Biomass and CCS: The influence of technical change

The combination of bioenergy production and carbon capture and storage technologies (BECCS) provides an opportunity to create negative emissions of CO₂ in biofuel production. However, high capture costs reduce profitability. This paper investigates carbon price uncertainty and technological uncertainty through a real option approach. We compare the cases of early and delayed CCS deployments. An early technological progress may arise from aggressive R&D and pilot project programs, but the expected cost reduction remains uncertain. We show that this approach results in lower emissions and more rapid investment returns although these returns will not fully materialise until after 2030. In a second set of simulations, we apply an incentive that prioritises sequestered emissions rather than avoided emissions. In other words, this economic instrument does not account for CO₂ emissions from the CCS implementation itself, but rewards all the sequestered emissions. In contrast with technological innovations, this subsidy is certain for the investor. The resulting investment level is higher, and the project may become profitable before 2030. Negative emission in bioethanol production does not seem to be a short-term solution in our framework, whatever the carbon price drift.     

An integrated scenario analysis for future zero‐carbon energy system

An integrated scenario analysis methodology has been proposed for zero‐carbon energy system in perspectives of social‐economy, environment and technology. By using the methodology, service demands in all sectors were estimated based on social‐economic data, and then the best technology and energy mixes were obtained to meet the service demands. The methodology was applied to Japan toward zero‐carbon energy system out to the year of 2100, and three different scenarios of nuclear power development are considered in light of the Fukushima accident: (i) no further introduction of nuclear, (ii) fixed portion and (iii) no limit of nuclear. The results show that, zero‐carbon energy scenario can be attained in the year 2100 when electricity will supply 75% of total energy consumption, and three power generation scenarios were proposed, 30% renewable and 70% gas‐carbon capture and storage (CCS) in Scenario 1, respective one‐third nuclear, renewable and gas‐CCS in Scenario 2, and 60% nuclear power, 20% renewable and 10% gas‐CCS in Scenario 3. Finally, Scenario 2 is rated as the most balanced scenario by putting emphasis on the availability of diversified power source, considering the inter‐comparison of the three scenarios from the four aspects of cost, CO₂ emission, risk and diversity. Copyright © 2015 John Wiley & Sons, Ltd.     

Carbon capture and storage at scale: Lessons from the growth of analogous energy technologies

At present carbon capture and storage (CCS) is very expensive and its performance is highly uncertain at the scale of commercial power plants. Such challenges to deployment, though, are not new to students of technological change. Several successful technologies, including energy technologies, have faced similar challenges as CCS faces now. To draw lessons for the CCS industry from the history of other energy technologies that, as with CCS today, were risky and expensive early in their commercial development, we have analyzed the development of the US nuclear-power industry, the US SO₂-scrubber industry, and the global liquefied natural gas (LNG) industry. Through analyzing the development of the analogous industries we arrive at three principal observations. First, government played a decisive role in the development of all of these analogous technologies. Second, diffusion of these technologies beyond the early demonstration and niche projects hinged on the credibility of incentives for industry to invest in commercial-scale projects. Third, the conventional wisdom that experience with technologies inevitably reduces costs does not necessarily hold. Risky and capital-intensive technologies may be particularly vulnerable to diffusion without accompanying reductions in cost.     

The diffusion of renewable electricity in the presence of climate policy and technology learning: The case of Sweden

The overall objective of this paper is to analyze the impact of climate policy and technology learning on future investments in the Swedish power sector. Methodologically we assess the lifetime engineering costs of different power generation technologies in Sweden, and analyze the impact of carbon pricing on the competitive cost position of these technologies under varying rate-of-return requirements. We also argue that technological learning in the Swedish power sector – not the least in the case of wind power – is strongly related to the presence of international learning and R&D spillovers, and for this reason capacity expansions abroad have important influences of the future cost of power generation in Sweden. The results suggest that renewable power will benefit from existing EU climate policy measures, but overall additional policy instruments (e.g., green certificate schemes) are also needed to stimulate the diffusion of renewable power. Moreover, under a recent European Commission scenario and using estimated learning rates for wind power and the combined cycle gas turbine (CCGT), wind power gains considerable competitive ground due to international technology learning impacts. These latter results are, however, very sensitive to the assumed learning-by-doing rates for wind power and CCGT, respectively.     

First‐mover advantages of the European Union's climate change mitigation strategy

This paper assesses the costs and benefits for the European Union (EU) as a first mover in climate change mitigation. Scenarios of EU and global climate action to 2050 are quantified using the GEME3‐RD model, a global multi‐sectoral computable general equilibrium model with endogenous technology progress and detailed representation of the clean energy technologies. The model includes two‐factor learning curves (stock and research and development funding) for clean energy technologies, such as electric vehicles, carbon capture and storage, and renewable and efficient appliances. Funding of research and development is endogenously derived as a production factor enabling productivity improvement. The scenarios compare stylised climate strategies, which are asymmetric by world region and have different emission reduction profiles over time. Assuming that strong climate mitigation action will be undertaken only after 2030, the scenarios compare two main strategies for the EU: pursuing strong emission reduction unilaterally until 2030 versus deferring action for the period after 2030. Asymmetric climate action by region enables asymmetric innovation and manufacturing of clean energy technologies. The macroeconomic assessment of the climate action strategies does not only depend on costs of clean technologies but also on induced technology progress implying asymmetric effects on manufacturing and trade by region, taking into account spillovers. The model‐based projections show clear advantages for the EU as a first mover in climate change mitigation compared with a delaying of climate action until 2030. Delayed climate action until 2030 implies higher gross domestic product losses for the EU compared with unilateral action until 2030. The model finds benefits of early action by the EU driven by activity and progress related to clean energy technologies as the EU can achieve competitive advantages over other world regions pursuing climate action later. Copyright © 2016 John Wiley & Sons, Ltd.     

Technology interactions among low-carbon energy technologies: What can we learn from a large number of scenarios?

Advanced low-carbon energy technologies can substantially reduce the cost of stabilizing atmospheric carbon dioxide concentrations. Understanding the interactions between these technologies and their impact on the costs of stabilization can help inform energy policy decisions. Many previous studies have addressed this challenge by exploring a small number of representative scenarios that represent particular combinations of future technology developments. This paper uses a combinatorial approach in which scenarios are created for all combinations of the technology development assumptions that underlie a smaller, representative set of scenarios. We estimate stabilization costs for 768 runs of the Global Change Assessment Model (GCAM), based on 384 different combinations of assumptions about the future performance of technologies and two stabilization goals. Graphical depiction of the distribution of stabilization costs provides first-order insights about the full data set and individual technologies. We apply a formal scenario discovery method to obtain more nuanced insights about the combinations of technology assumptions most strongly associated with high-cost outcomes. Many of the fundamental insights from traditional representative scenario analysis still hold under this comprehensive combinatorial analysis. For example, the importance of carbon capture and storage (CCS) and the substitution effect among supply technologies are consistently demonstrated. The results also provide more clarity regarding insights not easily demonstrated through representative scenario analysis. For example, they show more clearly how certain supply technologies can provide a hedge against high stabilization costs, and that aggregate end-use efficiency improvements deliver relatively consistent stabilization cost reductions. Furthermore, the results indicate that a lack of CCS options combined with lower technological advances in the buildings sector or the transportation sector is the most powerful predictor of high-cost scenarios.     

Energy‐saving evaluation of a thermosyphon heat recovery unit for an air‐conditioning system

The energy‐saving effect and economic benefits of a thermosyphon heat recovery unit installed in a shopping mall are investigated. To evaluate the thermal performance of the heat recovery unit in a season, a seasonal temperature effectiveness is advanced, and its calculation formula is deduced referring to the calculation method of seasonal energy efficiency ratio (SEER) for an air conditioner. The annual operating energy‐saving effect of the unit is analyzed by using the seasonal temperature effectiveness while the static economic evaluation method is applied for the economic benefits analysis of the unit. The analysis results indicate the seasonal temperature effectiveness of the unit is 66.08% in the winter and 55.43% in the summer. The energy‐saving effect of the unit is quite remarkable, and the payback time is about 2.65 years. © 2013 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library (wileyonlinelibrary.com/journal/htj). DOI 10.1002/htj.21049     

Alternative energy development strategies for China towards 2030

The purposes, objectives and technology pathways for alternative energy development are discussed with the aim of reaching sustainable energy development in China. Special attention has been paid to alternative power and alternative vehicle fuels. Instead of limiting alternative energy to energy sources such as nuclear and renewable energy, the scope of discussion is extended to alternative technologies such as coal power with carbon capture and sequestration (CCS), electric and hydrogen vehicles. In order to take account of the fact that China’s sustainable energy development involves many dimensions, a six-dimensional indicator set has been established and applied with the aim of comprehensively evaluating different technology pathways in a uniform way. The analysis reaches the following conclusions: (a) in the power sector, wind power, nuclear power and hydro power should be developed as much as possible, while R&D of solar power and coal power with CCS should be strengthened continuously for future deployment. (b) in the transportation sector, there is no foreseeable silver bullet to replace oil on a large scale within the time frame of 20 to 30 years. To ease the severe energy security situation, expedient choices like coal derived fuels could be developed. However, its scale should be optimized in accordance to the trade-off of energy security benefits, production costs and environmental costs. Desirable alternative fuels (or technologies) like 2nd generation biofuels and electrical vehicles should be the subject of intensive R&D with the objective to be cost effective as early as possible.     

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.     

Analysis of energy technology changes and associated costs

An integrated mathematical model constituting of interlinked submodels on technology costs, progress and market penetration has been developed. The model was applied to a few new energy technologies to investigate the economic boundary conditions for a full market breakthrough and corresponding market impact on a 50 years time scale. The model shows that public subsidies amounting to slightly over 220 billion € in total worldwide would be necessary over the next 30–40 years to bring wind and photovoltaics to a cost breakthrough in the market and to reach a 20 and 5% share of all electricity at t = 50 years, respectively. These up‐front learning investments would be partly amortized toward the end of the interval as the new technologies become cost competitive but could be fully paid off earlier if CO₂ emission trading schemes emerge even with modest CO₂ price levels. The findings are sensitive to changes in the parameter assumptions used. For example, a 2% uncertainty in the main parameters of the model could lead to a spread of tens of per cents in the future energy impact and subsidy needs, or when related to the above subsidy estimate, 155–325 billion €. This underlines the overall uncertainty in predicting future impacts and resource needs for new energy technologies. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimating GHG emission mitigation supply curves of large-scale biomass use on a country level

This study evaluates the possible influences of a large-scale introduction of biomass material and energy systems and their market volumes on land, material and energy market prices and their feedback to greenhouse gas (GHG) emission mitigation costs. GHG emission mitigation supply curves for large-scale biomass use were compiled using a methodology that combines a bottom-up analysis of biomass applications, biomass cost supply curves and market prices of land, biomaterials and bioenergy carriers. These market prices depend on the scale of biomass use and the market volume of materials and energy carriers and were estimated using own-price elasticities of demand. The methodology was demonstrated for a case study of Poland in the year 2015 applying different scenarios on economic development and trade in Europe. For the key technologies considered, i.e. medium density fibreboard, poly lactic acid, electricity and methanol production, GHG emission mitigation costs increase strongly with the scale of biomass production. Large-scale introduction of biomass use decreases the GHG emission reduction potential at costs below 50 €/Mg CO_2eq with about 13–70% depending on the scenario. Biomaterial production accounts for only a small part of this GHG emission reduction potential due to relatively small material markets and the subsequent strong decrease of biomaterial market prices at large scale of production. GHG emission mitigation costs depend strongly on biomass supply curves, own-price elasticity of land and market volumes of bioenergy carriers. The analysis shows that these influences should be taken into account for developing biomass implementations strategies.     

Energy supply performance and environmental load‐reduction effect of a cogeneration system for an apartment building using distributed heat storage technology

In order to make distributed generation systems for apartment buildings economically viable, it is essential to develop an efficient and low‐cost heat supply system. We are developing a new cogeneration system (Neighboring CoGeneration system: NCG system). The key concept of this system is to install a heat storage unit for the hot water supply, floor heating, and bath heating in each house, and to connect the heat storage units by a single‐loop hot water pipe. The system leads to time leveling of the total heat supply and reduced installation costs. Furthermore, it is expected that the cogeneration can operate according to electrical demand because of the large heat storage capacity of the system. In this study, a dynamic simulation model is developed to evaluate the performance and environmental load‐reduction effect of the NCG system for 50 households. The results show that the NCG system can supply sufficient heat for peak demand in winter and reduce annual CO₂ emissions by 23% on average. © 2013 Wiley Periodicals, Inc. Heat Trans Asian Res, 42(8): 745–757, 2013; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.20376     

Implications of technological learning on the prospects for renewable energy technologies in Europe

The objective of this article is to examine the consequences of technological developments on the market diffusion of different renewable electricity technologies in the EU-25 until 2020, using a market simulation model (ADMIRE REBUS). It is assumed that from 2012 a harmonized trading system will be implemented, and a target of 24% renewable electricity (RES-E) in 2020 is set and met. By comparing optimistic and pessimistic endogenous technological learning scenarios, it is found that diffusion of onshore wind energy is relatively robust, regardless of technological development, but diffusion rates of offshore wind energy and biomass gasification greatly depend on their technological development. Competition between these two options and (existing) biomass combustion options largely determines the overall costs of electricity from renewables and the choice of technologies for the individual member countries. In the optimistic scenario, in 2020 the market price for RES-E is 1 €ct/kWh lower than in the pessimistic scenario (about 7 vs. 8 €ct/kWh). As a result, total RES-E production costs are 19% lower, and total governmental expenditures for RES-market stimulation are 30% lower in the optimistic scenario.     

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.     

Evaluating the development of carbon capture and storage technologies in the United States

Carbon capture and storage (CCS) is seen as an important solution to solve the twin challenge of reducing GHG emissions, while utilizing fossil fuel reserves to meet future energy requirements. In this study an innovation systems perspective is applied to review the development of CCS technologies in the US between 2000 and 2009 and to come up with policy recommendations for technology managers that wish to accelerate the deployment of CCS. The analysis describes the successful built-up of an innovation system around CCS and pinpoints the key determinants for this achievement. However, the evaluation of the system's performance also indicates that America's leading role in the development of CCS should not be taken for granted. It shows that the large CCS R&D networks, as well as the extensive CCS knowledge base, which have been accumulated over the past decade, have not yet been valorized by entrepreneurs to explore the market for integrated CCS concepts linked to power generation. Therefore, it is argued that the build-up of the innovation system has entered a critical phase that is decisive for a further thriving development of CCS technologies in the US. This study provides a clear understanding of the current barriers to the technology's future deployment and outlines a policy strategy that (1) stimulates technological learning; (2) facilitates collaboration and coordination in CCS actor networks; (3) creates financial and market incentives for the technology; and (4) provides supportive regulation and sound communication on CCS.     

The case for a new energy research,development and promotion policy for the UK

This paper is a critical assessment of the current balance of efforts towards energy research and development (R&D) and the promotion of low-carbon electricity technologies in the UK. We review the UK's main technological options and their estimated cost ranges in the medium term. We contrast the energy R&D spending with the current and expected future cost of renewable promotion policies and point out the high cost of carbon saving through existing renewable promotion arrangements. We also note that liberalisation of the electricity sector has had significant implications for the landscape of energy R&D in the UK. We argue that there is a need for reappraisal of the soundness and balance of the energy R&D and renewable capacity deployment efforts towards new energy technologies. We suggest that the cost-effectiveness of UK deployment policies needs to be more closely analysed as associated costs are non-trivial and expected to rise. We also make a case for considering increasing the current low level of energy R&D expenditure. Much of energy R&D is a public good and we should consider whether the current organisation of R&D effort is fit for purpose. We argue that it is important to build and maintain the research capability in the UK in order to absorb spillovers of technological progress elsewhere in the world. Against this background, the recent signs that an energy R&D renaissance could be underway are therefore positive and welcome.     

Policy interactions,risk and price formation in carbon markets

Carbon pricing is an important mechanism for providing companies with incentives to invest in carbon abatement. Price formation in carbon markets involves a complex interplay between policy targets, dynamic technology costs, and market rules. Carbon pricing may under-deliver investment due to R&D externalities, requiring additional policies which themselves affect market prices. Also, abatement costs depend on the extent of technology deployment due to learning-by-doing. This paper introduces an analytical framework based on marginal abatement cost (MAC) curves with the aim of providing an intuitive understanding of the key dynamics and risk factors in carbon markets. The framework extends the usual static MAC representation of the market to incorporate policy interactions and some technology cost dynamics. The analysis indicates that supporting large-scale deployment of mature abatement technologies suppresses the marginal cost of abatement, sometimes to zero, whilst increasing total abatement costs. However, support for early stage R&D may reduce both total abatement cost and carbon price risk. An important aspect of the analysis is in elevating risk management considerations into energy policy formation, as the results of the stochastic modelling indicate wide distributions for the emergence of carbon prices and public costs around the policy expectations.     

Modeling technological learning and its application for clean coal technologies in Japan

Estimating technological progress of emerging technologies such as renewables and clean coal technologies becomes important for designing low carbon energy systems in future and drawing effective energy policies. Learning curve is an analytical approach for describing the decline rate of cost and production caused by technological progress as well as learning. In the study, a bottom-up energy-economic model including an endogenous technological learning function has been designed. The model deals with technological learning in energy conversion technologies and its spillover effect. It is applied as a feasibility study of clean coal technologies such as IGCC (Integrated Coal Gasification Combined Cycle) and IGFC (Integrated Coal Gasification Fuel Cell System) in Japan. As the results of analysis, it is found that technological progress by learning has a positive impact on the penetration of clean coal technologies in the electricity market, and the learning model has a potential for assessing upcoming technologies in future.     

Alternative energy development strategies for China towards 2030

The purposes, objectives and technology pathways for alternative energy development are discussed with the aim of reaching sustainable energy development in China. Special attention has been paid to alternative power and alternative vehicle fuels. Instead of limiting alternative energy to energy sources such as nuclear and renewable energy, the scope of discussion is extended to alternative technologies such as coal power with carbon capture and sequestration (CCS), electric and hydrogen vehicles. In order to take account of the fact that China’s sustainable energy development involves many dimensions, a six-dimensional indicator set has been established and applied with the aim of comprehensively evaluating different technology pathways in a uniform way. The analysis reaches the following conclusions: (a) in the power sector, wind power, nuclear power and hydro power should be developed as much as possible, while R&D of solar power and coal power with CCS should be strengthened continuously for future deployment. (b) in the transportation sector, there is no foreseeable silver bullet to replace oil on a large scale within the time frame of 20 to 30 years. To ease the severe energy security situation, expedient choices like coal derived fuels could be developed. However, its scale should be optimized in accordance to the trade-off of energy security benefits, production costs and environmental costs. Desirable alternative fuels (or technologies) like 2nd generation biofuels and electrical vehicles should be the subject of intensive R&D with the objective to be cost effective as early as possible.     

Assessing the impacts of technology improvements on the deployment of marine energy in Europe with an energy system perspective

Marine energy could play a significant role in the long-term energy system in Europe, and substantial resources have been allocated to research and development in this field. The main objective of this paper is to assess how technology improvements affect the deployment of marine energy in the EU. To do so the linear optimization, technology-rich model JRC-EU-TIMES is used. A sensitivity analysis is performed, varying technology costs and conversion efficiency under two different carbon-emissions paths for Europe: a current policy initiative scenario and a scenario with long-term overall CO₂ emission reductions. We conclude that, within the range of technology improvements explored, wave energy does not become cost-competitive in the modelled horizon. For tidal energy, although costs are important in determining its deployment, conversion efficiency also plays a crucial role. Ensuring the cost-effectiveness of tidal power by 2030 requires efficiency improvements by 40% above current expectations or cost reductions by 50%. High carbon prices are also needed to improve the competitiveness of marine energy. Finally, our results indicate that investing 0.1–1.1 BEuro₂₀₁₀ per year in R&D and innovation for the marine power industry could be cost-effective in the EU, if leading to cost reduction or efficiency improvements in the range explored.