Open Source software and crowdsourcing for energy analysis

Executive Summary

Informed energy decision making requires effective software, high-quality
input data, and a suitably trained user community. Developing these
resources can be expensive and time consuming. Even when data and tools are
intended for public re-use they often come with technical, legal, economic
and social barriers that make them difficult to adopt, adapt and combine
for use in new contexts.

We focus on the promise of open, publically accessible software and data as
well as crowdsourcing techniques to develop robust energy analysis tools
that can deliver crucial, policy-relevant insight, particularly in
developing countries, where planning resources are highly constrained –
and the need to adapt these resources and methods to the local context is
high. We survey existing research, which argues that these techniques can
produce high-quality results, and also explore the potential role that
linked, open data can play in both supporting the modelling process and in
enhancing public engagement with energy issues.

Authors

Morgan Bazilian (a,b), Andrew Rice (c), Juliana Rotich (d), Mark Howells
(e), Joseph DeCarolis (f), Stuart Macmillan (g,h), Cameron Brooks (i),
Florian Bauer (j), and Michael Liebreich (k).

(a) United Nations Industrial Development Organisation, Vienna, Austria

(b) International Institute for Applied Systems Analysis, Laxenburg,
Austria

(c) Computer Laboratory, University of Cambridge, Cambridge, UK

(d) Ushahidi, Nairobi, Kenya

(e) Royal Swedish Institute of Technology, Stockholm, Sweden

(f) North Carolina State University, North Carolina, USA

(g) Stanford University, California, USA

(h) National Renewable Energy Laboratory, Colorado, USA

(i) Tendril Networks, Colorado, USA

(j) Renewable Energy and Energy Efficiency Partnership, Vienna, Austria

(k) Bloomberg New Energy Finance, London, UK

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