Introducing technology learning for energy technologies in a national CGE model through soft links to global and national energy models

This paper describes a method to model the influence by global policy scenarios, particularly spillover of technology learning, on the energy service demand of the non-energy sectors of the national economy. It is exemplified by Norway. Spillover is obtained from the technology-rich global Energy Technology Perspective model operated by the International Energy Agency. It is provided to a national hybrid model where a national bottom-up Markal model carries forward spillover into a national top-down CGE¹ model at a disaggregated demand category level. Spillover of technology learning from the global energy technology market will reduce national generation costs of energy carriers. This may in turn increase demand in the non-energy sectors of the economy because of the rebound effect. The influence of spillover on the Norwegian economy is most pronounced for the production level of industrial chemicals and for the demand for electricity for residential energy services. The influence is modest, however, because all existing electricity generating capacity is hydroelectric and thus compatible with the low emission policy scenario. In countries where most of the existing generating capacity must be replaced by nascent energy technologies or carbon captured and storage the influence on demand is expected to be more significant.     

Global technology learning and national policy—An incentive scheme for governments to assume the high cost of early deployment exemplified by Norway

In this paper it is argued that technology learning may be both a barrier and an incentive for technology change in the national energy system. The possibility to realize an ambitious global emission reduction scenario is enhanced by coordinated action between countries in national policy implementation. An indicator for coordinated action is suggested. Targeted measures to increase deployment of nascent energy technologies and increasing energy efficiency in a small open economy like Norway are examined. The measures are evaluated against a set of baselines with different levels of spillover of technology learning from the global market. It is found that implementation of technology subsidies increase the national contribution to early deployment independent of the level of spillover. In a special case with no spillover for offshore floating wind power and endogenous technology learning substantial subsidy or a learning rate of 20% is required. Combining the high learning rate and a national subsidy increases the contribution to early deployment. Enhanced building code on the other hand may reduce Norway’s contribution to early deployment, and thus the realization of a global emission reduction scenario, unless sufficient electricity export capacity is assured.     

Internalisation of external cost in the power generation sector: Analysis with Global Multi-regional MARKAL model

The Global MARKAL-Model (GMM), a multi-regional “bottom-up” partial equilibrium model of the global energy system with endogenous technological learning, is used to address impacts of internalisation of external costs from power production. This modelling approach imposes additional charges on electricity generation, which reflect the costs of environmental and health damages from local pollutants (SO₂, NO_x) and climate change, wastes, occupational health, risk of accidents, noise and other burdens. Technologies allowing abatement of pollutants emitted from power plants are rapidly introduced into the energy system, for example, desulphurisation, NO_x removal, and CO₂ scrubbers. The modelling results indicate substantial changes in the electricity production system in favour of natural gas combined cycle, nuclear power and renewables induced by internalisation of external costs and also efficiency loss due to the use of scrubbers. Structural changes and fuel switching in the electricity sector result in significant reduction of emissions of both local pollution and CO₂ over the modelled time period. Strong decarbonisation impact of internalising local externalities suggests that ancillary benefits can be expected from policies directly addressing other issues then CO₂ mitigation. Finally, the detailed analysis of the total generation cost of different technologies points out that inclusion of external cost in the price of electricity increases competitiveness of non-fossil generation sources and fossil power plants with emission control.     

Forecasting of CO2 emissions from fuel combustion using trend analysis

The accelerating use of fossil fuels since the Industrial Revolution and the rapid destruction of forests causes a significant increase in greenhouse gases. The increasing threat of global warming and climate change has been the major, worldwide, ongoing concern especially in the last two decades. The impacts of global warming on the world economy have been assessed intensively by researchers since the 1990s. Worldwide organizations have been attempting to reduce the adverse impacts of global warming through intergovernmental and binding agreements. Carbon dioxide (CO₂) is one of the most foremost greenhouse gases in the atmosphere. The energy sector is dominated by the direct combustion of fuels, a process leading to large emissions of CO₂. CO₂ from energy represents about 60% of the anthropogenic greenhouse gas emissions of global emissions. This percentage varies greatly by country, due to diverse national energy structures. The top-25 emitting countries accounted 82.27% of the world CO₂ emissions in 2007. In the same year China was the largest emitter and generated 20.96% of the world total. Trend analysis is based on the idea that what has happened in the past gives traders an idea of what will happen in the future. In this study, trend analysis approach has been employed for modelling to forecast of energy-related CO₂ emissions. To this aim first, trends in CO₂ emissions for the top-25 countries and the world total CO₂ emissions during 1971–2007 are identified. On developing the regression analyses, the regression analyses with R² values less than 0.94 showing insignificant influence in statistical tests have been discarded. Statistically significant trends are indicated in eleven countries namely, India, South Korea, Islamic Republic of Iran, Mexico, Australia, Indonesia, Saudi Arabia, Brazil, South Africa, Taiwan, Turkey and the world total. The results obtained from the analyses showed that the models for those countries can be used for CO₂ emission projections into the future planning. The calculated results for CO₂ emissions from fitted curves have been compared with the projected CO₂ emissions given in International Energy Outlook 2009 of U.S. Department of Energy calculated from “high economic growth case scenario”, “reference case scenario” and “low economic growth case scenario” respectively. Agreements between calculated results and the projected CO₂ emissions from different scenarios are in the acceptable range.     

Determinants of variation in household CO2 emissions between and within countries

Variation in household CO₂ emissions between and within countries may have important consequences for the equity dimension of climate policies. In this study we aim to identify some determinants of national household CO₂ emissions and their distribution across income groups. For that purpose, we quantify the CO₂ emissions of households in the Netherlands, UK, Sweden and Norway around the year 2000 by combining a hybrid approach of process analysis and input–output analysis with data on household expenditures. Our results show that average households in the Netherlands and the UK give rise to higher amounts of CO₂ emissions than households in Sweden and Norway. Moreover, CO₂ emission intensities of household consumption decrease with increasing income in the Netherlands and the UK, whereas they increase in Sweden and Norway. A comparison of the national results at the product level points out that country characteristics, like energy supply, population density and the availability of district heating, influence variation in household CO₂ emissions between and within countries.     

National energy policies: Obstructing the reduction of global CO2 emissions? An analysis of Swedish energy policies for the district heating sector

The effect of national energy policies on a local Swedish district heating (DH) system has been studied, regarding the profitability of new investments and the potential for climate change mitigation. The DH system has been optimised regarding three investments: biomass-fuelled CHP (bio CHP), natural gas-fuelled combined cycle CHP (NGCC CHP) and biomass-fuelled heat-only boiler (bio HOB) in two scenarios (with or without national taxes and policy instruments). In both scenarios EU’s tradable CO₂ emission permits are included. Results from the study show that when national policies are included, the most cost-effective investment option is the bio CHP technology. However, when national taxes and policy instruments are excluded, the DH system containing the NGCC CHP plant has 30% lower system cost than the bio CHP system. Regardless of the scenario and when coal condensing is considered as marginal electricity production, the NGCC CHP has the largest global CO₂ reduction potential, about 300 ktonne CO₂. However, the CO₂ reduction potential is highly dependent on the marginal electricity production. Demonstrated here is that national policies such as tradable green certificates can, when applied to DH systems, contribute to investments that will not fully utilise the DH systems’ potential for global CO₂ emissions reductions.     

Energy caps: Alternative climate policy instruments for China?

Decoupling fossil energy demand from economic growth is crucial for China's sustainable development, especially for addressing severe local air pollution and global climate change. An absolute cap on coal or fossil fuel consumption has been proposed as a means to support the country's energy and climate policy objectives. We evaluate potential energy cap designs that differ in terms of target fuel, point of control, and national versus regional allowance trading using a global numerical general equilibrium model that separately represents 30 provinces in China. First, we simulate a coal cap and find that relative to a cap on all fossil fuels, it is significantly more costly and results in high localized welfare losses. Second, we compare fossil energy cap designs and find that a national cap on downstream fossil energy use with allowance trading across provinces is the most cost effective. Third, we find that a national fossil energy cap with trading is nearly as cost effective as a national CO₂ emissions trading system that penalizes energy use based on carbon content. As a fossil energy cap builds on existing institutions in China, it offers a viable intermediate step toward a full-fledged CO₂ emissions trading system.     

Multi-objective optimization model for sustainable Indonesian electricity system: Analysis of economic,environment, and adequacy of energy sources

This paper presents a multi-objective optimization model for a long-term generation mix in Indonesia. The objective of this work is to assess the economic, environment, and adequacy of local energy sources. The model includes two competing objective functions to seek the lowest cost of generation and the lowest CO₂ emissions while considering technology diffusion. The scenarios include the use of fossil reserves with or without the constraints of the reserve to production ratio and exports. The results indicate that Indonesia should develop all renewable energy and requires imported coal and natural gas. If all fossil resources were upgraded to reserves, electricity demand in 2050 could be met by domestic energy sources. The maximum share of renewable energy that can be achieved in 2050 is 33% with and 80% without technology diffusion. The least cost optimization produces lower generation costs than the least CO₂ emissions, as well as the combined scenario. Total CO₂ emissions in 2050 are five to six times as large as current emissions. The least CO₂ emissions scenario can reduce almost half of the CO₂ emissions of the least cost scenario by 2050. The proposed multi-objective optimization model leads some optimal solutions for a more sustainable electricity system.     

ACROPOLIS: An example of international collaboration in the field of energy modelling to support greenhouse gases mitigation policies

Energy models are considered as valuable tools to assess the impact of various energy and environment policies. The ACROPOLIS initiative, supported by the European Commission and the International Energy Agency, used up to 15 energy models to simulate and evaluate selected policy measures and instruments and then compare their impacts on energy systems essentially in terms of costs of greenhouse gas emissions (GHG) reduction and energy technology choice. Four case studies are formulated considering policies and measures on renewable portfolio schemes and internationally tradable green certificates, emissions trading and global GHG abatement target, energy efficiency standards and internalisation of external costs. The main focus of the project is on the electricity sector. From a large set of quantified results, ACROPOLIS provides an international scientific consensus, on some key issues, which could be useful in assessing and designing energy and environment policies at the world, European and national/regional levels. It concludes that the Kyoto targets (and their continuation beyond 2010 in specific scenarios) could be achieved at a cost around 1% of GDP through global emissions trading, indicating also that this flexibility mechanism is a more cost-effective instrument for GHG mitigation than meeting the goal domestically without trade. It demonstrates that internalising external costs through a price increase reduces local pollutants (SO_x, NO_x, and others) and it produces other benefits such as triggering the penetration of clean technologies in addition to the curbing of CO₂ emissions.     

Impact of inter-sectoral trade on national and global CO2 emissions: An empirical analysis of China and US

This paper attempts to discuss the CO₂ emissions embodied in Sino-US international trade using a sector approach. Based on an input–output model established in this study, we quantify the impact of Sino-US international trade on national and global CO₂ emissions. Our initial findings reveal that: In 2005, the US reduced 190.13 Mt CO₂ emissions through the consumption of imported goods from China, while increasing global CO₂ emissions by about 515.25 Mt. Similarly, China reduced 178.62 Mt CO₂ emissions through the consumption of US goods, while reducing global CO₂ emissions by 129.93 Mt. Sino-US international trade increased global CO₂ emissions by 385.32 Mt as a whole, of which the Chemical, Fabricated Metal Products, Non-metallic Mineral Products and Transportation Equipment sectors contributed an 86.71% share. Therefore, we suggest that accelerating the adjustment of China’s trade structure and export of US advanced technologies and experience related to clean production and energy efficiency to China as the way to reduce the negative impact of Sino-US trade on national and global CO₂ emissions. This behavior should take into account the processing and manufacturing industries as a priority, especially the Chemical, Fabricated Metal Products, Non-metallic Mineral Products and Transportation Equipment sectors.     

Quantifying regional economic impacts of CO2 intensity targets in China

To address rising energy use and CO₂ emissions, China's leadership has enacted energy and CO₂ intensity targets under the Twelfth Five-Year Plan (2011–2015), which are defined at both the national and provincial levels. We develop a computable general equilibrium (CGE) model with global coverage that disaggregates China's 30 provinces and includes energy system detail, and apply it to assess the impact of the current binding provincial CO₂ emissions intensity targets. We compare the impact of the provincial targets approach to a single target for China that achieves the same reduction in CO₂ emissions intensity at the national level. The national target assumes trading of emissions allowances across provinces, resulting in the least-cost reductions nationwide. We find that the national target results in about 20% lower welfare loss in China relative to the provincial targets approach. Given that the regional distribution of impacts has been an important consideration in the target-setting process, we focus on the changes in provincial-level CO₂ emissions intensity, CO₂ emissions, energy consumption, and economic welfare. We observe significant heterogeneity across provinces in terms of the energy system response as well as the magnitude of welfare impacts. We further model the current policy of fixed end-use electricity prices in China and find that national welfare losses increase. Assumptions about capital mobility have a substantial impact on national welfare loss, while changing assumptions about the future availability of domestic natural gas resources does not have a large effect.     

Solar assisted absorption cooling cycles for reduction of global warming: A multi-objective optimization approach

This work addresses the use of absorption cycles combined with solar energy for reducing the green house gas (GHG) emissions in the cooling sector. The problem of satisfying a given cooling demand at minimum cost and environmental impact is formulated as a bi-criterion non-linear optimization problem that seeks to minimize the total cost of the cooling application and its contribution to global warming. The latter metric, which is assessed following the principles of life cycle assessment (LCA), accounts for the impact caused during the construction and operation of the system. The concept of Pareto optimality is employed to discuss different alternatives for reducing the contribution to global warming that differ in their economic and environmental performance. We also analyze the effect of taxes on CO₂ on the economic and environmental performance of the system. The capabilities of the proposed approach are illustrated through a case study that addresses the design of a solar assisted ammonia-water single effect absorption cooling system with 100 kW of cooling capacity considering Barcelona weather conditions. We show that reducing the contribution to global warming considering the current energy prices and taxes on carbon dioxide emissions is technically viable but economically not appealing. We also discuss the conditions under which reducing the CO₂ emissions could become economically attractive.     

Effects of technological learning on future cost and performance of power plants with CO2 capture

This paper demonstrates the concept of applying learning curves in a consistent manner to performance as well as cost variables in order to assess the future development of power plants with CO₂ capture. An existing model developed at Carnegie Mellon University, which had provided insight into the potential learning of cost variables in power plants with CO₂ capture, is extended with learning curves for several key performance variables, including the overall energy loss in power plants, the energy required for CO₂ capture, the CO₂ capture ratio (removal efficiency), and the power plant availability. Next, learning rates for both performance and cost parameters were combined with global capacity projections for fossil-fired power plants to estimate future cost and performance of these power plants with and without CO₂ capture. The results of global learning are explicitly reported, so that they can be used for other purposes such as in regional bottom-up models. Results of this study show that IGCC with CO₂ capture has the largest learning potential, with significant improvements in efficiency and reductions in cost between 2001 and 2050 under the condition that around 3100 GW of combined cycle capacity is installed worldwide. Furthermore, in a scenario with a strict climate policy, mitigation costs in 2030 are 26, 11, 19 €/t (excluding CO₂ transport and storage costs) for NGCC, IGCC, and PC power plants with CO₂ capture, respectively, compared to 42, 13, and 32 €/t in a scenario with a limited climate policy. Additional results are presented for IGCC, PC, and NGCC plants with and without CO₂ capture, and a sensitivity analysis is employed to show the impacts of alternative assumptions on projected learning rates of different systems.     

Systemic approach for techno-economic evaluation of triple hybrid (RO,MSF and power generation) scheme including accounting of CO2 emission

A system of models for the techno-economic evaluation of a triple hybrid, reverse osmosis (RO), multistage flush (MSF) and power generation process has been developed. There are three groups of models underlying the system: (A) models describing power-generating technology; (B) models describing RO desalination, and (C) models describing MSF desalination. Any group of individual models, in turn, consists of a set of submodels of different hierarchy levels; they are: (1) technological submodel, (2) fuel or energy submodel, (3) ecological submodel and (4) economic submodel. (1) The technological submodel is focused on the calculation of technological characteristics at different operating loads of the generating systems; (2) the fuel or energy submodel covers the calculation of fuel influx into power-generating systems at different operating loads; (3) the ecological submodel focuses on estimation of CO₂ emissions at different operating regimes; (4) the economic submodel gives values of economic indicators, such as (a) cost of water, (b) cost of energy, and (c) accounting for CO₂ emissions through imposed carbon tax (assuming rates of environmental taxes recommended by European Union tax legislation). This paper contains an analysis of the behavior of economic and ecological indicators for various technological parameters and economic assumptions, such as (1) load, specific fuel consumption and efficiency of the energy generating system, (2) specific energy consumption for desalination, (3) specific emissions of CO₂, and (4) taxes on CO₂ emissions. The model presented can be applied for the analysis of schemes where seasonal surplus of unused power is utilized by RO which are characterized by higher efficiency of fuel consumption and decreasing specific CO₂ emissions.     

Increasing RES penetration through H2 technologies on Flores island,Azores: A techno-economic analysis

On Flores island (Azores, Portugal), energy production depends up to 47% on fossil fuels, namely Diesel. To minimize CO₂ emissions, the dependency on fuel prices, and to mitigate the consequences of variability and intermittency of renewable energy sources, a new energy system, based on H₂ storage was analysed. To achieve the optimal size of the system, a computer model was developed and a multi-objective genetic algorithm function was used to minimize three objectives: the difference of levelised cost of energy (△LCOE), CO₂ emissions and the percentage of renewable energy dumped (R_{RES, dump}). From the set of solutions obtained, one that meets R_{RES, dump} ≤ 1%, lowest CO₂ emissions and lowest △LCOE is chosen and an economical and energetic analysis is performed. The newly proposed system reduces Diesel consumption by 68,7% (1057487 L/year) and CO₂ emissions by 65,9% (2455,1 CO₂ tons/year) achieving a renewable energy sources (RES) penetration of 89% (36% increase), but fails to decrease the levelised cost of energy (56,62 €/MWh increase). However, a way to make the project viable through financial support is presented and an alternative to reduce the levelised cost of energy by commercialising the products of electrolysis, hydrogen and oxygen, is proposed. Finally, it is expected that with further research and development of H₂ technologies, economic and energetic results will get more advantageous, opening up new perspectives for the future.     

Climate sensitivity uncertainty and the necessity to transform global energy supply

This paper analyses the policy relevance of the dominant uncertainty in our current scientific understanding of the terrestrial climate system, and provides further evidence for the need to radically transform—this century—our global energy supply infrastructure, given the global average temperature increase as a result of anthropogenic carbon dioxide (CO₂) emissions. We investigate the effect on required CO₂ emission reduction efforts, both in terms of how much and when, of our present uncertain knowledge of the climate sensitivity to a doubling of the atmospheric CO₂ concentration. We use a top–down integrated assessment model in which there are two competing energy sources, fossil and non-fossil. Technological change is represented endogenously through learning curves, and modest but non-zero demand exists for the relatively expensive carbon-free energy resource. We find that during the forthcoming two decades the relative roles of carbon-free energy and energy savings are similar, while in the long run the importance of carbon-free energy deployment becomes predominant, independent of the assumed climate sensitivity, but dependent on some of our model's characteristic features. We also find that, in the absence of the realisation of drastic energy efficiencies or a massive deployment of carbon capture and storage technologies, non-carbon energy resources should provide 10–30% and 80–90% of total energy supply, in 2020 and 2100, respectively. Finally, we observe that in our model the timing of the emissions reduction effort is nearly linear and close to independent of either the climate sensitivity or policy target.     

Implications of process energy efficiency improvements for primary energy consumption and CO2 emissions at the national level

The improvement of energy efficiency is seen as one of the most promising measures for reducing global CO₂ emissions. However, the emission reduction potential may seem different from the industrial plant and policy-maker’s perspectives. This paper evaluates the influences of process heat conservation on CHP electricity production, primary energy consumption and CO₂ emissions from both the mill site and national perspectives. The results indicate that heat conservation in an industrial process may lead to varying results in primary energy consumption and CO₂ emissions, depending on the form of marginal heat production used at the mill site. In the CHP process, reduction of the heat load lowers electricity production, and this reduction may have to be compensated for at the national level. Therefore, the energy conservation potential in industry has to be evaluated by taking into account the connections to the outside society, which means that a wider system boundary than a mill site has to be used. This study demonstrates by theoretical analysis and case mill studies the magnitude of the effects of system boundary definition when evaluating the contribution of an individual energy efficiency investment towards fulfilling the commitment to reduce CO₂ emissions at the national level.     

Techno-economic assessment on the fuel flexibility of a commercial scale combined cycle gas turbine integrated with a CO2 capture plant

Post-combustion carbon capture is a valuable technology, capable of being deployed to meet global CO₂ emissions targets. The technology is mature and can be retrofitted easily with existing carbon emitting energy generation sources, such as natural gas combined cycles. This study investigates the effect of operating a natural gas combined cycle plant coupled with carbon capture and storage while using varying fuel compositions, with a strong focus on the influence of the CO₂ concentration in the fuel. The novelty of this study lies in exploring the technical and economic performance of the integrated system, whilst operating with different fuel compositions. The study reports the design of a natural gas combined cycle gas turbine and CO₂ capture plant (with 30 wt% monoethanolamine), which were modelled using the gCCS process modelling application. The fuel compositions analysed were varied, with focus on the CO₂ content increasing from 1% to 5%, 7.5% and 10%. The operation of the CO₂ capture plant is also investigated with focus on the CO₂ capture efficiency, specific reboiler duty and the flooding point. The economic analysis highlights the effect of the varying fuel compositions on the cost of electricity as well as the cost of CO₂ avoided. The study revealed that increased CO₂ concentrations in the fuel cause a decrease in the efficiency of the natural gas combined cycle gas turbine; however, rising the CO₂ concentration and flowrate of the flue gas improves the operation of the capture plant at the risk of an increase in the flooding velocity in the column. The economic analysis shows a slight increase in cost of electricity for fuels with higher CO₂ contents; however, the results also show a reduction in the cost of CO₂ avoided by larger margins.     

Introduction of subsidisation in nascent climate-friendly learning technologies and evaluation of its effectiveness

Given its importance as a practical phenomenon underlying the progress of learning technologies, attention should be paid to the role of subsidisation in learning theory, particularly in the case of nascent climate-related sociable learning technologies, in order to examine its benefits. Thus, this study focuses on subsidy procurement of energy technologies in several economies in the context of the component learning track in endogenous global clusters in order to suggest improvements to the adoption mechanism and examine the climate stabilization constraint. At the same time, the study attempts to determine the global progress ratio of the lithium-ion battery in order to analyse various endogenous learning scenarios for hybrid technologies. An integrated energy system model with highly disaggregated global regions (DNE21+) is used to execute this research in a medium time frame. Subsidisation of the learning track of battery technology encourages greater development of plug-in hybrid vehicles, promotes early diffusion of hybrid technologies, and relieves heavy dependency on crude oil and biofuels. The subsidies in the common learning domains in few economies benefit the nearby economies because of the technology spillover that occurs through numerous cross-feedback learning mechanisms. Endogenous learning with subsidies augments diffusion potentials, abates emissions, and shifts sectoral emissions.     

Bi-lateral CO2 emissions embodied in Australia–China trade

This paper quantifies the CO₂ emissions embodied in bi-lateral trade between Australia and China using a sectoral input–output model. The results revealed: (1) that China performs lower than Australia in clean technology in the primary, manufacturing, energy sectors due to their overuse of coal and inefficient sectoral production processes, and (2) that China had a 30.94 Mt surplus of bi-lateral CO₂ emissions in 2010–2011 and (3) overall global emissions were reduced by 20.19 Mt through Australia–China trade in 2010–2011. The result indicates that the greater the energy efficient a country among the trading partners the lower will be the overall global CO₂ emissions. Global emissions decreased mainly because China consumed Australian primary products rather than producing them. Australia is an energy efficient producer of primary products relative to China. The bilateral trade compositions and trade volume played an important role in lowering global emissions and therefore one can view proposed China Australia Free trade Agreement positively in reducing global emissions. However, for the sustainable development, China should strengthen clean energy use and both countries should adopt measures to create an emission trading scheme in order to avoid protectionism in the form of future border price adjustments.