Uncertain long-run emissions targets,CO2 price and global energy transition: A general equilibrium approach

The persistent uncertainty about mid-century CO₂ emissions targets is likely to affect not only the technological choices that energy-producing firms will make in the future but also their current investment decisions. We illustrate this effect on CO₂ price and global energy transition within a MERGE-type general-equilibrium model framework, by considering simple stochastic CO₂ policy scenarios. In these scenarios, economic agents know that credible long-run CO₂ emissions targets will be set in 2020, with two possible outcomes: either a “hard cap” or a “soft cap”. Each scenario is characterized by the relative probabilities of both possible caps. We derive consistent stochastic trajectories—with two branches after 2020—for prices and quantities of energy commodities and CO₂ emissions permits. The impact of uncertain long-run CO₂ emissions targets on prices and technological trajectories is discussed. In addition, a simple marginal approach allows us to analyze the Hotelling rule with risk premia observed for certain scenarios.     

Economic evaluation of renewable energy systems under varying scenarios and its implications to Korea’s renewable energy plan

This paper studies economics of renewable energy systems with consideration of future prospects on costs and uncertain external conditions that may affect competitiveness in the power plant market. The concept of learning curve is adopted to compute estimates on the costs of installing and operating renewable energy systems in the future; fuel costs and carbon price are modeled as scenario-dependent variables to analyze their impact on total costs under different scenarios. The proposed approach allows evaluation and comparison of total costs necessary in implementing renewable energy plans under varying technological, and/or economical conditions that face uncertainty at present. Moreover, analyzing the evaluation results further with techniques like sensitivity analysis can identify factors central to reducing the total costs. As an illustrative case-study, the Korean government’s renewable energy plan has been evaluated accordingly, under three different scenarios defined by International Energy Agency (IEA). The evaluation results indicate minor changes in total costs of achieving the plan among three scenarios, mainly due to counterbalancing between the price of fossil fuels and carbon price. Further analyses revealed factors central to lowering the total costs necessary in implementing the plan—hybridization between renewable energy systems, reduction of biomass production costs via technological innovation, increasing learning rates by focusing on R&D and international cooperation.     

Mitigating wind exposure with zero-cost collar insurance

Renewable energy generation worldwide has relied increasingly on wind farms where wind energy is transformed into electricity. On the other hand, electricity prices are uncertain and wind speeds are highly variable, which exposes the producer to risks. Typically wind power producers enter into long term fixed price contracts in order to hedge against energy price risk, but these contracts expose the wind farm to energy volume risk, as they require delivery of the full amount of energy contracted, even if energy production falls short due to low wind speeds. To mitigate this risk, wind producers can purchase insurance. This article proposes a zero-cost collar insurance and develop a stochastic model to determine the feasible range of wind strikes for both the wind farm and the insurer. The results indicate there is a set of possible strike combinations that meets the objectives of both parties.     

The forest products industry at an energy/climate crossroads

Transformational energy and climate policies are being debated worldwide that could have significant impact upon the future of the forest products industry. Because woody biomass can produce alternative transportation fuels, low-carbon electricity, and numerous other “green” products in addition to traditional paper and lumber commodities, the future use of forest resources is highly uncertain. Using the National Energy Modeling System (NEMS), this paper assesses the future of the forest products industry under three possible U.S. policy scenarios: (1) a national renewable electricity standard, (2) a national policy of carbon constraints, and (3) incentives for industrial energy efficiency. In addition, we discuss how these policy scenarios might interface with the recently strengthened U.S. renewable fuels standards. The principal focus is on how forest products including residues might be utilized under different policy scenarios, and what such market shifts might mean for electricity and biomass prices, as well as energy consumption and carbon emissions. The results underscore the value of incentivizing energy efficiency in a portfolio of energy and climate policies in order to moderate electricity and biomass price escalation while strengthening energy security and reducing CO₂ emissions.     

Fuel price and technological uncertainty in a real options model for electricity planning

Electricity generation is an important source of total CO₂ emissions, which in turn have been found to relate to an acceleration of global warming. Given that many OECD countries have to replace substantial portions of their electricity-generating capacity over the next 10–20 years, investment decisions today will determine the CO₂-intensity of the future energy mix. But by what type of power plants will old (mostly fossil-fuel-fired) capacity be replaced? Given that modern, less carbon-intensive technologies are still expensive but can be expected to undergo improvements due to technical change in the near future, they may become more attractive, especially if fossil fuel price volatility makes traditional technologies more risky. At the same time, technological progress is an inherently uncertain process itself. In this paper, we use a real options model with stochastic technical change and stochastic fossil fuel prices in order to investigate their impact on replacement investment decisions in the electricity sector. We find that the uncertainty associated with the technological progress of renewable energy technologies leads to a postponement of investment. Even the simultaneous inclusion of stochastic fossil fuel prices in the same model does not make renewable energy competitive compared to fossil-fuel-fired technology in the short run based on the data used. This implies that policymakers have to intervene if renewable energy is supposed to get diffused more quickly. Otherwise, old fossil-fuel-fired equipment will be refurbished or replaced by fossil-fuel-fired capacity again, which enforces the lock-in of the current system into unsustainable electricity generation.     

Hedging local volume risk using forward markets: Nordic case

With focus on the Nordic electricity market, this paper develops hedging strategies for an electricity distributor who manages price and volume risk from fixed price agreements on stochastic electricity load. Whereas the distributor trades in the spot market at area prices, the financial contracts used for hedging are settled against the system price. Area and system prices are correlated with electricity load, as are price differences. In practice, however, this is often disregarded. Here, we develop a joint model for the area price, the system price and the load, accounting for correlations, and we suggest various strategies for hedging in the presence of local volume risk. We benchmark against a strategy that ignores correlation and hedges at expected load, as is common practice in the industry. Using data from 2013 and 2014 for two Danish bidding areas, we show that our best hedging strategy reduces gross loss by 5.8% and 13.6% and increases gross profit by 3.8% and 9.5%, respectively. Although this is partly due to the inclusion of correlation, we show that performance improvement is mainly driven by the choice of risk measure.     

The relationship among energy prices and energy consumption in China

The pricing mechanism for energy is not in line with the international standards, because the energy prices are controlled by the government partly or completely in China. Chinese government made a lot of efforts to improve the pricing mechanism for energy. The relations between Chinese energy prices and energy consumption are the foundations to reform the mechanism. In this paper, the relations between Chinese energy consumption and energy prices are researched by cointegration equations, impulse response functions, granger causality and variance decomposition. The cointegration relations among energy prices, energy consumption and economic outputs show that higher energy price will decrease energy consumption in Chinese industrial sectors but will not reduce the economic output in the long run. The cointegration relation between energy price and household energy consumption shows that higher energy price will decrease household energy consumption in the long run and increase it in the short run. So Chinese government should deepen the reform of pricing mechanism for energy, and increase the energy prices reasonably to save energy.     

Correlation between Chinese and international energy prices based on a HP filter and time difference analysis

To establish a reasonable system and mechanism for Chinese energy prices, we use the Granger causality test, Hodrick–Prescott (HP) filter and time difference analysis to research the pricing relationship between Chinese and international energy prices. We find that Chinese and international crude oil prices changed synchronously while Chinese refined oil prices follow the changes of international oil prices with the time difference being about 1 month to 2 months. Further, Australian coal prices Granger causes Chinese coal prices, and there is a high correlation between them. The U.S. electricity price is influenced by the WTI crude oil price, the U.S. gasoline price and the HenryHub gas price. Due to the unreasonable price-setting mechanism and regulation from the central government, China′s terminal market prices for both electricity and natural gas do not reflect the real supply–demand situation. This paper provides quantitative results on the correlation between Chinese and international energy prices to better predict the impact of international energy price fluctuations on China′s domestic energy supply and guide the design of more efficient energy pricing policies. Moreover, it provides references for developing countries to improve their energy market systems and trading, and to coordinate domestic and international energy markets.     

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn.     

Examination of energy price policies in Iran for optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm

The current subsidized energy prices in Iran are proposed to be gradually eliminated over the next few years. The objective of this study is to examine the effects of current and future energy price policies on optimal configuration of combined heat and power (CHP) and combined cooling, heating, and power (CCHP) systems in Iran, under the conditions of selling and not-selling electricity to utility. The particle swarm optimization algorithm is used for minimizing the cost function for owning and operating various CHP and CCHP systems in an industrial dairy unit. The results show that with the estimated future unsubsidized utility prices, CHP and CCHP systems operating with reciprocating engine prime mover have total costs of 5.6 and $2.9×10⁶ over useful life of 20 years, respectively, while both systems have the same capital recovery periods of 1.3 years. However, for the same prime mover and with current subsidized prices, CHP and CCHP systems require 4.9 and 5.2 years for capital recovery, respectively. It is concluded that the current energy price policies hinder the promotion of installing CHP and CCHP systems and, the policy of selling electricity to utility as well as eliminating subsidies are prerequisites to successful widespread utilization of such systems.     

Security of supply and regulation of energy networks

In recent years, the security of energy supplies has re-emerged as a central issue in the energy policy arena in the UK and elsewhere. This re-emergence takes place against a backdrop of increased liberalisation of the energy markets, so that security of supply needs to be revisited within this context. Security of supply is multifaceted, but is often discussed in terms of physical availability of energy sources and their commodity price risk. This paper discusses the relationship between security of supply and network regulation—that is, how the energy networks, and appropriate regulation of them, can contribute to security of supply in liberalised energy sectors. Energy networks are predominantly natural monopolies and as a result are generally subject to regulatory oversight. We discuss a range of issues and trends that pose challenges and opportunities to network regulation and which call for new and innovative measures. The paper identifies a number of areas where network regulation can play a significant role in increasing the security of supply of future energy systems.     

Volatility linkages between energy and agricultural commodity prices

We investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact for investment and hedging strategies of market participants as well as for policy makers. Volatilities and their short and long run linkages are analyzed using an asymmetric dynamic conditional correlation GARCH model as well as a multivariate multiplicative volatility model. Our approach provides a flexible and accurate fitting procedure for volatility and correlation risk. We find that in the long run prices move together and preserve an equilibrium, while correlations are mostly positive with persistent market shocks. Our results reveal that concerns about biodiesel being the cause of high and volatile agricultural commodity prices are rather unjustified.     

Input–output analysis of alternative policies implemented on the energy activities: An application for Catalonia

The aim of this paper is to analyze the economic impact of alternative policies implemented on the energy activities of the Catalan production system. Specifically, we analyze the effects of a tax on intermediate energy uses, a reduction in intermediate energy demand, and a tax on intermediate uses combined with a reduction in intermediate energy demand. The methodology involves two versions of the input–output price model: a competitive price formulation and a mark-up price formulation. The input–output price framework will make it possible to evaluate how the alternative measures modify production prices, consumption prices, private real income, and intermediate energy uses. The empirical application is for the Catalan economy and uses economic data for the year 2001. The combination of a tax on energy uses and an improvement in the energy efficiency of the production system is a measure that accomplishes both economic and environmental goals, since it has no effects on prices, it has a positive effect on private real income and, finally, energy consumption is considerably reduced.     

Pricing the (European) option to switch between two energy sources: An application to crude oil and natural gas

We consider a firm, which can choose between crude oil and natural gas to run its business. The firm selects the energy source, which minimizes its energy or production costs at a given time horizon. Assuming the energy strategy to be established over a fixed time window, the energy choice decision will be made at a given future date T. In this light, the firm's energy cost can be considered as a long position in a risk-free bond by an amount of the terminal oil price, and a short position in a European put option to switch from oil to gas by an amount of the terminal oil price too. As a result, the option to switch from crude oil to natural gas allows for establishing a hedging strategy with respect to energy costs. Modeling stochastically the underlying asset of the European put, we propose a valuation formula of the option to switch and calibrate the pricing formula to empirical data on a daily basis. Hence, our innovative framework handles widely the hedge against the price increase of any given energy source versus the price of another competing energy source (i.e. minimizing energy costs). Moreover, we provide a price for the cost-reducing effect of the capability to switch from one energy source to another one (i.e. hedging energy price risk).     

Energy and exergy prices of various energy sources along with their CO2 equivalents

Various types of energy sources are used in the residential and industrial sectors. Choosing the type of sources is important. When an energy source is selected, its CO₂ equivalent and energy and exergy prices must be known for a sustainable future and for establishing energy policies. These prices are based on their energy values. Exergy analysis has been recently applied to a wide range of energy-related systems. Thus, obtaining the exergy values has become more meaningful for long-term planning. In this study, energy and exergy prices of various energy sources along with CO₂ equivalents are calculated and compared for residential and industrial applications in Turkey. Energy sources considered include coal, diesel oil, electricity, fuel oil, liquid petroleum gas (LPG), natural gas, heat pumps and geothermal, and their prices were obtained over a period of 18 months, from January 2008 to June 2009. For the residential and industrial sectors, minimum energy and exergy prices were found for ground source heat pumps, while maximum energy and exergy prices belong to LPG for both sectors.     

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.     

Power-to-ammonia in future North European 100 % renewable power and heat system

Power-to-gas and other chemicals-based storages are often suggested for energy systems with high shares of variable renewable energy. Here we study the North European power and district heat system with alternative long-term storage, the power-to-ammonia (P2A) technology. Assuming fully renewable power and heat sectors and large-scale electrification of road transport, we perform simultaneous optimization of capacity investments and dispatch scheduling of wind, solar, hydro and thermal power, energy storages as well as transmission, focusing on year 2050. We find that P2A has three major roles: it provides renewable feedstock to fertilizer industry and it contributes significantly to system balancing over both time (energy storage) and space (energy transfer). The marginal cost of power-based ammonia production in the studied scenarios varied between 431 and 528 €/t, which is in the range of recent ammonia prices. Costs of P2A plants were dominated by electrolysis. In the power and heat sector, with our cost assumptions, P2A becomes competitive compared to fossil natural gas only if gas price or CO₂ emission price rises above 70 €/MWh or 200 €/tCO₂.     

Wind farm investment risks under uncertain CDM benefit in China

China has set an ambitious target to increase its wind power capacity by 35 GW from 2007 to 2020. The country’s hunger for clean power provides great opportunities for wind energy investors. However, risks from China’s uncertain electricity market regulation and an uncertain energy policy framework, mainly due to uncertain Clean Development Mechanism (CDM) benefits, prevent foreign investors from investing in China’s wind energy. The objectives of this paper are to: (1) quantify wind energy investment risk premiums in an uncertain international energy policy context and (2) evaluate the impact of uncertain CDM benefits on the net present values of wind power projects. With four scenarios, this study simulates possible prices of certified emissions reductions (CERs) from wind power projects. Project net present values (NPVs) have been calculated. The project risk premiums are drawn from different and uncertain CER prices. Our key findings show that uncertain CDM benefits will significantly affect the project NPVs. This paper concludes that the Chinese government needs revising its tariff incentives, most likely by introducing fixed feed-in tariffs (FITs), and re-examining its CDM-granting policy and its wind project tax rates, to facilitate wind power development and enable China to achieve its wind energy target.     

Risk-constrained probabilistic optimal scheduling of FCPP-CHP based energy hub considering demand-side resources

Renewable energy sources (RES) with sharing a large percentage of future energy generation capacities play an essential role in the decarbonization of the future electricity and thermal networks as well as transportation sectors. However, the uncertainties in their outputs make some difficulties in making operational decisions. Hydrogen energy plays a considerable role in this concept. Besides, energy hubs (EHs) provide an efficient and reliable framework for gathering multi-type energy carriers.This paper optimally schedules the operating of the EH and decreases the emission cost, considering the electrical and thermal demand response (DR) program in a probabilistic environment. Besides plug-in electric vehicles (PEVs) and a complete model of hydrogen-based renewable energy sources are presented in the EH. Taking into account uncertainties of electrical/thermal energy markets real-time prices, customers' energy demand, and energy production of RESs into account, various scenarios are generated using the Monte Carlo simulation technique. Next, an efficient method is used to reduce the number of the scenario to make the optimization problem computable and fast. In order to reduce the risk of encountering high operating costs, the conditional value at risk (CVaR) technique is used to manage the associated risk. Simulation results show the efficiency of the proposed method in decreasing the operational cost and managing the risk of encountering unfavorable states.     

Sectoral energy demand in Canadian manufacturing industries

Several studies have been undertaken which analyse the price elasticities of demand for energy in the aggregate manufacturing sectors of different countries. This paper investigates the impact of changing energy prices on factor demands in each of the many subsectors of manufacturing in Canada. Translog cost functions are estimated and the energy price elasticities of demand are derived. These elasticities enable us to pinpoint those sectors that will have the most difficulty in adapting to high energy prices.