EU ETS Impact on Electricity Market
Disclaimer: This dissertation has been submitted by a student. This is not an example of the work written by our professional dissertation writers. You can view samples of our professional work here.
Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of UK Essays.
To meet its obligations to reduce greenhouse gas (GHG) concentration under the Kyoto Protocol, the European Union (EU) introduced the first cap-and-trade mechanism for carbon dioxide emissions in the world starting in 2005. Launched in 2005, the EU ETS works on cap-and-trade principle by putting a cap or an upper limit on the total amount of CO2 emissions per annum, which can be emitted by industries, power plants and other installations in the system. Within this cap, the emitters receive emission allowances, which indicate the maximum allowable CO2 emissions. However, these emission allowances are tradable within the EU, and if the emitters need more CO2 allowances, they are free to purchase from the entities, which have excess quantities of emission allowances thus rewarding the entities for reducing their emissions. In addition, the companies may get extra CO2 allowances by implementing green or less carbon intensive technologies to under CDM and JI mechanisms. It is reasonable to say that the implementation of EU ETS is a serious effort towards global CO2 emissions reduction with the ultimate goal being bring about drastic reduction in CO2 emissions (80% reduction from the base year emissions by 2050) and promote low carbon energy production technologies in the long term.
The emission trading scheme started with first three-year trading period (2005-2007) recognized as a trial period and this was followed by the present five year (2008-2012) second phase of EU ETS.In each phase, the EU member states allow a maximum amount of carbon dioxide equivalents to be emitted by the installations included in the EU ETS. This emission limit is expected to be reduced in future periods, thereby increasing the incentive for technology investments that reduce emissions. In the third phase of EU-ETS, which would come into force from 2013 for a period of eight years (until 2020), the grandfathering or the free allocation of carbon credits will no more be an option for energy producers and they would need to buy the emission allowances via market based auctioning of emission rights. This is expected to further increase the marginal cost of electricity production using conventional sources such as coal and gas fired power plants, which in principle would make investments in renewables and green technologies attractive.
However, it should be kept in mind that the European Union is expected to need some 650GW of new power capacity and to replace some 330GW of existing power stations over the next 30 years (IEA, 2003a). Investment in new power is also essential for a well-functioning electricity market. But, the decisions pertaining to investment in new capacity are surrounded by considerable uncertainties about the future economics of the projects. On one hand, the introduction of EU ETS is expected to promote green technology investments in the long run, on the other hand, the auctioning of emission allowances, unclear policies in long term and volatility of CO2 prices are seen as the main hurdles for investments in electricity production industries.
The present study is an attempt to critically analyze the impact of EU ETS on the investment outlook in the electricity market over the long term. The study builds up the arguments based on the work carried out by previous researchers and identifies the key issues which affect the investment decisions in the power sector. The study extrapolates the arguments to assess the future investment scenario in the EU electricity generation within EU ETS regime.
The main purpose of the EU ETS is to achieve emission reduction targets at minimum costs and to promote global innovation (EU, 2005).Ideally, the “cap and trade” approach ensures that emissions are reduced such that it is cheapest to do so and that the market price for allowances creates a effective price signal and reflects their scarcity in the system (Baumol & Oates, 1988). In other words, the EU Emission Trading Scheme (ETS) creates a continental market for CO2 emissions by attaching an economic value to environmental externalities. In this market, the price of carbon should be equal to the lowest marginal abatement cost which encourages power utilities to shift towards a lower carbon intense fuel mix at the cheapest cost. Hence in recent times, the marginal cost of electricity production for different technologies has become the most important criteria for investment decisions.
Considerable amount of research has been put in assessing current and future performance of the EU ETS in achieving its main aim of cost-efficient greenhouse gas abatement. The researchers have analyzed expected effects of different design alternatives of the regulation on aggregated (i.e., not firm-specific) technology investment decisions. The main subject of all these studies have been the different rules governing the allocation of emissions allowances. Whereas earlier work by researchers was more of a general manner (Vesterdal and Svendsen, 2004), recent studies have been focusing on incentives and distortions introduced by different detailed allocation rules for e.g. closure rules, updating, and allowance allocations to new entrants (Ahmanet al., 2007,Ahman and Holmgren, 2007,Betzet al., 2006 & Neuhoffet al., 2006). Another set of studies tries to elucidate the effect of emission trading on operating decisions and investment options by analyzing the varying cost increases for different technologies. Whereas Reinaud (2003)analyzed the effects of different carbon prices on profitability of different power plant capital investments,Laurikka and Koljonen (2006)used real option pricing approach to incorporate the large uncertainties in investment decisions.
Also about the power generation technology, Laurikka developed a stochastic simulation model based on the real option theory, and explored the influence of carbon emissions trading, the EU ETS in particular, on integrated gasification combined cycle (IGCC) investment. The results showed that a straightforward application of discounted cash flow (DCF) analysis may not be a appropriate and might lead to biased results within the carbon emissions trading scheme, where a number of uncertainties potentially combined with several real options could make quantitative investment appraisals very complex. Moreover, the IGCC technology did not yet seem competitive in power plant retrofits within the EU ETS, for its investment cost was too high for viable retrofit in investment (Laurikka, 2006).
Case studies of German & Finnish Power Sector
Existing research showed that the carbon trading market had become an important factor for enterprises in the decision to invest in energy technology, while the extent of its impact appeared quite limited. In this regard, Hoffmann empirically studied the impact of the EU ETS on German electricity sector investment decisions during 2005-2007, finding there was little empirical evidence regarding its actual effects on corporate investment decisions; specifically, the EU ETS constituted the main driver for small-scale investment with short amortization times, while its impact on large-scale investment in power plants or in R&D efforts was quite limited. To address this issue, the author suggested that policy-makers should reflect their long-term reduction intentions in the scarcity of allowances, provide more incentives to increase efficiency and reduce regulatory uncertainty (Hoffmann, 2007).
By taking a case study from Finnish power sector, Laurikka, studied the impact of emission trading scheme on investment decision. They extended the standard discounted cash flow (DCF) analysis to take into account the value of two real options: the option to wait and the option to alter operating scale. They argued that in a quantitative investment appraisal, the impact of emissions trading not only depends on the expected level of allowance prices, but also on their volatility and correlation with electricity and fuel prices. Emission trading has significant impacts on the results of a quantitative investment appraisal through several variables: through the output prices, through the value of the surrendered allowances, through the operating hours and through the value of free allowances allocated for installations. This makes it challenging to assign the weights to the impacts. The case study shows that the uncertainty regarding the allocation of emission allowances is critical in a quantitative investment appraisal of fossil fuel-fired power plants (Laurikka et al, 2006).
Investment evaluation methodology: Discounted cash flow vs. Real options approach
Power generators normally employ discounted cash flow (DCF) model to evaluate the economic merits of different technology options, and in particular a surrogate of the DCF approach, the so-called levelized cost methodology. Within this approach all power generation costs (i.e., capital, operation and maintenance, and fuel costs) are discounted to a present value and then divided by the total discounted output over the lifetime of the plant, hence the levelized cost method results are thus an average cost per unit of electricity produced (e.g., Bemis and DeAngelis, 1990). This cost is then compared over different new investment options. However, all DCF methods suffer from a serious limitation as the methodology itself does not allow explicit consideration of uncertainty and flexibility.
This gives rise to the need for the project evaluation techniques having capabilities to explicitly consider the uncertainty and flexibility. Real option valuation techniques represent such a tool to assess how the economic value of selected Swedish power generation projects are affected by uncertainties related to: (a) the green certificate scheme as well as carbon emissions trading within EU ETS; (b) fuel prices and; (c) electricity price. For this reason the interest of many analysts and the energy companies has been growing towards real option valuation techniques (Dixit and Pindyck, 1994). An option represents an opportunity, i.e., the right but not the obligation to take some action in the future. According to the real options approach, when an agent decides to undertake an irreversible investment, it gives up the option of waiting for new information that might affect the attractiveness or the timing of the investment. The option value, which is destroyed by undertaking the investment decision, is an opportunity cost that must be taken into account in calculating the overall value of the investment. Therefore, in order to optimize the project implementation by an amount equal to the value of keeping the deferral option alive, at a given point in time, the present value of benefit streams to be generated would have to exceed the costs incurred. As a result, by analyzing the problem faced by power sector operators with a real option framework, a relevant change of perspective is observed.
The real options approach provides a realistic modeling approach with the option to include uncertainties as in case of EU ETS regime. However, this might either have a negative impact on the investment decisions or delay the investments in electricity markets. The effect is significant as the electricity generation investments are capital intensive and the investors have a bias towards risk averse approach in light of policy and regulatory uncertainties.
The uncertainties associated with the auctioning on allowances and lack of policy clarity for long run has also been responsible for investment delays in the EU electricity markets. Actually, there exists a threshold price that significantly varies depending on both the decision rules adopted by power players, and how the policy makers implement the EU ETS. By applying a Real option framework, the EU allowance price triggering the technological shift significantly rises when considering the policy uncertainties resulting in adverse impact on power investments and green technology promotions.
The interrelation between policy measures and uncertainties should be taken into account for at least two reasons: (1) Policies could directly affect the power price and thus increase the level of uncertainties and (2) affect the input price, changing the optimal choice of technology. Moreover, energy and climate policy - not the least the green certificate system and the European emission trading systems for carbon dioxide - may add to investment uncertainties. The negative impact on overall investments in the power industry as the result of the ETS implementation appears inevitable, but on the other hand this does guide the choice of generation technologies for new entrants. A new generation plant is normally expected to keep operation for 20-30 years. However, in making the decision only limited and short-term market information is available for investors, and many uncertain factors will be encountered. Hence, setting a long term ETS policy is crucial for providing a clear incentive for investing in new low-emission technologies. Also depending on the climate policy, the investments are affected differently, foremost on the carbon cost resulting from the policies. As a consequence, climate policies might indirectly put an upward pressure on the electricity price through the absence of investments in the power sector.
For example, in the third phase of the EU ETS commencing from 2013, the free allocations of emission permits will not be an option for electricity generation industries, and the industries would need to acquire the emission allowances via market based auctioning mechanism. This is supposed to create wild fluctuations in carbon prices, and would also result into increase in the electricity prices. This uncertainty in carbon pricing introduces high risks in investment decisions. Hence the companies in general align the planning processes for investments with the timeline for regulatory decisions when new information becomes available and associated uncertainties decrease. Hoffmann carried out a study of inventors' outlook in German electricity generation industries by interviewing the company representatives. Following is the quote from above study expressing the views investment decisions post 2012 (Hoffmann, 2007):
“All power plants which are only operational after 2012 will have difficulties due to post-2012 uncertainty. They have been put on hold because economic evaluation is difficult. At the moment, no plant seems profitable.”
Thus, companies try to align and optimize their investment decisions in accordance with the timeline of regulatory developments of the EU ETS. This is, for example, done by initiating planning processes for new power plants with different technologies and at different locations. Then a decision regarding which of them to realize can be taken as late as possible when regulatory conditions have become clear. A main reason for this effect is the short duration of trading periods, compared to higher amortization times in the electricity industry. While the amortization of a fossil fuel power plant may be 15-20 years, planning reliability only exists for 3-5 years since in the current trading scheme the detailed allocation rules are renegotiated for each trading period. Accordingly, industry representatives are in favor of longer trading periods which should be more or less in accordance with amortization times for power generation industries in order to increase planning reliability. Thus, the investors are subjected to the additional complexity of a changing regulatory scheme while taking investment decisions with the EU ETS regime This requires them to align the timing of investment decisions and planning processes with developments of the EU ETS in order to reduce risk.
Investment timing and technology choice
Investment timing and technology choice are of principal interest to not only to policy-makers but also to the various market participants. Due to the non-storage nature of electricity, investments are crucial to ensure the balance between supplies and future demand expectations and hence the investment timing can therefore strongly affect the power price. In addition, there are only a limited number of available alternative technology options for power production. For example, in Sweden, there is a prohibition to invest in large-scale hydro and nuclear power reducing the available technologies to wind-, gas- and bio power (Lundmark & Pettersson, 2008). This might force power generators to invest in more expensive technologies that require higher power prices in order to make them financially attractive. Each technology is associated with different cost structures and uncertainties in input price, power price and policy formulations, which together with the irreversibility of the investment affect the investment behavior. Through technological improvements and learning the initial investment costs are most likely to decrease over time. However, there is no a priori basis of estimating this reduction for different technologies.
The lead-time generated by the often prolonged permit processing for green-field investments also has an effect on the level of investment. In terms of the permitting processes for new power plants the results suggests that if the investment cannot occur in the first time period it is more likely that the investor will wait with the investment or choose not to invest at all. Thus, a lengthy permitting process will result in investment delay and in general would have a negative affect on the investment timing.
Size and timing of the initial investment together with the subsequent annual cash flows mainly determine the financial performance of a power investment and the flexibility in timing gives the investor a valuable option to wait for new information. The standard models of irreversible investment under uncertainty show that the value of this option increases with a higher degree of uncertainty in the operating environment (McDonald and Siegel, 1986). As the EU ETS introduces new price risks for capacity investments, it should thus contribute to this direction. Although on the other hand, it has been argued that emission trading as such does not reduce a firm's incentive to invest in abatement capital, such as renewable technologies, relative to e.g. emission taxes, since the most important uncertainty factor-the abatement cost uncertainty-is there irrespective of the regulatory instrument (Zhao, 2003).
Increased risk to investors and the diversification
In a deregulated market private investors typically have to bear a greater portion of the investment risk compared to a monopoly utility in a regulated market. Due to the large volatility of the allowance price and associated regulatory uncertainties, the EU ETS constitutes significant risks for technology investment decisions. Michanek and Söderholm argued in their work that delayed and uncertain permitting processes also increase investors' risks (Michanek and Söderholm, 2006). There are also important implications of the scenario character of regulatory uncertainty, which especially relate to diversifying investments and creating flexibility. As companies need to be prepared for multiple and changing scenarios regarding fuel prices, CO2allowance price, and climate regulation, they try to optimize the mix of power generation technologies. Although such types of diversification strategies are not new to the electricity industry, the uncertainties in current climate policy appear to be adding a further reason for a diversified energy mix rather than focusing on specific low carbon emitting technologies. Focusing on flexibility and considering different technological options for various scenarios are important. This includes option clauses in contracts with suppliers that enable the power companies to withdraw from projected power plant investments (Hoffmann, 2007). Especially in the case of carbon capture and storage, the companies also think in options and try to maximize flexibility in the light of uncertainties. This refers to the staged character of R&D investments that depend on public and political opinion about the technology as well as to developing particularly flexible CCS technologies such as CO2 washers (Hoffmann, 2007).
In conclusion, increased risks associated with uncertainties in the EU ETS have affected risk management processes in the electricity industry and this clearly underlines the necessary measures regarding the increased necessity to diversify risks in order to incorporate flexibility in investment planning process.
Short allocation period: Retro-fit vs. long term investments
The economic lifetime of an investment in power capacity typically ranges from 20-40 years (OECD NEA/IEA, 1998) and the investments in power plants are capital intensive and hence are associated with larger amount of risk. Hence, the short allocation period of EU ETS does not help encouraging long term investment in energy sector, as the life spans of power plants are much longer than the trading periods. The short allocation period often delays or even postpones an investment as the policy goals are reviewed after completion of each trading phase thus the planning for investment considering certain set of regulations also requires a revision.
The policy uncertainty and associated market risks for carbon pricing over the long term de-motivates the investors to commit large sum of capital for a project in which case they may choose the option to wait or new entrants may choose not to invest at all. However, investors may also have an option to stage the investment: instead of committing to a ‘‘lump'' project, the investor may implement several smaller projects sequentially. It has been argued that a higher uncertainty, e.g. due to emissions trading, may nevertheless cause the investor to prefer the smaller projects to the lump project (e.g. Dixit and Pindyck, 1994, pp. 51-54). This also favors flexible investment alternatives with short-lead times and low capital requirements (e.g., Söderholm, 1999). However, this typically results in higher unit costs, which eventually get transferred to the consumers.
Investments in low carbon technologies are capital intensive and decision process is complex given the uncertainties about the future pricings of the EU Electricity markets. For a time horizon of year 2050, there are a number of factors such as uncertainties in carbon prices, lack of long term policies, increased risk to investors, effects of international climate control policies, and government regulatory policies, which will have significant impact on investments decisions in such technologies. In light of above said variability, the present study explored long term investments prospects in the EU power generation sector within the EU ETS regime. The study carried out an intensive literature search about the work of previous researchers in the similar filed. Key issues were identified and the arguments were built assessing the impact of each key issue on generation investments over long term. In context of increased uncertainty and high volatility in carbon prices, it was seen that the conventional project appraisal approaches such as discounted cash flow models were not able to evaluate the future economics of the project and real options methodology has been increasingly used for such applications. The benefit of using it is the ability to carry out economic evaluation of the option to wait in the project appraisal. However, the owing to its sensitivity to uncertainty, the real options method combined with risk averse attitude of investors may retard the rate of investment in electricity generation in the EU. On one hand, it may dampen the investor sentiments for investments however on the other hand it may provide with the choices for investments for new entrants. Lack of clarity in policies for long term in EU ETS also adds to the investment risks to the investors. The short allocation periods of allocation also result in accurate evaluation of future economics of the projects. It is observed that investors even prefer to wait until the policy guidance becomes clear before taking any major investment decision. This might have a misbalancing on the electricity generation capacity needed to cater the future expected demands. In addition, it is also observed that the technology choice for investors is also influenced by national policies of a country and there exists a delay if the national policies are not well synchronized with the EU ETS and the delay in permit process may affect the investment timing. However, the uncertainty in investment may sometimes also result in the investors staging the project owing to their short amortization periods, which also reduces the exposure to long term uncertainties. However, in this case, the marginal costs of production would be higher and the cost will be transferred to the customers. The generation companies also find it more compelling to generate an optimal energy mix portfolio rather than focusing on specific low carbon emitting technology. This is a nice approach for risk diversification but it can significantly impact the development rate of renewables, however it would also depend on many other factors. To conclude, in a liberalized competitive market, the investors are in general exposed to increased investment risks compared to regulated monopoly situation. The EU ETS has been effective in generating response to low carbon emitting technologies, however due to still being in developmental stage, it has considerable amount of uncertainties, which discourages the investors to make large commitments to power generation projects in the long term. The policy makers need to address the issue seriously as it is not only the investments in low carbon emitting technologies, but also the required capacity addition for future expected demands. Needless to say, the ‘business as usual' tendency owing to delays in investment might as well result in missing the CO2 emission reduction targets for the long term.
Cite This Dissertation
To export a reference to this article please select a referencing stye below: