ارزش انتخاب فن آوری تبدیل به گاز در یک طرح انتشار تجاری

Investment analysis is mostly implemented with Discounted Cash Flow (DCF) methods, such as the Net Present Value (NPV). The problem in a typical application of these methods is the limited ability to value real options, management's ability to adapt to changing market conditions or to revise decisions. This paper presents a simulation model, in which the investment is regarded as a single-firm problem in an operating environment with multiple exogenous and stochastic prices. The simulation model is used to explore the impact of emissions trading, and in particular the European Union Emissions Trading Scheme (EU ETS), on investments in Integrated Gasification Combined Cycle (IGCC) plants. Two real case studies are presented: modifications of an existing condensing power plant and a new combined heat and power plant. The benefit of the selected approach is that it can take into account the value of multiple simultaneous real options better than a standard DCF analysis. The results show that a straightforward application of DCF analysis can lead to biased results in competitive energy markets within an emissions trading scheme, where a number of uncertainties potentially combined with several real options can make quantitative investment appraisals very complex.

Investment analysis is mostly implemented with Discounted Cash Flow (DCF) methods, such as the Net Present Value (NPV). A DCF analysis essentially involves discounting the expected net cash flows from an investment at a discount rate that reflects the risk of those cash flows. Typically the analysis is based on scenarios, which presume management's passive commitment to certain operating strategies, and is accompanied with a sensitivity analysis to the components of the cash flow. The problem in the approach is its limited ability to value active flexibility or real options. 1 A real option is a right, but not an obligation, to take action concerning an investment project: for example, to alter operating scale or to switch inputs, such as fuels. It thus refers to management's ability to adapt to changing market conditions or to revise decisions. This paper presents a simulation model, in which the investment is regarded as a single-firm problem in an operating environment with multiple exogenous and stochastic prices.2 The simulation model is used to explore the impact of emissions trading, and in particular the European Union Emissions Trading Scheme (EU ETS),3 on investments in a specific energy production technology. Two real case studies are studied. The benefit of the selected approach is that it can take into account the value of multiple simultaneous real options better than a standard DCF analysis. Valuation of real options requires an expansion of the standard analysis. As a simple equation: the Extended Net Present Value (NPVext) is equal to the standard Net Present Value (NPV) plus the value of the real options (O) ( Trigeorgis, 1995). Literature provides different methods to the estimation of NPVext ranging from contingent claims analysis to dynamic programming and to simulation (e.g. Dixit and Pindyck, 1994; Amram and Kulatilaka, 1999). All the methods have strengths and weaknesses, and set different requirements for the problem formulation and availability of data. For example, contingent claims analysis is based on the idea that determination of the risk-adjusted discount rate is avoided through market-traded assets, such as futures for commodities. The method works, if the project cash flows can be completely replicated with market-traded assets, which is not currently the case, e.g. in heat and power projects within the EU ETS. In such cases, the determination of the risk-adjusted discount rate is necessary. Laurikka and Koljonen (2005) applied Monte Carlo simulation for valuation of a power generation investment within the EU ETS using two stochastic variables (price of electricity and emission allowance price) in a risk-adjusted framework. The simulation model presented here is also based on a risk-adjusted framework, but can simultaneously deal with multiple stochastic variables, such as prices of electricity, emission allowance, and fuels, to estimate the value of flexibility. The object of the case studies of this paper is the Integrated Gasification Combined Cycle (IGCC) technology. Solid fuel gasification technologies, such as IGCC, are promising alternatives for future heat and power generation due to the high generating efficiency and favourable characteristics regarding potential carbon dioxide capture (e.g. Harmoinen et al., 2002; Lako, 2004). The IGCC technology is expected to find first commercial applications in oil refineries and coal power condensed power plants (Harmoinen et al., 2002). Section 2 describes the basic structure of the model and the common data applied in the case studies. Specifications in the model, the case-specific data, and the model outcomes are presented in Sections 3 (gasification of biomass in an existing condensing power plant) and 4 (gasification of coal in a residential CHP plant). Section 5 concludes.

The present paper explored the impacts of emissions trading on valuation of IGCC investments. A stochastic price model, which is able to quantify the value of multiple simultaneous real options involved in the investment decision, was applied in the analysis. The outcome was compared to the results from a simple DCF analysis ignoring all real options. The results suggest that a straightforward application of DCF analysis can cause biased results in current competitive energy markets within an emissions trading scheme, where a number of uncertainties potentially combined with several real options can make quantitative investment appraisals very complex. The IGCC technology does not yet seem competitive in power plant retrofits within the EU ETS. The current investment cost of IGCC technology is too high for viable retrofit investments. The first case study analysed the value of the IGCC technology as an additional component to an existing power plant with a limited lifetime and found no significant differences in deterministic vs. stochastic valuation. The price of the option to switch fuel provided by the IGCC technology was too high. However, there was a remarkable difference to the straightforward NPV estimate totally ignoring real options. The second case study explored the value of a preparation investment to the potential later use of the IGCC technology. The price of such a compound option to switch fuel was too high with the current investment cost estimate. If the total investment were lower, the stochastic approach would give significantly different results from a deterministic approach and could even change the investment decision (according to a strict NPV rule). The additional benefit from a stochastic approach for investment appraisals depends on the individual parameters of the appraisal, such as the investment cost. A stochastic approach to valuation requires more input parameters and is more laborious than conventional methods. The additional work is probably negligible compared to the potential benefits in most—but not all—cases. An adequate pre-screening is therefore recommendable.