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Evaluating investment in base load coal fired power plant using real options approach

Evaluating investment in base load coal fired power plant using real options approach
Evaluating investment in base load coal fired power plant using real options approach
This thesis investigates the impact of uncertainty on investment in a coalfired power plant using a real options (RO) framework. It is organized in five chapters. In the first chapter I give an outline of the thesis.

In Chapter 2 I review the background material. I describe the electricity sector in the pre- and post-liberalization periods and discuss the implication of the transition on investment in new generation capacity. Further, I analyze the mainstream approach to investment analysis used by the majority of electricity companies, the discounted cash flow (DCF) approach. Next, I describe an alternative approach for evaluating investments, RO.

In Chapter 3 I perform an econometric analysis of dark spread prices. I select four different stochastic processes and fit them to the observed data. The goal is to find which of the four processes (arithmetic Brownian motion (ABM), Ornstein-Uhlenbeck (OU), Cox-Ingersoll-Ross (CIR) and the Schwartz one-factor process) can best describe the evolution of dark spread prices. The analysis shows that the CIR process is the most appropriate model to use to represent the evolution of dark spread prices.

In Chapter 4 I evaluate an investment in a coal-fired power plant assuming the dark spread is the only source of uncertainty and using the stochastic processes for which I estimated parameters in Chapter 3. First I calculate the optimal investment threshold using a traditional budgeting approach based on the DCF principle. Following this, using the RO framework, I calculate the optimal investment threshold for the four stochastic processes. I conclude that one should use mean reverting process to model the investment decision but the choice of mean reverting process does not significantly affect the investment threshold values.

In Chapter 5 I extend the analysis and model coal and electricity prices separately. Now the investment decision is affected by two factors: the price of electricity (output) and the price of coal (input). The goal of this chapter is to analyze whether this increase in complexity (going from a one-factor to a two-factor model) affects the result obtained in the previous chapter. Given the different dynamics of electricity and coal prices, I find that this approach enriches the investment analysis and gives additional insights. In particular, the higher the coal price, the greater the dark spread needs to be in order to undertake the investment. Finally, Chapter 6 concludes.

The thesis contributes to the existing knowledge in several ways. RO have been applied to the electricity sector before, but this is the first time they have been applied to the evaluation of investment in a coal-fired power plant. Secondly, this is the first time that dark spread, electricity and coal prices are modeled for use in a RO analysis. Finally, the thesis provides a comparison of investment analysis for a coal-fired power plant using RO based on single and two state variables, which has not been carried out so far.
University of Southampton
Brajkovic, Jurica
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Brajkovic, Jurica
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Mason, Robin A
12af1112-cb0d-4c0f-b8bb-f22a8b885333
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51

Brajkovic, Jurica (2010) Evaluating investment in base load coal fired power plant using real options approach. University of Southampton, School of Social Sciences, Doctoral Thesis, 164pp.

Record type: Thesis (Doctoral)

Abstract

This thesis investigates the impact of uncertainty on investment in a coalfired power plant using a real options (RO) framework. It is organized in five chapters. In the first chapter I give an outline of the thesis.

In Chapter 2 I review the background material. I describe the electricity sector in the pre- and post-liberalization periods and discuss the implication of the transition on investment in new generation capacity. Further, I analyze the mainstream approach to investment analysis used by the majority of electricity companies, the discounted cash flow (DCF) approach. Next, I describe an alternative approach for evaluating investments, RO.

In Chapter 3 I perform an econometric analysis of dark spread prices. I select four different stochastic processes and fit them to the observed data. The goal is to find which of the four processes (arithmetic Brownian motion (ABM), Ornstein-Uhlenbeck (OU), Cox-Ingersoll-Ross (CIR) and the Schwartz one-factor process) can best describe the evolution of dark spread prices. The analysis shows that the CIR process is the most appropriate model to use to represent the evolution of dark spread prices.

In Chapter 4 I evaluate an investment in a coal-fired power plant assuming the dark spread is the only source of uncertainty and using the stochastic processes for which I estimated parameters in Chapter 3. First I calculate the optimal investment threshold using a traditional budgeting approach based on the DCF principle. Following this, using the RO framework, I calculate the optimal investment threshold for the four stochastic processes. I conclude that one should use mean reverting process to model the investment decision but the choice of mean reverting process does not significantly affect the investment threshold values.

In Chapter 5 I extend the analysis and model coal and electricity prices separately. Now the investment decision is affected by two factors: the price of electricity (output) and the price of coal (input). The goal of this chapter is to analyze whether this increase in complexity (going from a one-factor to a two-factor model) affects the result obtained in the previous chapter. Given the different dynamics of electricity and coal prices, I find that this approach enriches the investment analysis and gives additional insights. In particular, the higher the coal price, the greater the dark spread needs to be in order to undertake the investment. Finally, Chapter 6 concludes.

The thesis contributes to the existing knowledge in several ways. RO have been applied to the electricity sector before, but this is the first time they have been applied to the evaluation of investment in a coal-fired power plant. Secondly, this is the first time that dark spread, electricity and coal prices are modeled for use in a RO analysis. Finally, the thesis provides a comparison of investment analysis for a coal-fired power plant using RO based on single and two state variables, which has not been carried out so far.

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Published date: November 2010
Organisations: University of Southampton

Identifiers

Local EPrints ID: 171553
URI: https://eprints.soton.ac.uk/id/eprint/171553
PURE UUID: 6681b484-25f4-43b3-8964-b46db252aafa
ORCID for Jean-Yves Pitarakis: ORCID iD orcid.org/0000-0002-6305-7421

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Date deposited: 03 Feb 2011 11:52
Last modified: 29 May 2019 00:35

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