On improvement rates for renewable energy technologies: Solar PV, wind turbines, capacitors, and batteries

Significance Statement

  Quantification of the future technological capabilities is a particularly important capability in the renewable energy field due to the long lifecycles of the equipment involved.  The paper quantifies the rate of improvement per year for two key renewable energy generation technologies (Wp/$) and two electrical energy storage domains (Whr/$) showing the superior rate of improvement for solar energy relative to wind turbines and for capacitors relative to electrochemical batteries. A critical issue is making choices now while recognizing that the systems being chosen are undergoing improvement.  Arriving at adequate renewable energy systems over time means that systems that have less performance now but promise fully adequate performance later might be more favorable than systems that are better now but are still not adequate in the long term.  The paper also develops a theoretical basis and testable hypotheses to allow more robust understanding and prediction of the rates of improvement in various technological domains.      

 

On improvement rates for renewable energy technologies .Renewable Energy Global Innovations

Journal Reference

Renewable Energy, Volume 68,  2014, Pages 745–751.

Christopher L. Benson , Christopher L. Magee.

Massachusetts Institute of Technology, SUTD-MIT International Design Center, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.

Abstract

An important issue in various domains of renewable energy is the use of technological improvement trends to project future capabilities of energy technologies. This paper analyzes two pairs of renewable energy technologies and finds that the annual improvement rate of cost/investment is quite different for the four technological domains: namely, solar photovoltaics (PV) (9.0% per year), wind turbines (2.9%), batteries (3.1%) and capacitors (21.1%). While these trends have been reasonably consistent over long time frames, projecting these trends into the future without a better understanding of the underlying causes of the improvements is not at all reliable. This paper establishes theoretical fundamentals for explaining the differences in such rates and a framework for empirically probing such explanations using patent data. Employing this framework, this study collects and analyzes a set of highly representative patents for each of the four domains, allowing measurement of: patenting rates, reliance on scientific literature and other characteristics of the different fields. Our study of the inventions, while not establishing an indisputable causal relationship for the differing rates, establishes a broader theoretical basis for why such rates differ so greatly and why they might be stable over time. Among many possible effects, this study indicates that the age of knowledge utilized in the patents and the percentage of very important inventions in the field are the most likely significant contributors to higher rates of advance.

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