Technological change in energy - TIAM-UCL: Difference between revisions

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TIAM-UCL includes exogenously determined through cost-reductions and efficiency improvements through the various different technolgies available, although learning by doing has also been used in specific studies. R&D expenditures are not explicitly considered.
TIAM-UCL represents technological change through exogenously determined cost-reductions and efficiency improvements for the various different technologies available, although learning curves have also been used in specific studies. However, R&D expenditures are not explicitly considered.


Technology vintages are full represented and explicit growth and decline constraints can be used to simulate the diffusion and phase out of technologies.
Technology vintages are fully represented and explicit growth and decline constraints can be used to simulate the diffusion and phase out of technologies.


Representation of inertias and path-dependencies, e.g. via capacity stocks, knowledges stocks (cf. technological change), constraints of the expansion and decline of technology deployment, and early retirements of fossil capacities are all included.
Representation of inertias and path-dependencies, e.g. via capacity stocks, knowledges stocks (cf. technological change), constraints of the expansion and decline of technology deployment, and early retirements of fossil capacities are all included.


Endogenous technological learning is possible but not when running the Climate Module
Endogenous technological learning is also possible.

Latest revision as of 18:51, 14 December 2016

Model Documentation - TIAM-UCL

Corresponding documentation
Previous versions
Model information
Model link
Institution University College London (UCL), UK, https://www.ucl.ac.uk.
Solution concept Partial equilibrium (price elastic demand)
Solution method Linear optimisation
Anticipation Perfect Foresight

(Stochastic and myopic runs are also possible)

TIAM-UCL represents technological change through exogenously determined cost-reductions and efficiency improvements for the various different technologies available, although learning curves have also been used in specific studies. However, R&D expenditures are not explicitly considered.

Technology vintages are fully represented and explicit growth and decline constraints can be used to simulate the diffusion and phase out of technologies.

Representation of inertias and path-dependencies, e.g. via capacity stocks, knowledges stocks (cf. technological change), constraints of the expansion and decline of technology deployment, and early retirements of fossil capacities are all included.

Endogenous technological learning is also possible.

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