Technical learning: Difference between revisions
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Often ρ is expressed by the progress ratio P, which indicates how fast the costs metric, Y, decreases with the doubling of Q (P=2<sup>-ρ</sup>). Progress ratios reported in empirical studies lie mostly between 0.65 and 0.95, with a median value of 0.82 (Argotte and Epple, 1990). In the TIMER model, 'learning by doing' influences the capital output ratio of coal, oil and gas production, the specific investment cost of renewable and nuclear energy, the cost of hydrogen technologies, and the rate at which the energy conservation cost curves decline. The actual values used depend on the technologies and the scenario setting. The p for solar/wind and bio-energy has been set at a lower level than for fossil-based technologies, based on their early stage of development and observed historical trends (Wene, 2000). There is evidence that, in the early stages of development, p is higher than for those technologies that have already been in use for long periods of time. For instance, values for solar energy have typically been below 0.8, while those for fossil-fuel production were around 0.9 to 0.95. For technologies in early stages of development, other factors may also contribute to technology progress, such as relatively high investments in research and development (Wene, 2000). In TIMER, we postulate the existence of a single global learning curve. Regions are then assumed to pool knowledge and 'learn' together, or, depending on the scenario assumptions, to be (partly) excluded from this pool. In the last case, only the smaller cumulated production within that region itself would drive the learning process and costs will decline at a slower rate. | Often ρ is expressed by the progress ratio P, which indicates how fast the costs metric, Y, decreases with the doubling of Q (P=2<sup>-ρ</sup>). Progress ratios reported in empirical studies lie mostly between 0.65 and 0.95, with a median value of 0.82 (Argotte and Epple, 1990). In the TIMER model, 'learning by doing' influences the capital output ratio of coal, oil and gas production, the specific investment cost of renewable and nuclear energy, the cost of hydrogen technologies, and the rate at which the energy conservation cost curves decline. The actual values used depend on the technologies and the scenario setting. The p for solar/wind and bio-energy has been set at a lower level than for fossil-based technologies, based on their early stage of development and observed historical trends (Wene, 2000). There is evidence that, in the early stages of development, p is higher than for those technologies that have already been in use for long periods of time. For instance, values for solar energy have typically been below 0.8, while those for fossil-fuel production were around 0.9 to 0.95. For technologies in early stages of development, other factors may also contribute to technology progress, such as relatively high investments in research and development (Wene, 2000). In TIMER, we postulate the existence of a single global learning curve. Regions are then assumed to pool knowledge and 'learn' together, or, depending on the scenario assumptions, to be (partly) excluded from this pool. In the last case, only the smaller cumulated production within that region itself would drive the learning process and costs will decline at a slower rate. | ||
|BelongsTo=Energy supply and demand; | |BelongsTo=Energy supply and demand; | ||
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