The experience curve theory and its application in the field of electricity generation technologies – A literature review

Samadi, Sascha

doi:10.1016/j.rser.2017.08.077

Cited by 100 publications

(101 citation statements)

References 107 publications

(184 reference statements)

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“…The learning curve concept originates from a study by Wright [8]. Since then, many studies have been conducted to develop the learning curve method for analyzing the relationships between cumulative production and production cost [9][10][11][12][13][14][15][16][17][18][19][20][21]. This study suggests a new application of the learning curve with a presentation of previous models; the variables used within the models are summarized in Table 1.…”

Section: Learning Curve Methodsmentioning

confidence: 99%

“…There have been many applications of the learning curve method in analyzing the technological development of the energy industry. Samadi [16] examined and compared the learning rate of electricity generation technologies using a number of previous studies. Hong et al [17] calculated the learning rate for photovoltaic power generation in Korea using a two-factor model based on cumulative production and cumulative investment and production costs.…”

Section: Introductionmentioning

confidence: 99%

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Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources

Kim

Lee

2018

Sustainability

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Since 2007, shale oil and gas production in the United States has become a significant portion of the global fossil fuel market. The main cause for the increase in production of shale oil and gas in the US is the adoption of new production technologies, namely, horizontal drilling and hydraulic fracturing. However, the production cost of shale oil and gas in the US is comparably higher than the production cost of conventional oil and gas. In 2014, the crude oil and natural gas price decreased significantly to approximately 40 dollars per barrel, and natural gas prices decreased to 3 dollars per million British thermal unit, and thus the productivity and financial conditions for the exploration and production of shale oil and natural gas for producers in the United States have worsened critically. Therefore, technological innovation has become one of the most interesting issues of the energy industry. The present study analyzes the trends in technological innovation having a relationship with production activities. This study calculates the learning rate of 30 companies from the petroleum exploration and production industry in the United States using an improved learning rate calculation formula that reflects the changes in the oil production ratio. Thus, more statistically confident calculation results and interpretations of strategic production activities with regard to changes in the industrial environment were achieved in this study.

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Section: Learning Curve Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources

Kim

Lee

2018

Sustainability

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“…Additionally, there is no inherent reason that future costs should fall at the same learning rate as in the past (Arrow 1962;Ferioli et al 2009). Moreover, the use of learning rates to understand wind costs has primarily focused on understanding trends in CapEx (Wiser et al 2011;Lindman and Söderholm 2012;Rubin et al 2015;Samadi 2018). Wiser et al (2016) and Williams et al (2017), however, argue that applying learning rates to wind LCOE is more appropriate, because LCOE has been the principal criterion for assessing industry progress and technological advancements, and because reducing CapEx is only one way to reduce wind's LCOE.…”

Section: Estimating Future Opex For Land-based Windmentioning

confidence: 99%

“…Notwithstanding the criticisms, the application of learning rates to wind energy remains common (Wiser et al 2011;Lindman and Söderholm 2012;Rubin et al 2015;Samadi 2018), and represents a useful, simple means of estimating future wind costs or reinforcing estimates derived through other methods. Recent analyses suggest historical global learning rates of 6%-9% for land-based wind CapEx, meaning the CapEx has declined by 6%-9% for each doubling of cumulative global installed wind capacity (IRENA 2018;Wiser et al 2016).…”

Section: Estimating Future Opex For Land-based Windmentioning

confidence: 99%

“…More specifically, extensive literature on land-based wind CapEx has tracked trends over time and across countries (IRENA 2018;Wiser and Bolinger 2018;IEA Wind 2018), established data-driven costreduction trajectories based on learning curves (Wiser et al 2011;Lindman and Söderholm 2012;Rubin et al 2015;Samadi 2018), and developed engineering models to understand past and possible future cost-reduction options (Sieros et al 2012). A growing literature also emphasizes improvements in wind project performance, especially as turbine rotor diameters and hub heights have increased (IRENA 2018;Wiser and Bolinger 2018).…”

Section: Introductionmentioning

confidence: 99%

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Benchmarking Wind Power Operating Costs in the United States: Results from a Survey of Wind Industry Experts

Wiser

Bolinger

Lantz

2019

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This paper draws on a survey of wind industry professionals to clarify trends in the operational expenditures (OpEx) of U.S. land-based wind power plants. The paper also highlights key drivers of those trends. We find that average all-in lifetime OpEx has declined from approximately $80/kW-yr (~$35/MWh) for projects built in the late 1990s to a level that is approaching $40/kW-yr (~$11/MWh) for projects under construction in 2018. Turbine operations and maintenance (O&M) costs-inclusive of scheduled and unscheduled maintenance-represent the single largest component of overall OpEx and the primary source of cost reductions over the last decade. We observe wide ranges of OpEx over time; for example, survey respondents cite a range in average expected costs for projects commissioned between 2015 and 2018 from $33/kW-yr to $59/kW-yr. Notably, these broad ranges include high levels of variability in both turbine O&M costs and non-turbine OpEx. Potential technical and strategic drivers of this variability are highlighted. We also use historical OpEx learning rates, showing a 9% OpEx reduction for each doubling of global installed wind capacity, to project a further $5-$8/kW-yr (12%-18%) OpEx reduction from 2018 to 2040. When compared with the broader literature, these findings suggest that continued OpEx reductions may contribute 10% or more of the expected reductions in land-based wind's levelized cost of energy. Moreover, these estimates may understate the importance of OpEx owing to the multiplicative effects through which operational advancements influence not only O&M costs but also component reliability, performance, and plant-level availability-thereby affecting levelized costs though OpEx reduction and by enhancing annual energy production and plant lifetimes. Given the limited quantity and comparability of previously available OpEx data, the data and trends reported here may usefully inform OpEx assumptions used by electric system planners, analysts, modelers, and research and development managers. The results may also provide useful benchmarks to the wind industry, helping developers and asset owners compare their OpEx expectations with historical experience and other industry projections.

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Toward Perovskite Solar Cell Commercialization: A Perspective and Research Roadmap Based on Interfacial Engineering

2018

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High-efficiency and low-cost perovskite solar cells (PVKSCs) are an ideal candidate for addressing the scalability challenge of solar-based renewable energy. The dynamically evolving research field of PVKSCs has made immense progress in solving inherent challenges and capitalizing on their unique structure-property-processing-performance traits. This review offers a unique outlook on the paths toward commercialization of PVKSCs from the interfacial engineering perspective, relevant to both specialists and nonspecialists in the field through a brief introduction of the background of the field, current state-of-the-art evolution, and future research prospects. The multifaceted role of interfaces in facilitating PVKSC development is explained. Beneficial impacts of diverse charge-transporting materials and interfacial modifications are summarized. In addition, the role of interfaces in improving efficiency and stability for all emerging areas of PVKSC design are also evaluated. The authors' integral contributions in this area are highlighted on all fronts. Finally, future research opportunities for interfacial material development and applications along with scalability-durability-sustainability considerations pivotal for facilitating laboratory to industry translation are presented.

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The experience curve theory and its application in the field of electricity generation technologies – A literature review

Cited by 100 publications

References 107 publications

Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources

Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources

Benchmarking Wind Power Operating Costs in the United States: Results from a Survey of Wind Industry Experts

Toward Perovskite Solar Cell Commercialization: A Perspective and Research Roadmap Based on Interfacial Engineering

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