Policies for the Energy Technology Innovation System (ETIS)

Grübler, Arnulf; Aguayo, Francisco; Gallagher, Kelly Sims; Hekkert, Marko P.; Jiang, Kejun; Mytelka, Lynn K.; Neij, Lena; Nemet, Gregory F.; Wilson, Charlie; Andersen, Per Dannemand; Clarke, Leon; Anadón, Laura Díaz; Fuss, Sabine; Jakob, Martin; Kammen, Daniel M.; Kempener, Ruud; Kimura, Osamu; Kiss, Bernadett; O’Rourke, Anastasia; Shock, Robert N.; Sousa, Paulo Teixeirade

doi:10.1017/cbo9780511793677.030

Cited by 55 publications

(59 citation statements)

References 133 publications

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“…However, some authors have pointed towards the apparent limits of exploiting economies of unit scale in coal power plants [56,57]. Supercritical coal power plants, which-according to the literature cited above-exhibit larger potential for economies of unit scale compared to subcritical coal power plants have experienced problems in regard to operating reliability due to their high technological complexity.…”

Section: Upsizing (Economies Of Unit Scale)mentioning

confidence: 99%

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A Review of Factors Influencing the Cost Development of Electricity Generation Technologies

Samadi

2016

Energies

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This article reviews the literature on the past cost dynamics of various renewable, fossil fuel and nuclear electricity generation technologies. It identifies 10 different factors which have played key roles in influencing past cost developments according to the literature. These 10 factors are: deployment-induced learning, research, development and demonstration (RD&D)-induced learning, knowledge spillovers from other technologies, upsizing, economies of manufacturing scale, economies of project scale, changes in material and labour costs, changes in fuel costs, regulatory changes, and limits to the availability of suitable sites. The article summarises the relevant literature findings for each of these 10 factors and provides an overview indicating which factors have impacted on which generation technologies. The article also discusses the insights gained from the review for a better understanding of possible future cost developments of electricity generation technologies. Finally, future research needs, which may support a better understanding of past and future cost developments, are identified.

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Section: Upsizing (Economies Of Unit Scale)mentioning

confidence: 99%

“…Quantifying inter-industry spillover effects is very difficult, as knowledge is highly heterogeneous and unobservable [57]. Therefore, an attempt is usually made in empirical analysis to capture inter-industry spillover effects by including a simple time trend in regression models.…”

Section: Knowledge Spillovers From Other Technologiesmentioning

confidence: 99%

A Review of Factors Influencing the Cost Development of Electricity Generation Technologies

Samadi

2016

Energies

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“…Innovation studies make clear that the drivers and mechanisms of -in this case -up-scaling will vary as a function of institutional, infrastructural, and other differences between innovation systems at different scales (Edquist and Johnson, 1997;Jacobsson and Lauber, 2006). Local knowledge and institutions are needed to develop, manufacture (or import), adapt, install, and above all, use a new energy technology effectively (Grubler et al, 2012).…”

Section: Generalitymentioning

confidence: 99%

Up-scaling, formative phases, and learning in the historical diffusion of energy technologies

2012

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a b s t r a c tThe 20th century has witnessed wholesale transformation in the energy system marked by the pervasive diffusion of both energy supply and end-use technologies. Just as whole industries have grown, so too have unit sizes or capacities. Analysed in combination, these unit level and industry level growth patterns reveal some consistencies across very different energy technologies. First, the upscaling or increase in unit size of an energy technology comes after an often prolonged period of experimentation with many smaller-scale units. Second, the peak growth phase of an industry can lag these increases in unit size by up to 20 years. Third, the rate and timing of up-scaling at the unit level is subject to countervailing influences of scale economies and heterogeneous market demand. These observed patterns have important implications for experience curve analyses based on time series data covering the up-scaling phases of energy technologies, as these are likely to conflate industry level learning effects with unit level scale effects. The historical diffusion of energy technologies also suggests that low carbon technology policies pushing for significant jumps in unit size before a 'formative phase' of experimentation with smaller-scale units are risky.

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“…It involves networks of actors (e.g., firms, users, universities), acting within a particular context of institutions and policies that influence knowledge production, technological development, adoption behavior and performance, bringing new products, processes and organization structures into economic use (Jacobsson andBergek, 2012, Carlsson andStankiewicz, 1991). In this paper, we draw on the Technological Innovation Systems (TIS) perspective, considering that it provides an adequate framework to addresses the interactive nature of the process of emergence and growth of new energy innovation systems (Jacobsson and Bergek, 2012, Carlsson and Stankiewicz, 1991Markard et al, 2012;Grubler et al, 2012). This approach considers that the technology development process takes place within a particular innovation system whose main components are actors, institutions and networks (Jacobsson and Johnson, 2000) and addresses the institutional and organizational changes that are needed to for these processes to successfully unfold (Markard et al, 2012).…”

Section: Conceptual Backgroundmentioning

confidence: 99%

“…But despite the existence of a large number of empirical studies (Bonaccorsi and Thoma, 2007), discussion remains on the relative role of science--based R&D and experience--based learning in innovation processes. This issue has namely been raised in the case of the emergence and diffusion of renewable energy technologies (Wilson et al, 2013;Hendry and Harbone, 2011;Nemet, 2009;Grubb, 2004). The objective of this paper is to contribute to this debate, by investigating the relation between the dynamics of knowledge production and technology diffusion along the process of emergence and development of a new energy innovation system, focusing on the case of wind energy.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of knowledge production and technology diffusion: Insights from the emergence of wind energy

Sousa¹,

Bento²,

Fontes³

2014

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The objective of this paper is to contribute to a better understanding of the relation between the dynamics of knowledge production and technology diffusion along the process of emergence of a new technology, as it unfolds in diverse spatial locations. For this purpose, the paper traces the process of knowledge production over time -expressed in the number of scientific publications --and assesses how its dynamics relate with those of technology up--scaling and diffusion, for the case of a new renewable energy technology: wind power. It also compares these processes in different spatial areas, looking at similarities and differences in the evolving patterns in initial markets and follower regions. In order to trace the dynamics of knowledge production we conduct a bibliometric analysis, using data collected from the Thomson Reuters Web of Science database (for the period 1970--2012). In order to trace the diffusion dynamics we use data collected on both unit scale of turbines and installed capacity of wind power (starting in late 1970s), following the empirical scaling methodology. These analyses are conducted at global scale and, subsequently, at a regional scale, for a pioneer (Denmark) and a fast follower (Portugal). The comparison of the outcomes from the bibliometric and the technology growth analyses permits to understand the rhythm and order in which knowledge was created and applied in this particular innovation. It also provides a preliminary account of the interplay between pioneer and fast follower regions.

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Policies for the Energy Technology Innovation System (ETIS)

Cited by 55 publications

References 133 publications

A Review of Factors Influencing the Cost Development of Electricity Generation Technologies

A Review of Factors Influencing the Cost Development of Electricity Generation Technologies

Up-scaling, formative phases, and learning in the historical diffusion of energy technologies

Dynamics of knowledge production and technology diffusion: Insights from the emergence of wind energy

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