Open Source Software and Crowdsourcing for Energy Analysis

By Ijeoma Oneyji and Morgan Bazilian
November 2012

In a mid-July article in Energy Policy, my colleagues and I discussed issues around refining and augmenting energy planning model through innovative new tools and methods. This short blog draws from that piece.

Modern energy systems are characterised by increasingly complex interactions between energy supply, distributors, and consumer demand. High quality analytical data and tools are vital for predicting and understanding these interactions in order to enable informed energy system design, implementation, and operation decisions. Creating energy analytics that can effectively inform public policy requires three key factors:

  1. Validated models must be available and appropriate for the target environment.
  2. Suitable data must be available for input into the model and for verifying model-based results.
  3. People trained in the use of the tools and in interpreting the outcomes for local conditions must operate the models.

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. New tools, methods, and systems are emerging to address these issues.

illustration interconnecting lines and points

In April 2012, the then President of the World Bank tweeted, "Open information, open data, and open access to knowledge may turn out to be the most important legacy of the past 5 years.” Still, potentially transformative open source software (OSS) and open data are in the early stages of adoption in the area of energy system analysis. It appears likely that open modelling efforts can improve the utility and accessibility of energy models and also lower the cost of data collection and management. In addition, the directed application of crowdsourcing to push the development of open modelling tools and datasets could yield significant benefits to the international energy modelling community.

Adequate national capacity to track progress toward universal modern energy access represents a crucial element of energy poverty alleviation and sustainable development strategies. For developing countries—which frequently lack established infrastructure, data, and software tools—there are significant potential benefits from rigorous analyses enabled by open source tools and data. Ultimately, these open energy resources, combined with open innovation processes, can be harnessed to better inform energy decision-making and rapidly develop low-cost, high-quality and localised energy resources.

Governmental acceptance and adoption of open data has been growing rapidly with examples ranging from the United States ( and the UK ( and, to Kenya ( and Ghana. As another example, the World Bank's open data initiative includes multiple platforms through which one can access and process data, including mobile apps, Application Programming Interfaces (APIs), resource listings, data visualization tools, and a knowledge repository. The Open Data Initiative also allows interactive development of metadata standards. Transparency, accountability and the belief that opening this data to the public will lower the barriers to innovations that will benefit society seem to be the impetus for these open data initiatives.

Crowdsourcing has proven to be an effective and efficient way to generate and maintain valued datasets, tools, and educational resources. The term first appeared in Wired Magazine6, and the concept has since been applied on a huge range of projects. Because quality energy data is often not available for particular local needs, crowdsourcing can be an effective method for distributing the task among the broader community. Crowdsourcing data collection from reviewers and users of the data has several benefits including the potential for reduced cost, reduced time, and higher quality.

The possibilities for using these tools and methods to leapfrog current ways of thinking about data gathering and energy planning are significant. These in turn can lead to better energy systems, and, most importantly, high quality and affordable energy service for all. Finally, the storage and maintenance of publicly accessible datasets, software tools, and training materials require a long-term funding mechanism. This presents an important opportunity for the international community, especially in relation to developing countries.

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