续生产模型预测期望单位成本随时间呈幂律下降。在这种情况下,单位成本的对数的预测误差随着预测范围的对数的平方根而缓慢增长。为了说明该方法,我们对到2060年的太阳能光伏组件价格进行了概率预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic forecasting of transition towards sustainable energy production
It is observed that cumulative production of electricity by renewable technologies increases exponentially with time, while the unit cost exponentially decreases. However, the exponential growth of annual production even by a sustainable technology will eventually flatten due to saturation of the global market. This should result in a linear growth of cumulative production with a passage of time. To capture this qualitative picture, we introduce the novel model of cumulative production by a sustainable technology with negative feedback in the different form than in the traditional logistic model. To account for irregularity of technological progress, we utilize the method of cumulant expansion that allows to make probabilistic forecasts for the unit cost, which do not depend on the specific model of underlying stochastic processes and a scenario of the future production growth. The derived results demonstrate that during the period of initial exponential growth of production, the effective rate of decrease of the unit cost is slightly lower than its average value. The respective confidence interval is growing linearly with the square root of the forecasting horizon. In the long run, the model of sustainable production forecasts the power law decline of the expected unit cost with time. In this regime, the forecasting error of the logarithm of the unit cost is slowly growing as the square root of the logarithm of the forecasting horizon. To illustrate the method, we make probabilistic forecasts for prices of solar photovoltaic modules up to 2060.
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