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

被引:127
|
作者
Rafaj, Peter [1 ]
Kypreos, Socrates [1 ]
机构
[1] Paul Scherrer Inst, Gen Energy Dept, Energy Econ Modelling Grp, CH-5232 Villigen, Switzerland
关键词
external cost; technology learning; air pollution; carbon capture; total generation cost;
D O I
10.1016/j.enpol.2006.03.003
中图分类号
F [经济];
学科分类号
02 ;
摘要
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, NOx) 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, NOx 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. (c) 2006 Elsevier Ltd. All rights reserved.
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页码:828 / 843
页数:16
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