Global experience curves for wind farms

Junginger, Martin; Faaij, André; Turkenburg, Wim

doi:10.1016/s0301-4215(03)00205-2

Cited by 289 publications

(193 citation statements)

References 14 publications

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“…The majority of technological learning studies to date attribute deployment and innovation as isolated policies to expand and plan for future cost reductions [8][9][10] . However, we also know there are synergies between deployment and innovation where we can capitalize and strategically target public spending to benefit society 11 .…”

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confidence: 99%

Energy storage deployment and innovation for the clean energy transition

2017

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The clean energy transition requires a co-evolution of innovation, investment, and deployment strategies for emerging energy storage technologies. A deeply decarbonized energy system research platform needs materials science advances in battery technology to overcome the intermittency challenges of wind and solar electricity. Simultaneously, policies designed to build market growth and innovation in battery storage may complement cost reductions across a suite of clean energy technologies. Further integration of R&D and deployment of new storage technologies paves a clear route toward cost-e ective low-carbon electricity. Here we analyse deployment and innovation using a two-factor model that integrates the value of investment in materials innovation and technology deployment over time from an empirical dataset covering battery storage technology. Complementary advances in battery storage are of utmost importance to decarbonization alongside improvements in renewable electricity sources. We find and chart a viable path to dispatchable US$1 W −1 solar with US$100 kWh −1 battery storage that enables combinations of solar, wind, and storage to compete directly with fossil-based electricity options.

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confidence: 99%

Energy storage deployment and innovation for the clean energy transition

2017

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“…In more recent studies [45] it is argued that the simulation of interest rates may contribute to the elimination of arbitrary risk premium assumptions, mainly within the framework of real-options models. The capital costs may decrease over time due to the global experience on similar projects, introducing further time-dependent characteristics in the analysis of energy investments [21,46,47].…”

Section: Time Dependent Investments Under Uncertaintymentioning

confidence: 99%

An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios

Tolis

Rentizelas

2011

Applied Energy

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This version is available at https://strathprints.strath.ac.uk/44919/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. AbstractThe present work concerns a systematic investigation of power sector portfolios through discrete scenarios of electricity and CO2 allowance prices. The analysis is performed for different prices, from regulated to completely deregulated markets, thus representing different electricity market policies. The modelling approach is based on a stochastic programming algorithm without recourse, used for the optimisation of power sector economics under multiple uncertainties. A sequential quadratic programming routine is applied for the entire investigation period whilst the time-dependent objective function is subject to various social and production constraints, usually confronted in power sectors. The analysis indicated the optimal capacity additions that should be annually ordered from each competitive technology in order to substantially improve both the economy and the sustainability of the system. It is confirmed that higher electricity prices lead to higher financial yields of power production, irrespective of the CO2 allowance price level.Moreover, by following the proposed licensing planning, a medium-term reduction of CO2 emissions per MWh by 30% might be possible. Interestingly, the combination of electricity prices subsidisation with high CO2 allowance prices may provide favourable conditions for investors willing to engage on renewable energy markets.

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“…Beyond the turbines in a wind farm (typically, 65%-85% of total costs of a wind farm are based on turbine costs [14]), the investment cost of a wind farm is also subject to experience curve effects, but there are many other site specific considerations. A wind farm would necessarily consist of foundations, grid connection, project management, etc., all of which have some characteristics of fixed costs that are spread among increased generation capacity.…”

Section: Manufactured Technologymentioning

confidence: 99%

Renewable Energy Technology—Is It a Manufactured Technology or an Information Technology?

Shum

2010

Sustainability

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Socio-technical or strategic approach to renewable energy deployment all suggests that the uptake of renewable energy technology such as solar photovoltaic is as much a social issue as a technical issue. Among social issues, one most direct and immediate component is the cost of the renewable energy technology. Because renewable electricity provides no new functionality-a clean electron does the same work as a dirty electron does-but is relatively expensive compared with fossil fuel based electricity, there is currently an under-supply of renewable electricity. Policy instruments based on economics approaches are therefore developed to encourage the production and consumption of renewable electricity, aiming to remediate the market inefficiencies that stem from the failure in internalizing the environmental or social costs of fossil fuels. In this vein, the most discussed instruments are renewable portfolio standard or quota based system and the general category of feed-in tariff. Feed-in tariff is to support output or generation of the renewable electricity by subsidizing revenues. The existing discussions have all concerned about the relative effectiveness of these two instruments in terms of cost, prices and implementation efficiency. This paper attempts a different basis of evaluation of these two instruments in terms of cost and (network) externality effects. The cost effect is driven by deploying the renewable as a manufactured technology, and the network externality effect is driven by deploying the renewable as an information technology. The deployment instruments are studied in terms of how these two effects are leveraged in the deployment process. Our formulation lends itself to evolutionary policy interpretation. Future research directions associated with this new energy policy framework is then suggested. OPEN ACCESSSustainability 2010, 2 2383

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Global experience curves for wind farms

Cited by 289 publications

References 14 publications

Energy storage deployment and innovation for the clean energy transition

Energy storage deployment and innovation for the clean energy transition

An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios

Renewable Energy Technology—Is It a Manufactured Technology or an Information Technology?

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