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.     

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.     

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.     

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.     

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 evaluation model for the diffusion prospects of new renewable power generation technologies

This study presents a policy planning model that integrates learning curve information on renewable power generation technologies into a dynamic programming formulation featuring real options analysis. The model recursively evaluates a set of investment alternatives on a year-by-year basis, thereby taking into account that the flexibility to delay an irreversible investment expenditure can profoundly affect the diffusion prospects of renewable power generation technologies. Price uncertainty is introduced through stochastic processes for the average wholesale price of electricity and for input fuel prices. Demand for electricity is assumed to be increasingly price-sensitive, as the electricity market deregulation proceeds, reflecting new options of consumers to react to electricity price changes (such as time-of-use pricing, unbundled electricity services, and choice of supplier). The empirical analysis is based on data for the Turkish electricity supply industry. Apart from general implications for policy-making, it provides some interesting insights about the impact of uncertainty and technical change on the diffusion of various emerging renewable energy technologies.     

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.     

The asymmetric response of gasoline prices to oil price shocks and policy uncertainty

This study shows that the effect of oil price shocks on the real price of gasoline is interrelated with economic policy uncertainty. Economic policy shocks are linked with increased real price of gasoline and reduced consumption of gasoline. There is evidence that the fluctuation of both real gasoline prices and of gasoline consumption is associated with uncertainty of tax legislation expiration expectation as well as other components of economic policy uncertainty. Positive shocks to economic policy uncertainty have relatively larger effects on gasoline prices than do negative shocks to economic policy uncertainty. Economic policy uncertainty responds asymmetrically to increases and decreases in real oil price. Shocks to economic policy uncertainty account for 16.1% of variation in real gasoline prices and for 4.9% of variation in gasoline consumption in the long-run.     

Inducing low-carbon investment in the electric power industry through a price floor for emissions trading

Uncertainty about long-term climate policy is a major driving force in the evolution of the carbon market price. Since this price enters the investment decision process of regulated firms, this uncertainty increases the cost of capital for investors and might deter investments into new technologies at the company level. We apply a real options-based approach to assess the impact of climate change policy in the form of a constant or growing price floor on investment decisions of a single firm in a competitive environment. This firm has the opportunity to switch from a high-carbon “dirty” technology to a low-carbon “clean” technology. Using Monte Carlo simulation and dynamic programming techniques for real data, we determine the optimal CO₂ price floor level and growth rate in order to induce investments into the low-carbon technology. We find that a carbon price floor can be used to induce earlier low-carbon technology investment and show this result to be robust to a large variety of input parameter settings.     

The potential impacts of climate-change policy on freshwater use in thermoelectric power generation

Climate change policy involving a price on carbon would change the mix of power plants and the amount of water they withdraw and consume to generate electricity. We analyze what these changes could entail for electricity generation in the United States under four climate policy scenarios that involve different costs for emitting CO₂ and different technology options for reducing emissions out to the year 2030. The potential impacts of the scenarios on the U.S. electric system are modeled using a modified version of the U.S. National Energy Modeling System and water-use factors for thermoelectric power plants derived from electric utility data compiled by the U.S. Energy Information Administration. Under all the climate-policy scenarios, freshwater withdrawals decline 2–14% relative to a business-as-usual (BAU) scenario of no U.S. climate policy. Furthermore, water use decreases as the price on CO₂ under the climate policies increases. At relatively high carbon prices (>$50/tonne CO₂), however, retrofitting coal plants to capture CO₂ increases freshwater consumption compared to BAU in 2030. Our analysis suggests that climate policies and a carbon price will reduce both electricity generation and freshwater withdrawals compared to BAU unless a substantial number of coal plants are retrofitted to capture CO₂.     

Primary energy demand in Japan: an empirical analysis of long-term trends and future CO2 emissions

This paper examines the long-run relationship between energy demand, GNP and the real energy price in Japan using data covering 1887–2001. It is found that, if an Underlying Energy Demand Trend is appropriately incorporated, the resulting econometric model produces a long-run income elasticity of about unity and a long-run price elasticity of about–0.2. The estimated model is utilised to forecast energy consumption and CO₂ emissions up to 2012. It is shown that given current economic conditions and policies there is considerable uncertainty about whether Japan will be able to meet its Kyoto target by reducing CO₂ emissions in 2008–2012 to the 1990 level. It is shown that this uncertainty depends on the strength of the economy and leaves the Japanese government with a difficult policy dilemma. If there is a resurgence in growth to something near the annual average growth rate since the early 1980s a considerable effort will be required in order to meet its Kyoto target; requiring not only using the Kyoto Mechanisms, but also additional tougher domestic policies and measures such as emissions capping, R&D incentives, and education for energy conservation in addition to a pricing and tax policy.     

Fuel cost uncertainty,capacity investment and price in a competitive electricity market

This paper studies the effect of natural-gas fuel cost uncertainty on capacity investment and price in a competitive electricity market. Our model has a two-stage decision process. In the first stage, an independent power producer (IPP) builds its optimal capacity, conditional on its perceived uncertainties in fuel cost and electricity demand. In the second stage, equilibrium prices and quantities are determined by IPPs competing in a Cournot market. Under the empirically reasonable assumption that per MWh fuel costs are log-normally distributed, we find that a profit-maximizing IPP increases its capacity in response to rising fuel cost volatility. Consequently, the expected profit of the IPP and expected consumer surplus increase with volatility, rejecting the hypothesis that rising fuel cost uncertainty tends to adversely affect producers and consumers. Expected consumer surplus further increases if the IPP hedges the fuel cost risk. However, the IPP's optimal strategy is not to do so. The policy implication of these results is that the government should not intervene to reduce the price volatility of a well-functioning spot market for natural gas, chiefly because such intervention can have the unintended consequence of discouraging generation investment, raising electricity prices, and harming consumers.     

Electric sector capacity planning under uncertainty: Climate policy and natural gas in the US

This research investigates the dynamics of capacity planning and dispatch in the US electric power sector under a range of technological, economic, and policy-related uncertainties. Using a two-stage stochastic programming approach, model results suggest that the two most critical risks in the near-term planning process of the uncertainties considered here are natural gas prices and the stringency of climate policy. Stochastic strategies indicate that some near-term hedging from lower-cost wind and nuclear may occur but robustly demonstrate that delaying investment and waiting for more information can be optimal to avoid stranding capital-intensive assets. Hedging strategies protect against downside losses while retaining the option value of deferring irreversible commitments until more information is available about potentially lucrative market opportunities. These results are explained in terms of the optionality of investments in the electric power sector, leading to more general insights about uncertainty, learning, and irreversibility. The stochastic solution is especially valuable if decision-makers do not sufficiently account for the potential of climate constraints in future decades or if fuel price projections are outdated.     

Investors’ reaction to the government credibility problem: A real option analysis of emission permit policy risk

In relation to creating a CO₂ emission permit market, there are two types of climate change policy risks: (1) It is uncertain whether and when a cap-and-trade system will be implemented; and (2) once a policy is in place, there may be government credibility issues. This paper examines the effect of these policy risks on real option decisions of electric power plant investment. To model both an investment decision and generation flexibility, this study evaluates an exotic compound American option on multiple strips of European spread options through the implementation of least squares Monte Carlo simulation. Government credibility risk leads to more investment in “less green” resources and induces additional cash flow variation, which increases the average time to investment (value of waiting). However, in an extreme case, government credibility can actually hasten investment because the risk may be more favorable to electric power companies. Furthermore, if emission trading is planned to be implemented in the future (e.g., 2020), and the market believes that the probability of successful implementation is low, firms will build a “less green” plant early to benefit from the period before the green rule is applied.     

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.     

Innovation subsidies versus consumer subsidies: A real options analysis of solar energy

Given the interest in the commercialization of affordable, clean energy technologies, we examine the prospects of solar photovoltaics (PV). We consider the question of how to transition to a meaningful percentage of solar energy in a sustainable manner and which policies are most effective in accelerating adoption. This paper develops a stochastic dynamic model of the adoption of solar PV in the residential and commercial sector under two sources of uncertainty – the price of electricity and cost of solar. The analytic results suggest that a high rate of innovation may delay adoption of a new technology if the consumer has rational price expectations. We simulate the model across alternative rates technological change, electricity prices, subsidies and carbon taxes. It is shown that there will be a displacement of incumbent technologies and a widespread shift towards solar PV in under 30 years – and that this can occur without consumer incentives and carbon pricing. We show that these policies have a modest impact in accelerating adoption, and that they may not be an effective part of climate policy. Instead, results demonstrate that further technological change is the crucial determinant and main driver of adoption. Further, results indicate that subsidies and taxes become increasingly ineffective with higher rates of technological change.     

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.     

Technological uncertainty and cost effectiveness of CO2 emission reduction

This paper studies implications of uncertainty about CO₂ backstop technology for cost effectiveness of CO₂ emission reduction policy. For this purpose, we develop a dynamic general equilibrium model that captures empirical links between CO₂ emissions associated with energy use, the rate and direction of technical change and the economy. We specify CO₂ capture and storage (CCS) as the backstop technology whose arrival is anticipated or not. We find a negative value of information in that the discounted welfare loss associated with the emission reduction is lower if CCS is not anticipated. CO₂ shadow prices are then relatively high in the years before the CCS has arrived. By not simply waiting with the emission reduction until CCS has arrived, one relies more on economy wide technical change and its welfare enhancing technology externalities in turn allowing for a higher steady state. We believe that policy makers should thus be prudent in designing CO₂ emission reduction policy and be careful not to let polluters become complacent by postponing some of their emission reduction efforts awaiting the silver bullet technology on the horizon.     

Policy uncertainties: What investment choice for solar panel producers?

Solar power has achieved great development in the last decade, and it should continue to play a central role in the face of climate change and sustainable development challenges. This paper builds a real options model that provides a microeconomic analytical framework with the Least Squares Monte Carlo (LSM) method to assess the investment choices of a typical solar panel producer in China facing trade and domestic supply- and demand-side policy uncertainties. It builds a baseline scenario and three policy scenarios with decreasing anti-dumping and countervailing charges, constant feed-in tariff (FIT) level and reduced investment cost. A typical producer will have to make an investment decision on building a new production line in five years based on a decision impact analysis within 20 years. The result shows an immediate investment decision for all scenarios. The producer will have higher return from investment in building a solar power plant with a constant FIT. Export is the optimal choice in other scenarios where investment return is lower. After sensitivity analysis, the paper concludes and can be used as a toolkit for solar panel producers and a reference for policy makers to evaluate the impact of policy uncertainties.     

Lifecycle analysis of different urban transport options for Bangladesh

Once again, sustained high oil prices are forcing policy makers in oil importing countries to consider alternatives to oil products as transportation fuels. Unlike in the past, advancements in technology, relative success of some experiments and increased familiarity among and acceptance by the public of some alternatives indicate a higher likelihood of success. In particular, natural gas offers a couple of the best options as compressed natural gas (CNG) and chemical conversion of natural gas into diesel (gas-to-liquids, GTL). These options are likely to be most attractive in countries that have cheap access to natural gas. We compare lifetime costs of several individual transportation options for Bangladesh, an oil importer with natural gas reserves. The results are then used to inform the natural gas policy debate in the country. Assuming a natural gas price of $1.5 per million Btu, both the CNG and GTL options are competitive with conventional gasoline/diesel cars if the oil price stays higher than $35–40 per barrel. If natural gas price increases after new upstream developments, CNG becomes less attractive while GTL remains competitive up to $2.5 if capital costs of GTL facilities decline as expected. Under a government policy push (lower discounting), the breakeven price of oil falls to $30–35 per barrel.