Schilling:Outsourcing_book_temp.qxd 24/08/2009 11:41 Page 11
Plotting Renewables and Fossil Fuels on the Technology S-curve
values  against the cumulative R&D spending of the nine countries
Figure 2: Cumulative Historical Research and Development Funding of
listed previously. The results (shown in
Renewable Energies, Fossil Fuel Technologies and Nuclear Energy by
Figure 4) are illuminating.
Governments of Canada, Japan, The Netherlands, Norway, Spain,
Sweden, Switzerland, the UK and the US
The first important observation is that both wind energy and
geothermal energy have accrued far greater improvement per dollar
160,000
Nuclear energy
invested than concentrating solar (thermal solar captured through
Fossil fuels
140,000
concentrating mechanisms, such as curved mirrors) or photovoltaics. Total renewable
energies
The concentrating solar technology curve appears to have already 120,000
gone through one complete s-shaped cycle and is perhaps entering
100,000
another. Bear in mind that all of the cost data points are yearly data
between 1980 and 2005. Compression in points for concentrating
80,000
constant 2005 US$ millions
solar in the right side of the curve reflects the fact that R&D
60,000
investment in concentrating solar technology has slowed significantly.
40,000
This is consistent with the previous data shown on R&D investment.
Cumulative spend,
20,000
The photovoltaics curve appears to be at the very beginning of its
0
s-curve, showing a  much slower improvement rate than the other
1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
technologies. Even though significantly more has been spent on
photovoltaics than on the other renewables, it has thus far achieved Assuming that the performance improvement in renewable energy
much lower performance, at least in terms of kWh per dollar. technologies will approximate the Pearl curve most commonly used in
technology studies, it is possible to use regression to estimate the rate
Both wind energy and geothermal energy, on the other hand, show of improvement in the technologies and their ultimate performance
very steep s-curves, indicating rapidly increasing performance. Wind limits. For the wind energy data, a very good fit was achieved with a
energy shows the archetypal s-shape, suggesting that it may already limit of 50kWh per dollar (about 2.5 times the highest observed value),
be entering a period of slowing performance improvement. an intercept of 1.87 and a slope of 0.00069. The sum of squared
Geothermal energy shows exponential growth, achieving more kWh errors for the regression decreases as the limit decreases, which may
per dollar than the other three technologies and with no indication of suggest that the performance trajectory of wind is already flattening
slowing performance improvement. out. However, it is important to recognise that s-curves are not
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