By Martin Junginger, Wilfried van Sark, Andre Faaij
Technological studying is a key driving force in the back of the development of strength applied sciences and next relief of construction bills. realizing how and why creation expenses for strength applied sciences decline, and whether or not they will proceed to take action sooner or later, is of an important significance for coverage makers, commercial stakeholders and scientists alike. This well timed and informative ebook for this reason offers a finished assessment of technological improvement and value discounts for renewable strength, fresh fossil gasoline and energy-efficient demand-side applied sciences. It responds to the necessity for a quality-controlled info set of expertise curves, together with evaluation of dimension technique, technological wisdom and linked rate. The specialist members current a radical review and dialogue of the pitfalls of utilising the adventure curve process, together with facets resembling geographical process barriers, even if the slope of the adventure curves is continuing or now not, statistical errors and sensitivity research of expertise curves, and even if the adventure curve procedure can be used to quantify advancements in strength potency. a transparent set of options for using the event curve technique is usually prescribed. offering an important contribution to the present literature on power and weather types, state of affairs research, and methodological classes on adventure curves, this ebook will strongly attract teachers and scholars within the parts concentrating on power and public quarter economics. coverage makers in those fields also will locate the ebook to be of serious curiosity.
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Extra resources for Technological Learning in the Energy Sector: Lessons for Policy, Industry and Science
With historical annual growth rates of 15 per cent (as assessed in 1997), photovoltaic modules would reach break-even point around the year 2025. Doubling the rate of growth (as was the case between 1997–2007) would move the break-even point 10 years earlier, to 2015. To achieve this increased rate of growth, additional subsidies are needed for continuing the ride down the experience curve and to bring prices to the break-even point. The application for policy makers is basically twofold. First of all, experience curves can serve as a monitoring tool.
3 shows the trend in learning rates for wind power over time. 0025 per year. In this case the dispersion in values decreases over time. 3 Extension of the One-Factor Experience Curve In the conventional one-factor experience curve (OFEC), unitary cost reduction is only explained by the cumulative production doubling. As the experience curve itself only describes the empirically observed trend without opening the ‘black box’ of underlying mechanisms, a crucial General aspects and caveats of experience curve analysis 25 question for many policy makers is whether an estimated PR could be actively influenced by policy measures.
This has become known as the ‘two-factor learning curve’ approach (see also Chapter 3 and Chapter 5). g. Grübler, 1998 and Wene in IEA, 2000). They first started to relate learning rates to the different ‘stages of technology’ (from invention and R&D via demonstration and niche-market commercialization, to full commercialization, saturation and decline), but already acknowledged that these stages often display significant overlap and are difficult to separate. 1 (see, for example, IEA, 2000). 1 Influences on the learning system from public policy Many researchers also paid explicit attention to learning processes in the other stages of technological developments.