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Title:
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Learning from the Sun; Analysis of the use of experience curves for energy policy purposes: The case of photovoltaic power. Final report of the Photex project
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Author(s):
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Schaeffer, G.J.; Seebregts, A.J.; Beurskens, L.W.M.; Moor, H.H.C. de; Alsema, E.A.; Sark, W.G.J.H.M. van; Durstewitz, M.; Perrin, M.; Boulanger, P.; Laukamp, H.; Zuccaro, C.
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Published by:
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Publication date:
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ECN
Energy in the Built Environment
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1-8-2004
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ECN report number:
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Document type:
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ECN-C--04-035
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ECN publication
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Number of pages:
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Full text:
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99
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Download PDF
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Abstract:
Since the 1990s energy policy scientists have started to explore the
possibilities of using the experience curve approach for energy policy
making. The concept of the experience curve is simple, at least in principle.
It states that, for every doubling of cumulative produced capacity of
a product or technology, the cost for making it declines with a fixed
percentage (learning rate). Historical statistical analysis can be used
to define this percentage. Extrapolating the trend thus found, into
the future will then give relevant information about future cost developments
and will also give information how much ?learning money? will be needed
to get to the break-even point. The Photex project used the development
of solar PV as a case to further explore this approach, and also to
deduce lessons for PV policy. Other aims were to look at learning rates
of the different components of PV-systems and to combine the experience
curve analyses with bottom-up engineering studies. The main conclusion
with regard to the use of experience curves for energy policy making
is that this is an interesting approach, but that such an analysis should
be done with much care. For the historical analysis the availability
of reliable and firm data is essential. As cost data often are not available,
price data could be used as a proxy, as long as sufficient long time
ranges are used. Also, the analyst should take care he considers the
right learning system boundaries. Furthermore the number of years to
be included in the statistical analysis should at least be 10 years
and this period sample should not over-represent stable price periods
or periods of steep price decline. If possible, data uncertainties should
be taken into account as well. An interesting finding was that, at least
in the case of PV, the learning rate is not a constant, but can vary
over time. In the case of PV it improved from 20% to 23%. Extrapolations
into the future should take uncertainties into account and always be
done scenario-wise. Doing this for grid-connected PV, the analysis shows
that self-sustaining markets could be expected in Europe at specific
locations before 2010. Reaching break-even for the wholesale electricity
market will most probably not happen before 2030. To reach break-even
within a reasonable time-frame, the market deployment growth rate should
be at least 15%-20% over the next coming decades, assuming that the
learning rate remains at the current 20%-25%.
Because the learning rate is not fixed, it might be possible to influence
it by a right combination of market deployment policy (learning investment)
and R&D-policy supporting the market development (investment in
learning). An experience curve analysis can contribute interesting information
to policy discussions on the balance between market support and R&D.
In the case of PV it seems that a substantially increased support for
learning processes, such as R&D, and interactive learning networks
within and between users, producers and component suppliers, which supports
current and future market deployment instruments, can yield a huge public
benefit in the longer term. Furthermore the experience curve approach
shows that from a European perspective the cost-effectiveness of PV-
policy could be improved. This effectiveness could be reached if a European-wide
market-based incentive scheme were implemented. As cost-effectiveness
is just one policy goal among many others, such a European market-based
deployment instrument should not exclude additional Member State PV
deployment policies.
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