posted on 2019-02-01, 00:00authored byRola Malaeb, Hussein Tarhini, Sabla Y. Alnouri
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.