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Capturing the Effects of Oil Price Uncertainty in Carbon Integration Network Design
Industrial & Engineering Chemistry Research ( IF 3.8 ) Pub Date : 2019-02-13 , DOI: 10.1021/acs.iecr.8b05185
Rola Malaeb 1 , Hussein Tarhini 1 , Sabla Y. Alnouri 2
Affiliation  

Carbon integration is a novel concept that targets the recovery and allocation of industrially emitted CO2 streams into CO2-using sinks, with the goal of attaining a CO2 allocation strategy that meets a desired carbon dioxide emission reduction target and an ultimate aim of minimizing the cost of the network while maximizing any revenue. Enhanced oil recovery (EOR) is considered one of the most attractive CO2 sink options. CO2 streams that are delivered and injected into EOR sites are great revenue sources for CO2-supplying entities. Since oil pricing heavily affects the revenue generated via CO2 streams injected into EOR sites, this paper studies the effect of oil price fluctuations onto the design of carbon integration networks. Hence, oil pricing has been selected as the main uncertainty parameter and has been fed into a linearized multiperiod carbon integration model using stochastic data. Since oil prices vary periodically, this model has been formulated over several time periods, in which the oil pricing parameters are allowed to change over time. The proposed model has been optimized using two different approaches: (1) the binomial lattice approach, which primarily utilizes average uncertainties as expected values, and (2) the multiscenario approach.

中文翻译:

在碳整合网络设计中捕获油价不确定性的影响

碳整合是一个新颖的概念,其目标是将工业排放的CO 2物流回收和分配到使用CO 2的水槽中,目的是实现满足期望的二氧化碳减排目标并最大限度地减少二氧化碳的最终目标的CO 2分配策略。网络成本,同时最大程度地提高收入。增强采油率(EOR)被认为是最有吸引力的CO 2汇池选择之一。输送并注入EOR站点的CO 2物流是供应CO 2的实体的重要收入来源。由于石油定价严重影响了通过CO 2产生的收入注入EOR站点的天然气流,本文研究了石油价格波动对碳整合网络设计的影响。因此,石油价格已被选作主要的不确定性参数,并已使用随机数据输入到线性化的多期碳整合模型中。由于石油价格会定期变化,因此该模型是在多个时间段内制定的,其中允许石油价格参数随时间变化。所提出的模型已使用两种不同的方法进行了优化:(1)二项式点阵方法,该方法主要利用平均不确定性作为期望值;(2)多情景方法。
更新日期:2019-02-14
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