Evaluating the power investment options with uncertainty in climate policy

This paper uses a real options approach (ROA) for analysing the effects of government climate policy uncertainty on private investors’ decision-making in the power sector. It presents an analysis undertaken by the International Energy Agency (IEA) that implements ROA within a dynamic programming approach for technology investment choice. Case studies for gas, coal and nuclear power investment are undertaken with the model. Illustrative results from the model indicate four broad conclusions: i) climate change policy risks can become large if there is only a short time between a future climate policy event such as post-2012 and the time when the investment decision is being made; ii) the way in which CO₂ and fuel price variations feed through to electricity price variations is an important determinant of the overall investment risk that companies will face; iii) investment risks vary according to the technology being considered, with nuclear power appearing to be particularly exposed to fuel and CO₂ price risks under various assumptions; and iv) the government will be able to reduce investors' risks by implementing long-term (say 10 years) rather than short-term (say 5 years) climate change policy frameworks. Contributions of this study include: (1) having created a step function with stochastic volume of jump at a particular time to simulate carbon price shock under a particular climate policy event; (2) quantifying the implicit risk premium of carbon price uncertainty to investors in new capacity; (3) evaluating carbon price risk alongside energy price risk in investment decision-making; and (4) demonstrating ROA to be a useful tool to quantify the impacts of climate change policy uncertainty on power investment.     

Evaluation of new and renewable energy technologies in Korea using real options

For several years recently, the price of oil has fluctuated due to the weak US dollar and financial risks. In particular, the WTI crude oil price reached $147 per barrel in July of 2008, which is the highest price thus far. An awareness of an impending crisis and concern over climate change are driving an increase in R&D for alternative energy sources instead of fossil‐based energy. However, the researches based on traditional method show negative options about the economic value of new and renewable energy. This paper evaluates the value of new and renewable energy through a real option method which considers the uncertainty associated with fossil energy and the uncertainty of the success of R&D. The evaluating model assumes that the fossil energy price follows a geometric mean reverting process and that the probability of success with R&D on renewal forms of energy follows a binomial probability model. The model considers four options: the option to continue R&D, the option to delay R&D, the option to deploy R&D, and the option to abandon R&D. Finally, the value of Korean R&D on renewal forms of energy is analyzed by the model. Copyright © 2012 John Wiley & Sons, Ltd.     

The UK surface passenger transport sector : Energy consumption and policy options for conservation

The paper describes a study of the UK surface passenger transport sector whose main objectives were to investigate the pattern of present and future energy consumption and to provide a preliminary options to reduce energy use. Analysis shows the dominance of travel by private car in energy consumption patterns. Forecasts of energy consumption are then presented for four alternative future as a basis for evaluating long-term energy-saving options. This evaluation suggests that the most attractive policy relates to changes in private vehicle technology. However, there is considerable uncertainty about the outcome of this and other policy options.     

Decision frameworks and the investment in R&D

In this paper we provide an overview of decision frameworks aimed at crafting an energy technology Research & Development portfolio, based on the results of three large expert elicitation studies and a large scale energy-economic model. We introduce importance sampling as a technique for integrating elicitation data and large IAMs into decision making under uncertainty models. We show that it is important to include both parts of this equation – the prospects for technological advancement and the interactions of the technologies in and with the economy. We find that investment in energy technology R&D is important even in the absence of climate policy. We illustrate the value of considering dynamic two-stage sequential decision models under uncertainty for identifying alternatives with option value. Finally, we consider two frameworks that incorporate ambiguity aversion. We suggest that these results may be best used to guide future research aimed at improving the set of elicitation data.     

Oil and natural gas prices and greenhouse gas emission mitigation

The hikes in hydrocarbon prices during the last years have lead to concern about investment choices in the energy system and uncertainty about the costs for mitigation of greenhouse gas emissions. On the one hand, high prices of oil and natural gas increase the use of coal; on the other hand, the cost difference between fossil-based energy and non-carbon energy options decreases. We use the global energy model TIMER to explore the energy system impacts of exogenously forced low, medium and high hydrocarbon price scenarios, with and without climate policy. We find that without climate policy high hydrocarbon prices drive electricity production from natural gas to coal. In the transport sector, high hydrocarbon prices lead to the introduction of alternative fuels, especially biofuels and coal-based hydrogen. This leads to increased emissions of CO₂. With climate policy, high hydrocarbon prices cause a shift in electricity production from a dominant position of natural gas with carbon capture and sequestration (CCS) to coal-with-CCS, nuclear and wind. In the transport sector, the introduction of hydrogen opens up the possibility of CCS, leading to a higher mitigation potential at the same costs. In a more dynamic simulation of carbon price and oil price interaction the effects might be dampened somewhat.     

Assessing the effects of CO2 price caps on electricity investments—A real options analysis

This paper uses real options modeling to assess the impact of different climate change policy instruments on investment, profits and cumulative emissions in the electricity sector. Even though CO₂ price caps or “safety valves” have been suggested as methods to limit uncertainty emanating from fluctuating prices of CO₂ permits that would hurt the industry's profit and thereby also energy security, our analysis shows that price caps set at a too low level are detrimental to the adoption of e.g. modern biomass-fired capacity as a replacement for existing coal-fired power plants. We therefore conduct a series of experiments with different policy scenarios to analyze under which regime emissions are most effectively reduced. With respect to CO₂ price uncertainty, it turns out that even for moderately rising CO₂ prices, fluctuations frequently lead to investment into carbon capture and storage (CCS), while investment is often not triggered in the face of deterministic CO₂ prices.     

Uncertainty modeling of CCS investment strategy in China’s power sector

The increasing pressure resulting from the need for CO₂ mitigation is in conflict with the predominance of coal in China’s energy structure. A possible solution to this tension between climate change and fossil fuel consumption fact could be the introduction of the carbon capture and storage (CCS) technology. However, high cost and other problems give rise to great uncertainty in R&D and popularization of carbon capture technology. This paper presents a real options model incorporating policy uncertainty described by carbon price scenarios (including stochasticity), allowing for possible technological change. This model is further used to determine the best strategy for investing in CCS technology in an uncertain environment in China and the effect of climate policy on the decision-making process of investment into carbon-saving technologies.     

Impact of climate policy uncertainty on the adoption of electricity generating technologies

This paper presents a real options model where multiple options are evaluated simultaneously so that the effect of the individual options on each other is accounted for. We apply this model to the electricity sector, where we analyze three typical technologies based on fossil fuel, fossil fuel with carbon capture and renewable energy, respectively. In this way, we can analyze the transition from CO₂-intensive to CO₂-neutral electricity production in the face of rising and uncertain CO₂ prices. In addition, such a modelling approach enables us to estimate precisely the expected value of (perfect) information, i.e. the willingness of investors and producers to pay for information about the correct CO₂ price path. As can be expected, the expected value of information rises with increasing CO₂ price uncertainty. In addition, the larger the price uncertainty, the larger are the cumulative CO₂ emissions over the coming century. The reason for this is that the transition to less CO₂-intensive technologies is increasingly postponed with rising CO₂ price uncertainty. By testing different price processes (geometric Brownian motion versus jump processes with different jump frequencies), we can also make useful recommendations concerning the importance of policy predictability. We find that it is better to have climate change policies that are stable over a certain length of time and change abruptly than less abrupt but more frequently changing policies. Less frequent fluctuations reduce the expected value of information and result in smaller cumulative CO₂ emissions.     

Renewable energy policy evaluation using real option model — The case of Taiwan

This study presents a policy benefit evaluation model that integrates cost efficiency curve information on renewable power generation technologies into real options analysis (ROA) methods. The proposed model evaluates quantitatively the policy value provided by developing renewable energy (RE) in the face of uncertain fossil fuel prices and RE policy-related factors. The economic intuition underlying the policy-making process is elucidated, while empirical analysis illustrates the option value embedded in the current development policy in Taiwan for wind power. In addition to revealing the benefits that RE development provides when considering real options, analytical results indicate that ROA is a highly effective means of quantifying how policy planning uncertainty including managerial flexibility influences RE development. In addition to assessing the policy value of current RE development policy, this study also compares policy values in terms of internalized external costs and varying feed-in tariff (FIT). Simulation results demonstrate that the RE development policy with internalized CO₂ emission costs is appropriate policy planning from sustainability point of view. Furthermore, relationship between varying FIT and policy values can be shown quantitatively and appropriate FIT level could be determined accordingly.     

Electricity supply industry modelling for multiple objectives under demand growth uncertainty

Appropriate energy–environment–economic (E3) modelling provides key information for policy makers in the electricity supply industry (ESI) faced with navigating a sustainable development path. Key challenges include engaging with stakeholder values and preferences, and exploring trade-offs between competing objectives in the face of underlying uncertainty. As a case study we represent the South African ESI using a partial equilibrium E3 modelling approach, and extend the approach to include multiple objectives under selected future uncertainties. This extension is achieved by assigning cost penalties to non-cost attributes to force the model's least-cost objective function to better satisfy non-cost criteria. This paper incorporates aspects of flexibility to demand growth uncertainty into each future expansion alternative by introducing stochastic programming with recourse into the model. Technology lead times are taken into account by the inclusion of a decision node along the time horizon where aspects of real options theory are considered within the planning process. Hedging in the recourse programming is automatically translated from being purely financial, to include the other attributes that the cost penalties represent. From a retrospective analysis of the cost penalties, the correct market signals, can be derived to meet policy goal, with due regard to demand uncertainty.     

Investment under market and climate policy uncertainty

Climate change is considered as one of the major systematic risks for global society in the 21st century. Yet, serious efforts to slow the accumulation of emissions are still in their primordial stage and policy makers fail to give proper long-term signals to emitters. These days, investors do not only face uncertainty from volatile prices in the traditional markets, but also from the less conceivable uncertainty of stricter climate change policy. This paper investigates the impact of learning about the commitment of government to a climate policy regime in a real options framework. Two types of uncertainty are distinguished: market-driven price volatility around a mean price and bifurcating price trajectories mimicking uncertainty about changing policy regimes. One of the findings is that the producer facing market uncertainty about CO₂ prices invests into carbon-saving technology earlier than if the actual price path had been known on beforehand. This is not a typical real options outcome, but the result of optimizing under imperfect information, which leads to decisions that are different from the optimal strategies under full information. On the other hand, policy uncertainty induces the producer to wait and see whether the government will further commit to climate policy. This waiting is a real options effect. In other words, if learning about government commitment is more valuable than investing into mitigation technologies immediately, the option value exceeds the value of the technology and investment will be postponed. This might lead to supply shortages and limited diffusion of less carbon-intensive technology.     

Investment risks under uncertain climate change policy

This paper describes results from a model of decision-making under uncertainty using a real options methodology, developed by the International Energy Agency (IEA). The model represents investment decisions in power generation from the perspective of a private company. The investments are subject to uncertain future climate policy, which is treated as an external risk factor over which the company has no control. The aims of this paper are to (i) quantify these regulatory risks in order to improve understanding of how policy uncertainty may affect investment behaviour by private companies and (ii) illustrate the effectiveness of the real options approach as a policy analysis tool. The study analysed firms’ investment options of coal- and gas-fired power plants and carbon capture and storage (CCS) technologies. Policy uncertainty is represented as an exogenous event that creates uncertainty in the carbon price. Our findings indicate that climate policy uncertainty creates a risk premium for power generation investments. In the case of gas- and coal-fired power generation, the risk premium would lead to an increase in electricity prices of 5–10% in order to stimulate investment. In the case of CCS, the risk premium would increase the carbon price required to stimulate investment by 16–37% compared to a situation of perfect certainty. The option to retrofit CCS acts as a hedge against high future carbon prices, and could accelerate investment in coal plant. This paper concludes that to minimise investment risks in low carbon technologies, policy-makers should aim to provide some long-term regulatory certainty.     

A real options model for renewable energy investment with application to solar photovoltaic power generation in China

This paper proposes a real options model for evaluating renewable energy investment by considering uncertain factors such as CO₂ price, non-renewable energy cost, investment cost and market price of electricity. A phase-out mechanism is built into the model to reflect the long-term changes of subsidy policy. We apply the proposed model to empirically evaluate the investment value and optimal timing for solar photovoltaic power generation in China. Our empirical results show that the current investment environment in China may not be able to attract immediate investment, while the development of carbon market helps advance the optimal investment time. A sensitivity analysis is conducted to investigate the dynamics of investment value and optimal timing under the changes of unit generating capacity, subsidy level, market price of electricity, CO₂ price and investment cost. It is found that the high investment cost and the volatility of electricity and CO₂ prices, are not conducive to attract immediate investment. Instead, increasing the level of subsidy, promoting technological progress and maintaining the stability of market are useful to stimulate investment.     

Assessment of transport fuel taxation strategies through integration of road transport in an energy system model—the case of Sweden

Road transport is responsible for a large and growing share of CO₂ emissions in most countries. A number of new fuel‐efficient vehicle technologies and renewable transport fuels are possible alternatives to conventional options but their deployment relies strongly on different policy measures. Even though a future higher use of transport biofuels and electric vehicles is likely to increase the interaction between the transportation sector and the stationary energy system (heat, power, etc.), these systems are often analysed separately. In this study, a transport module is developed and integrated into the MARKAL_Nordic energy system model. The transport module describes a range of vehicle technologies and fuel options as well as different paths for conversion of primary energy resources into transport fuels. The integrated model is utilized to analyse the impact of transport fuel tax designs on future cost‐effective fuel and technology choices in the Swedish transportation sector, as well as the consequences of these choices on system costs and CO₂ emissions. The model, which is driven by cost‐minimization, is run to 2050 with various assumptions regarding transport fuel tax levels and tax schemes. The results stress the importance of fuel taxes to accelerate the introduction of fuel‐efficient vehicle technologies such as hybrids and plug‐in hybrids. Tax exemptions can make biofuels an economically favourable choice for vehicle users. However, due to limitations in biomass supply, a too strong policy‐focus on transport biofuels can lead to high system costs in relation to the CO₂ abatement achieved. The modelling performed indicates that the effects caused by linkages between the transportation sector and the stationary energy system can be significant and integrated approaches are thus highly relevant. Copyright © 2011 John Wiley & Sons, Ltd.     

Uncertainty—an argument for more stringent energy conservation

Most energy conservation analyses assume various future paths for energy prices and other parameters and then proceed to calculate the optimal value of conservation investment under the specified assumptions. Sensitivity analysis is used to examine the amount which the calculations change as parameters are varied. In fact, the future is not known with certainty, and it is desirable to include uncertainty explicitly in the analysis. This paper approaches the uncertainty problem in a simple way but one which provides considerable insight. We assume that future energy price growth is characterized by a probability distribution, and calculate the optimal investment strategy for conservation investment given this uncertainty. The results are striking. Introduction of uncertainty leads to the conclusion that more conservation investment is desirable than would be made without uncertainty. The conclusion stems, in essence, from the observation that the upside risk to the consumer resulting from unexpectedly high energy prices is larger than the downside savings which would result from unexpectedly low energy prices. The policy conclusion is straightforward: All else being equal, if you think that future energy prices are uncertain, it pays off (for both the individual and the nation) to err on the side of “too much” rather than “too little” conservation.One set of results is expressed in terms of an effective growth rate of energy prices. An example is an electrically heated house located in Washington, D.C. If the most likely growth rate of energy prices is 5% per year, but there is a normally distributed uncertainty about this price growth of 5%/yr (i.e. it is equally likely that prices will grow by 10%/yr and by 0%/yr), then one should calculate the conservation investment as if the price growth rate is 6.8%/yr.A second price assumption used is a price jump at some time from an initial price to a new, higher, final price. Uncertainty is introduced in the time when the price jump occurs. The inclusion of uncertainty leads to the conclusion that the effective time of the price jump is sooner than the most likely time. This result implies that a higher investment in conservation is warranted than would be optimal absent uncertainty.Our model is simple and maybe applied directly by individual decision makers. From a societal point of view, there are many additional arguments that suggest that uncertainty leads to changes in optimal strategies. The essential results cannot be captured simply by carrying out sensitivity analyses on deterministic models. Changes in model structure are required. We believe the inclusion of uncertainty in energy modeling is an important area, and one which can lead to fruitful results for policy analysis. We also make a prediction about energy conservation investment in buildings: Total energy use is predicted to fall exponentially with total conservation investment.     

Renewable electricity in Sweden: an analysis of policy and regulations

This study aims to analyse the developments in renewable energy policy making in Sweden. It assesses the energy policy context, changes in the choice of policy instruments, and provides explanations behind policy successes and failures. Swedish renewable energy policy has been developing in a context of uncertainty around nuclear issues. While there has been made a political decision to replace nuclear power with renewables, there is a lack of consensus about the pace of phasing out nuclear power due to perceived negative impacts on industrial competitiveness. Such uncertainty had an effect in the formulation of renewable energy policy. Biomass and wind power are the main options for renewable electricity production. Throughout 1990s, the combined effect of different policy instruments has stimulated the growth of these two renewable sources. Yet, both biomass and wind power are still a minor contributor in the total electricity generation. Lack of strong government commitment due to uncertainty around nuclear issues is a crucial factor. Short-term subsidies have been preferred rather than open-ended subsidy mechanisms, causing intervals without subsidies and interruption to development. Other factors are such as lack of incentives from the major electricity companies and administrative obstacles. The taxation system has been successful in fostering an expansion of biomass for heating but hindered a similar development in the electricity sector. The quota system adopted in 2003 is expected to create high demand on biomass but does not favour wind power. The renewable energy aims are unlikely to be changed. Yet, the future development of renewable energy policies especially for high-cost technologies will again depend strongly on nuclear policies, which are still unstable and might affect the pace of renewable energy development.     

A model-based analysis of biomethane production in the Netherlands and the effectiveness of the subsidization policy under uncertainty

Biomethane is a renewable alternative to natural gas. It has the potential to increase the sustainability of the energy system and to help deal with supply problems. However, several factors make the future of biomethane production complex and uncertain, such as resource availability, demand, capacity installation, profitability and the competition between the biomethane and electricity sectors for sharing the available biogas and biomass resources. In this research, we study the dynamics of the Dutch biomethane production and analyze the effects of subsidization policy with a system dynamics model. The policy is tested under uncertainty with respect to three conflicting objectives, namely maximizing production and emission reduction, and minimizing costs. According to the results, the subsidization is crucial to develop biomethane production, and the performance of the policy is enhanced in terms of robustness and of meeting all three objectives satisfactorily when the policy is implemented for a long time, with relatively low subsidy prices. Besides, the subsidization policy is found to be most vulnerable to the producers’ uncertain investment response to profitability. In future research, different policy options such as subsidizing other biomass-based renewable energy options and policies affecting the biomethane demand can be tested.     

Economy and CO2 emissions trade-off: A systematic approach for optimizing investments in process integration measures under uncertainty

In this paper we present a systematic approach for taking into account the resulting CO₂ emissions reductions from investments in process integration measures in industry when optimizing those investments under economic uncertainty. The fact that many of the uncertainties affecting investment decisions are related to future CO₂ emissions targets and policies implies that a method for optimizing not only economic criteria, but also greenhouse gas reductions, will provide better information to base the decisions on, and possibly also result in a more robust solution. In the proposed approach we apply a model for optimization of decisions on energy efficiency investments under uncertainty and regard the decision problem as a multiobjective programming problem. The method is applied to a case of energy efficiency investments at a chemical pulp mill. The case study is used to illustrate that the proposed method provides a good framework for decision-making about energy efficiency measures when considerations regarding greenhouse gas reductions influence the decisions. We show that by setting up the problem as a multiobjective programming model and at the same time incorporating uncertainties, the trade-off between economic and environmental criteria is clearly illustrated.     

Decarbonization of the U.S. electricity sector: Are state energy policy portfolios the solution?

State governments have taken the lead on U.S. energy and climate policy. It is not yet clear, however, whether state energy policy portfolios can generate results in a similar magnitude or manner to their presumed carbon mitigation potential. This article seeks to address this lack of policy evidence and contribute empirical insights on the carbon mitigation effects of state energy portfolios within the U.S. electricity sector. Using a dynamic, long-term electricity dispatch model with U.S. power plant, utility, and transmission and distribution data between 2010 and 2030, this analysis builds a series of state-level policy portfolio scenarios and performs a comparative scenario analysis. Results reveal that state policy portfolios have modest to minimal carbon mitigation effects in the long run if surrounding states do not adopt similar portfolios as well. The difference in decarbonization potential between isolated state policies and larger, more coordinated policy efforts is due in large part to carbon leakage, which is the export of carbon intensive fossil fuel-based electricity across state lines. Results also confirm that a carbon price of $50/metric ton CO₂e can generate substantial carbon savings. Although both policy options – an energy policy portfolio or a carbon price – are effective at reducing carbon emissions in the present analysis, neither is as effective alone as when the two strategies are combined.