| 1 |
How do learning externalities influence the evaluation of Ontario's renewables support policies?
Beck M, Rivers N, Wigle R
Energy Policy, 117, 86, 2018 |
| 2 |
Evaluating the case for supporting renewable electricity
Newbery D
Energy Policy, 120, 684, 2018 |
| 3 |
A dynamic programming approach for modeling low-carbon fuel technology adoption considering learning-by-doing effect
Chen YC, Zhang YT, Fan YY, Hu KJ, Zhao JY
Applied Energy, 185, 825, 2017 |
| 4 |
Experience curve for natural gas production by hydraulic fracturing
Fukui R, Greenfield C, Pogue K, van der Zwaan B
Energy Policy, 105, 263, 2017 |
| 5 |
The price evolution of wind turbines in China: A study based on the modified multi-factor learning curve
Yu Y, Li H, Che YY, Zheng QJ
Renewable Energy, 103, 522, 2017 |
| 6 |
Renewable energies cannot compete with forest carbon sequestration to cost-efficiently meet the EU carbon target for 2050
Vass MM
Renewable Energy, 107, 164, 2017 |
| 7 |
The prospects for Small Hydropower in Colombia
Arias-Gaviria J, van der Zwaan B, Kober T, Arango-Aramburo S
Renewable Energy, 107, 204, 2017 |
| 8 |
Learning by doing with spillovers: Strategic complementarity versus strategic substitutability
Kogan K, El Ouardighi F, Chernonog T
Automatica, 67, 282, 2016 |
| 9 |
Nuclear reactors' construction costs: The role of lead-time, standardization and technological progress
Berthelemy M, Rangel LE
Energy Policy, 82, 118, 2015 |
| 10 |
A review of learning rates for electricity supply technologies
Rubin ES, Azevedo IML, Jaramillo P, Yeh S
Energy Policy, 86, 198, 2015 |
