Accelerating the low-carbon transition will require policy to enhance local learning

B-Tier
Journal: Energy Policy
Year: 2022
Volume: 167
Issue: C

Authors (2)

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

The transition to a low-carbon society requires a deep transformation, enabled by rapid adoption of new energy technologies. A main driver for this will be technology learning, providing cost reductions in low-carbon technologies. Over the past two decades, learning has provided substantial cost reductions for a number of hardware technologies, such as PV modules, wind turbines, and battery packs, some by a factor of ten. Still, we observe weaker cost reductions in installing and integrating such technologies into the broader system. As a result, hardware costs comprise a decreasing share of total costs. In the case of US rooftop PV installations, hardware today accounts for less than a quarter of the total costs. Accelerating the transition to a low-carbon society will thus require more attention to learning in the implementation of technologies. In contrast to cost reductions of technology hardware, driven by global learning, learning in implementation is typically framed by local geography and structure, involving local actors, networks and institutions. In this Perspective we argue that accelerating the transition to a low-carbon society, depends on the advancement of our understanding of 1) the local learning required to reduce implementation costs, and 2) the policy mechanisms vital to stimulate local learning. The transition process calls for an improved understanding of the spatial dimensions that shape learning and the implications in designing policy that support local learning. Accordingly, we advocate for more comprehensive and contextualized research on policy to support local learning providing cost reductions in low-carbon technologies.

Technical Details

RePEc Handle
repec:eee:enepol:v:167:y:2022:i:c:s0301421522002683
Journal Field
Energy
Author Count
2
Added to Database
2026-01-26