Technological learning in the energy sector : lessons for policy, industry and science

By M. Junginger, W. van Sark, André P. C. Faaij. 2010

141 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/3188762a71392a5f40bca82feda8a1ed58f07eeb

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Citations in the corpus

A review of learning rates for electricity supply technologies (2015, background): “In all cases, however, there is still considerable uncertainty in the ability of different model formulations to represent induced technological change (Junginger et al., 2010; Yeh and Rubin, 2012).”
The economic viability of battery storage for residential solar photovoltaic systems – A review and a simulation model (2014, background): “[47] Module lifetime 25 years See Table A.”
Renewable Electricity Futures Study. Volume 1. Exploration of High-Penetration Renewable Electricity Futures (2012, background): “Learning curves have been used extensively to understand past cost trends and to forecast future cost reductions for a variety of energy technologies, including renewable energy (e.g., McDonald and Schrattenholzer 2001; Kahouli-Brahmi 2009; Junginger et al. 2010).”
The Effect of Local and Global Learning on the Cost of Renewable Energy in Developing Countries (2016, background): “Experience in the industrialized world has shown that cost reductions and performance improvements of new technologies are often closely linked to policies aimed at increased production and deployment (Jänicke, 2012), driven by mechanisms collectively referred to as technological learning (Junginger”
Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects (2011, unknown): “Generally, technological learning concepts are simulated through the learning curve model, which explains the relationship between cost decrease and output growth [3].”
The experience curve theory and its application in the field of electricity generation technologies – A literature review (2018, background): “[26] note, many authors today use the term “learning curve” as a synonym for “experience curve”.”
The political logics of clean energy transitions (2018, background): “50 Kasa and Underthun (2010). 504 Hanna Breetz, Matto Mildenberger and Leah Stokes”
The future cost of electrical energy storage based on experience rates (2017, unknown): “CO = (capexEES − RVEES (1 + r)NEES ) CRF mileage + ( Pfuel ηEES DoDEES) 1 CRF ηfuel NEES ∑ (1 − DEGEESn) N n=1 (8)”