Pathways To Low Carbon Power Generation Abatement Potential Towards 2020
DNV SERVING THE ENERGy INDUSTRyAbatement potential towards 2020Pathways to low-carbon coal-firedpower generation in Europethepoweroflowcarbonpowergeneration
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I pathways to low carbon power generation I ENERGy I 03CONTENTS04 Abatement potential towards 2020 07 What is a realistic reduction potential?04 How to read the abatement curves? 11 Conclusions05 The relevance to utility managersIn this Pathways to low-carbon coal-fired power generation in Europe, DNV analysesthe projected coal-fired power plant (CFPP) population in 2020 and the potential andcost of four major CO2 emission abatement measures. The baseline emission of thepopulation in 2010 is determined to be 830Mton. This corresponds to 17% of the totalCO2 emissions in Europe. Since nearly a third of the electricity in Europe is generated byCFPPs, this population covers a major fraction (64%) of the power sector’s greenhousegas emissions. The four measures have been investigated in order of cost-effectiveness,starting with the most cost-effective measure: combined heat and power, a shift fromsubcritical to supercritical units, biomass co-firing, and carbon capture and storage.The results of this study are presented in Marginal Abatement Cost Curves (MACC).These curves demonstrate that, by 2020, CO2 emissions from CFPPs can be reduced by7% below baseline at negative cost and by almost 13% if all four measures are fullyimplemented.the power of low carbon power generation
04 I ENERGy I pathways to low carbon power generation I abatement potential towards 2020 This study analyses the carbon dioxide emission reduction combustion technology or advanced boiler materials and potential in the year 2020 by introducing four major emis- performance, etc. sion reduction measures to the coal-fired power plant popu- lation in Europe. The population model includes units in countries with a share of electricity generated by coal that exceeds 20%. The Marginal abatement cost curves (MACC) have been devel- European countries with the largest contributions are oped based on DNV’s experience gained from energy effi- Germany, the UK, Spain and Poland. The IEA Clean Coal ciency studies, as well as on technology outlooks available in Centre Database  has been used as a basis for the base- literature , industry sources  and the DNV model for line population in 2010. In total, more than 76% of the low carbon shipping . installed electric CFPP capacity in Europe is produced in the selected countries, and the population database covers 79% Figure 1 illustrates the reduction potential achievable by of the capacity in these countries. The baseline emission of four emission reduction measures plotted against their the population in 2010 is determined to be 830Mton. This estimated cost-effectiveness for the coal-fired power plant corresponds to 17% of the total CO2 emission in Europe in population in Europe (see the box at the bottom of this 2010 . page “How to read the abatement curves?”). The measures included in the analysis are: combined heat and power DNV’s baseline scenario assumes a constant coal-fired elec- (CHP), a shift from subcritical to supercritical units tricity generation up to 2020 and predicts that the baseline (S2SC), biomass co-firing (BCF) and carbon capture emissions will be reduced to 767Mton. This baseline sce- and storage (CCS). nario is the situation in 2020 without implementing the proposed measures but incorporating the general improve- General improvements (GI) are also accounted for. These ments. In this scenario model, the construction of new units improvements include not only operations and control and decommissioning of old units are incorporated and optimisations and improvements in turbine technology, but determined on a yearly basis. also progress in material science which leads to improved How to reAd tHe AbAtement curves? The abatement curves illustrated in Figure 1 summarise the technical The marginal cost shown in Figure 1 is the average cost for all power opportunities to reduce emissions from the coal-fired power plant plant types and sizes. The graph is arranged from left to right, population in operation by 2020. The width of each bar represents showing the increasing cost per ton of CO2 averted. The effect of the the potential of that measure to reduce CO2 emissions from the remaining measures decreases as one measure is implemented, and population compared to a baseline scenario. The height of each bar the most cost-effective measures are implemented first. Where the represents the average marginal cost of avoiding 1 ton of CO2 bars cross the x-axis, the measures start to result in a net cost instead emissions through that measure, assuming that all measures to the of a net cost reduction. Future carbon cost is not included in the left are already applied. illustration (i.e. the carbon price is zero), but will in principle improve the cost-effectiveness of the measures.
I pathways to low carbon power generation I ENERGy I 05FIGure 1: Average marginal co 2 reduction per option - coal-fired power plants in Europe in 2020 Baseline: 767 million tons per year 100 75Cost per ton CO2 averted (€/ton) 50 25 BCF CCS 0 GI CHP S2SC -25 -50 0 10 20 30 40 50 60 70 80 90 100 CO2 reduction (million tons per year)tHe relevAnce to utIlIty mAnAGersThe model includes the majority of coal-fired power plants in results to be directly transferable to their own units or stations.Europe divided into a manageable set of segments. The resultspresented here show the emission reduction potential evaluated In the DNV models, individual CO2 reducing measures can befor characteristic (average) units within each segment. Detailed analysed and the effects and costs can be accurately assessedanalysis of individual units or stations within the same segment taking into account the specific details of each unit and itsmight result in different emission and cost curves depending on operational characteristics. The analysis presented here is primarilytechnical and operational aspects and taking into account designed to support decisions regarding policy and regulations. Itmeasures that may already have been implemented. Hence, utility also illustrates the overall sector dynamics and can serve asmanagers should read the results with care and not expect the guidance for portfolio management.
06 I ENERGy I pathways to low carbon power generation I In the DNV analysis, the population of coal-fired power Table 1 presents some of the main results highlighting the plants has been divided into 14 segments. These segments economic aspect. It shows the abatement cost levels neces- represent the major technology types, i.e. Pulverized Coal sary for ensuring a given emission reduction and the Combustion, Fluidized Bed Combustion, Integrated remaining emission level. Gasification Combined Cycles, as well as unit sizes. Examples are Pulverized Coal Combustion units larger than 600MWel Co-combustion of biomass or waste together with a base fuel or Fluidized Bed Combustion units between 100MWel and in a boiler is a simple way to replace fossil fuels with biomass 200MWel. A further differentiation into coal types (anthra- or to utilise waste. Figure 2 shows the abatement curve for cite, bituminous coal, sub-bituminous coal, lignite) and biomass co-firing. This curve illustrates that biomass co- steam conditions (subcritical, supercritical) has also been firing is considerably more expensive, especially for smaller incorporated. units, because of higher specific investment costs and increased operational and maintenance costs. Each of these segments has been modelled separately with regard to: An average biomass price of 65€/ton was used, but large ■■ fuel mix and fuel price variations in biomass price exist depending on type and ■■ the reduction potential of each measure location. The total marginal abatement potential for bio- ■■ the lifetime of each measure mass co-firing is 5.5Mton. Without policy support, biomass ■■ he utilisation rate of each measure, i.e. the percentage of co-firing is not recommended as a structural abatement units with the measure implemented measure, but it may be applied if inexpensive waste fuel is ■■ the cost of each measure (incl. additional investment available. Similar curves were developed for the other meas- costs and additional operational and maintenance costs) ures as well. ■■ the year when available measures are phased in Predicting future emissions involves significant uncertainty. This allows for an activity-based determination of the fuel A sensitivity analysis has been performed to determine the consumption and related carbon dioxide emissions. uncertainties in the model’s major input parameters. Important elements include uncertainty about the price and Some measures are available for implementation in existing emission reduction effect of measures, the rate of uptake of plants as retrofit solutions (e.g. biomass co-firing). Other new technologies and the population growth estimates. measures are available for new constructions only (e.g. a Best-case and worst-case scenarios have also been developed. shift from subcritical to supercritical units). The cost and reduction effect of the different measures can vary signifi- The main contributions to the uncertainty are caused by the cantly between segments. Not all measures are applicable to population growth estimates. Early retirement of old units every segment. For example, biomass co-firing is not applica- and replacement by new constructions will have a major ble to IGCC units. impact on the population’s CO2 emissions. The conclusions for the individual abatement measures were strengthened by The assumptions per measure regarding the emission reduc- the results of the sensitivity analysis. The ranking of the tion potential, cost and introduction schedule are based on abatement measures in terms of cost-effectiveness remained literature surveys and DNV’s research and sector expertise . unchanged in all scenarios. tAble 1 – Emission AbAtement emIssIon emIssIon cost level [€/tco2] reductIon [%] level [mton] reduction and emission level in baseline 0 767 2020 for specific 0 6.8 715 abatement cost levels 70 13 670
I pathways to low carbon power generation I ENERGy I 07 FIGure 2: Abatement curve for biomass co-firing 100 FBC >200MWe PC 0-50 MWe PC >600MWe PC 50-100 MWe FBC 100-200 MWe PFBC PC 100-150 MWe PC 400-500 MWeCost per ton CO2 averted (€/ton) PC 150-200 MWe PC 500-600 MWe PC 200-300 MWe 50 PC 300-400 MWe FBC 0-100 MWe 0 -50 0 1 2 3 4 5 CO2 reduction (million tons per year) wHAt Is A reAlIstIc reductIon potentIAl? This study has estimated the potential reduction in CO2 emissions is adopted and the rate of uptake of new technology are important from the coal-fired power plant population in Europe when a set of criteria. One crucial factor for achieving large reductions fast is the abatement measures is implemented. The aim has been to identify widespread use of technology as soon as it becomes available. the maximum technically obtainable emission reduction in 2020. Enforcement through regulatory means is necessary to ensure full Where emission reduction and sound economic rationale pull in the implementation when one cannot wait for the economic pull to same direction, the widespread implementation of cost-effective work. In this study, DNV has pointed out the costs of meeting measures will occur over time. The rate at which existing technology specific emission reduction targets.
8 I ENERGy I pathways to low carbon power generation IArtist’s impression of a Carbon Capture and Storage power plant
I pathways to low carbon power generation I ENERGy I 9conclusionsThe results of this study illustrate what can be achieved ■■ Combined heat and power is interesting when applicablewhen four measures are applied to Europe’s population of and can be achieved at negative cost for all segments.coal-fired power plants. The conclusion is that the popula- Local heat demand has to be seriously considered whention has the potential to reduce its CO2 emissions in 2020 by investigating suitable locations for new construction.7% below baseline at negative cost and by almost 13% if the ■■ A shift from subcritical to supercritical units has thefour abatement measures are fully implemented. This cor- largest abatement potential and can be achieved at nega-responds to a total reduction potential of 104Mton CO2 tive cost for all segments.(including the general improvements). Note that the CO2 price is set at zero. Including carbonDNV believes that the most important measures currently prices will result in a lower cost per ton abated and thusknown have been included. The main conclusions regarding increase the reduction potential achievable at negative cost.these measures are as follows: Predicting future emissions involves significant uncertainty.■■ Carbon capture and storage has a great potential for Important elements include uncertainty about the price reducing CO2 emissions but at a considerable cost (the and effect of measures, the rate at which existing technol- highest cost of all the measures considered). ogy will be adopted, the rate of uptake of new technologies,■■ Biomass co-firing is expensive and cannot be recom- population growth and unit decommissioning estimates. mended as a structural solution for the sector. However, However, a sensitivity study confirmed the conclusions when it may be an option if sources of inexpensive (waste) reasonable uncertainties in the input parameters were bio-fuel are available and it is aided by subsidy mecha- taken into account. nisms (e.g. green certificates) and specific market instru- ments (e.g. carbon credits).reFerences/Footnotes: For instance: IEA Energy Technology Perspectives 2010, Scenarios  IEA Clean Coal Centre Coal Power Database: http://www.iea-& Strategies to 2050, July 2010. coal.org.uk DNV Technical Report, Marginal abatement cost curves for  EU energy trends to 2030 – update 2009, Europeancoal-fired power plants in the EU – CO2 reduction potential for Commission, Directorate-General for Energy, 2010,2020, Report nr. 2010-9454. doi:10.2833/21664. Pathways to low carbon shipping. Abatement potential towards2030, February 2010. http://www.dnv.com
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