A dynamic programming approach for modeling low-carbon fuel technology adoption considering learning-by-doing effect

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• 作者：Yuche Chen^a ; ^{ychchen@ucdavis.edu} ; Yunteng Zhang^b ; Yueyue Fan^b ; Kejia Hu^c ; Jianyou Zhao^d
• 关键词：Dynamic programming ; New technology adoption pathway ; Learning by doing effect
• 刊名：Applied Energy
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：185
• 期：part_P1
• 页码：825-835
• 全文大小：910 K
• 卷排序：185

文摘

Dynamic programming method is used in transportation fuel portfolio planning. The learning effect in new fuel technology is endogenously modeled through an experience curve. Cellulosic biofuels play critical role in de-carbonization transport sector in near term. The initial 3–4 billion gallons production is critical to bring down cellulosic biofuels’ cost. Large penetration of Zero Emission Vehicles will discourage development of cellulosic biofuels.