Response from a MARKAL technology model to the EMF scenario assumptions
Introduction
Energy system models have acquired over time the capability to analyse environmental issues besides technological changes. Especially technology-rich models can provide interesting insights on future developments and deployments in the energy sector when the system is subjected to additional (external) constraints. Over time, especially after the Rio and Kyoto conferences, these constraints concern environmental aspects of the economic system, or the energy system in particular. Since then, several persons and teams at ECN Policy Studies have been working on the environmental impacts and consequences of climate policies on energy systems. To analyse these effects, long-term models are developed and used. Results of the recent studies can be found in Ybema and Kram (1997), Lako and Ybema (1997), Lako et al. (1998) Lako and Seebregts (1998), Seebregts et al., 2000, Seebregts et al., 2001, Gielen et al. (2000), Jansen et al. (2001) and Sijm et al. (2002).
Section snippets
MARKAL
The model used is a MARKAL model, a bottom-up-technology-based linear optimisation model. MARKAL, in its standard form, is a linear programming optimisation model that identifies the least-cost combinations of technological processes and improvement options that satisfy a specified level of demand for goods and services under certain policy constraints, notably the achievement of certain specified GHG reduction objectives, in a way that the overall system costs are minimised over all time
The scenarios
A number of scenarios and sensitivity cases have been run for EMF-19 to explore the technology response to different CO2 constraints:
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a modellers' reference;
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a standardised reference according to IPCC B2 scenario;
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a 550 ppmv stabilisation case;
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a 550 ppmv with an 50% increase and decrease in sequestration cost assumptions;
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a US$10 per decade carbon tax, starting from 2010 on;
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a US$10 per decade carbon tax from 2010 onwards with a 50% increase and decrease in sequestration cost assumptions;
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a US$25 per
Primary and final energy
Fig. 5 shows for each of the scenarios the primary energy mix for the years 2020, 2050 and 2100. As can be noticed, the total level of primary energy demand does not change much (between −6% and +2%, with the exception of the standardised reference which uses lower demand levels). Even so, the energy mix changes considerably between the scenarios. In 2020, the solid and liquid fossil fuels decline already somewhat in the 550 ppmv and the high tax (US$25–100) cases compared to the modellers'
Conclusions
Analysis with ECN's MARKAL Western European technology model shows that under carbon emission constraint scenarios, not only renewable energy but also carbon capture and removal are important actors in achieving carbon emission reduction objectives. Renewables, especially wind and solar, are important in the power sector, but nonrenewable technologies, especially nuclear and gas fuelled are also important. Biomass-based technologies remain limited because of the strong competition with
References (10)
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- Jansen, J.C., Gielen, D.J., Smekens, K.E.L., Chen C., 2001. Energy and environmental policy analysis: Shanghai Case...
- Lako P., Seebregts A. J., 1998. Characteristics of power generation options for the 21st century (Petten, Netherlands)....
- Lako, P., Ybema J.R., 1997. CO2 abatement in Western European power generation. Report ECN-C-97-053, Petten. The...
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2011, International Journal of Greenhouse Gas ControlCitation Excerpt :MARKAL and TIMES are integrated energy systems modelling platforms that can be tailored to analyze energy, economic and environmental issues at the global, national and municipal level over several decades. These modelling platforms are currently used by over 100 modelling teams worldwide and have been heavily utilized for analytical insights for energy policy (e.g., Loulou et al., 2009; Strachan et al., 2009; Chen, 2005; Smekens, 2004). MARKAL and TIMES are partial economic equilibrium models formulated as linear optimization problems (Loulou et al., 2004).