کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
568883 1452296 2014 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evaluation of two alternative carbon capture and storage technologies: A stochastic model
ترجمه فارسی عنوان
ارزیابی دو فناوری ضبط و ذخیره جایگزین کربن: یک مدل تصادفی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
چکیده انگلیسی


• The paper evaluates carbon capture and storage (CCS) with enhanced oil recovery (EOR).
• There are some uncertainties: the prices of electricity, oil and carbon allowances.
• A general stochastic model is calibrated with data for the UK.
• The investments with EOR in the North Sea might be profitable at current oil prices.
• The investments without EOR are not profitable at current oil prices.

In this paper we evaluate two alternative CCS technologies at a coal-fired power plant from an investor's point of view. The first technology uses CO2 for enhanced oil recovery (EOR) paired with storage in deep saline formations (DSF) and the second merely stores CO2 in DSF. The paper updates and improves on an earlier publication by Tzimas et al. (2005). For projects of this type there are many sources of risk, three of which stand out: the price of electricity, the price of oil and the price of carbon allowances. In this paper we develop a general stochastic model that can be adapted to other projects such as enhanced gas recovery (EGR) or industrial plants that use CO2 for either EOR or EGR with CCS. The model is calibrated with UK data and applied to help understand the conditions that generate the incentives needed for early investments in these technologies. Additionally, we analyse the risks of these investments. Investments with EOR and secondary DSF storage can only be profitable (NPV > 0) when there is a high long-term equilibrium price for oil of more than $56.38/barrel. When the investment decision can be made at any time, i.e. there is an option value, then the trigger value for optimal investment is significantly higher.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Modelling & Software - Volume 54, April 2014, Pages 182–195
نویسندگان
, , ,