Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615464
Title: Learning curves and engineering assessment of emerging energy technologies : onshore wind
Author: Mukora, Audrey Etheline
ISNI:       0000 0004 5367 6856
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2014
Availability of Full Text:
Access through EThOS:
Full text unavailable from EThOS. Please try the link below.
Access through Institution:
Abstract:
Sustainable energy systems require deployment of new technologies to help tackle the challenges of climate change and ensuring energy supplies. Future sources of energy are less economically competitive than conventional technologies, but there is the potential for cost reduction. Tools for modelling technological change are important for assessing the deployment potential of early-stage technologies. Learning curves are a tool for assessing and forecasting cost reduction of a product achieved through experience from cumulative production. They are often used to assess technological improvements, but have a number of limitations for emerging energy technologies. Learning curves are aggregate in nature, representing overall cost reduction gained from learning-by-doing. However, they do not identify the actual factors behind the cost reduction. Using the case study of onshore wind energy, this PhD study focuses on combining learning curves with engineering assessment methods for improved methods of assessing and managing technical change for emerging energy technologies. A third approach, parametric modelling, provides a potential means to integrate the two methods.
Supervisor: Mueller, Markus; Winskel, Mark Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.615464  DOI: Not available
Keywords: learning curves ; engineering assessment ; parametric modelling ; wind energy
Share: