Environmental Engineering Reference
In-Depth Information
declined and peaked at a higher level in 2009. According to OECD [
57
], public
spending in renewable energy RD&D in OECD countries represented in 2007, 25 %
of total public energy technology RD&D and was at the same level than in 2000.
The bulk of public R&D expenditures in renewables in IEA countries is cur-
rently dedicated to solar PV (about 35 %, 542 million USD in 2010) and wind
(about 30 %, 424 million USD) [
56
]. Expenditures on CSP, ocean, geothermal,
hydro and bioenergy are very similar (in the range of 101
130 million USD each)
[
56
]. These R&D expenditures are clearly lower (in fact, a very small fraction) than
expenditures on deployment, i.e., compare those
-
gures with the US$ 66 billion of
global subsidies to renewable power world-wide [
58
].
12
2.5.2 The Reply
Some economists are skeptical about the existence of a deployment externality and,
thus, they only justify a carbon price and R&D support and are critical direct
deployment support (see, e.g., [
37
,
60
]). However, R&D spending without the
acquisition of experience through deployment that involves learning will make the
technology harder to implement on a wide scale [
61
].
While it is obvious that a combination of deployment and R&D is needed, the
question remains as to the appropriate balance between the two. This certainly
depends on the level of maturity of the technologies, i.e., it is a technology-speci
c
issue. In general, for immature technologies, cost reductions and technology
improvements are more closely related to R&D investments and R&D support. In
contrast, improvements in the technology and cost reductions achieved in the
laboratory are limited for mature technologies. But, to the best of our knowledge,
there is no study indicating the optimal share of funds that should be dedicated to
either R&D support or deployment support in order to encourage the greatest
technology cost reductions per
of support. Further research should clarify, for
each technology, what the balance should be.
In addition, both deployment and R&D have been treated as if they were isolated
from each other when in reality they interact in complex ways. There are positive
feedbacks between the two. RD&D lead to cost reductions, make the technologies
more attractive for potential adopters, encourage diffusion and, thus, reinforces
advancements of technologies along their learning curves [
53
,
62
]. Learning effects
as a result of deployment reduce costs and promote diffusion, leading to more
dynamic markets for renewable energy technologies. In turn, market creation makes
RD&D investments in those technologies more attractive.
13
€
Indeed, empirical
12
For example, public R&D support for renewable energy technologies in Spain was 6.8 M
€
for
solar PV and 6.3 M
€
for wind in 2009, whereas net deployment support for these technologies
reached 2629 M
€
for solar PV and 1619 M
€
for wind [
60
].
13
derholm [
64
] note that if production costs
fall, the potential competitiveness of the technology increases, increasing also the return on
additional private RD&D efforts. This will induce more RD&D expenses on the part of private
For example, Gillingham et al. [
63
] and Ek and S
ö
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