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Über dieses Buch

The liberalization process, tightening environmental standards and the need for replacing aged power plants force European utilities to optimize their future generation mix. Power plants are real assets and as a consequence the power plant park of a utility firm equals a portfolio of different generation assets. This thesis adds to the understanding how to identify an efficient generation portfolio through time by assuming a non-constant feasible set. According to our results a combination of conventional thermal and renewable energies turn out to be efficient in terms of expected value and risks. Therefore, implementing a strategy based on renewable energies which cause less CO2 per MWh generated electricity clearly pays off.
Potential readership includes scholars from energy economics and energy finance as well as interested practitioners involved in these areas.



Chapter 1. Introduction

As evidenced in many reports of the International Energy Agency (IEA), by 2030 power consumption in the world will be twice as much as the current level at the end of 2009. While in Asia the need for investments in generation capacity is driven by the soaring demand for electricity, the growth-rate in Europe is rather moderate. However, huge investments in generation capacity are still required, as the European power plant park is aging.
Sebastian Rothe

Chapter 2. Economics of energy markets

The purpose of this section is to illustrate the main risk factors that have an impact on the profitability of power plants. Therefore, the outcome of liberalization and differences to regulated electricity markets are presented first. Secondly, the variety of power plant technologies is introduced to highlight individual merits regarding market, operational and other risk factors. Thirdly, we describe the European Emission Trading Scheme (EU ETS), as carbon prices affect the profitability of conventional thermal power plants.
Sebastian Rothe

Chapter 3. Mean-variance valuation approach for power plants

This chapter introduces a theoretical framework to analyze the issues targeted by the thesis. Therefore, first the traditional discounted free cash flow (DCF) valuation methodology is presented including a breakdown of the most relevant input parameters. Secondly, we demonstrate how computer simulation experiments are able to take various risk factors into account in order to gain a range of the expected DCF asset value. Thirdly, we introduce the portfolio theory of Markowitz (1952) to identify assets which lead to efficient generation portfolios.
Sebastian Rothe

Chapter 4. Simulation based model for analyzing generation portfolios

This chapter deals with the simulation procedure of the valuation model. For this purpose, we will first introduce the risky variables and corresponding probability distributions. In addition, we will show a methodology to cope with dependencies among the risky model input variables. Secondly, we will define technical, cost and price assumptions.
Sebastian Rothe

Chapter 5. Empirical analyses of European generation portfolios

The purpose of this chapter is to present the simulation results for the optimization of power generation portfolios. However, we will first describe the commodity and meteorological input data. Besides we will show not only the empirical correlation but also the simulated correlation results of these variables.
Sebastian Rothe

Chapter 6. Conclusions

This chapter responds to the underlying research questions by summarizing the main results of the simulation model. Based on the results, we derive implications for management and research practice and give an outlook for future research.
Sebastian Rothe


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