As energy researchers, the Department of Energy datasets are the foundation of our work. Choosing the most valuable among them is like being asked to choose the most valuable book from a library – the value comes from the library itself, not the single book. Yet, no dataset in recent memory has proved more important than OpenEI.gov’s new Transparent Cost Database (http://en.openei.org/apps/TCDB/). This database displays historical and projected cost estimates for vehicles, biofuels and electricity generation technologies. Using this dataset, currently in its infancy, has the potential to considerably improve the effectiveness, efficiency and economic impact of private and public sector energy decisions.
The costs of energy technologies are a consistent area of confusion. These technologies have capital expenses during acquisition, ongoing operating and maintenance expenses during a multi-decadal service life, fuel expenses for some technologies and other costs. The different timing and magnitude of these costs, and various “capacity factors” among types of electricity generation equipment make it difficult for citizens and businesses to make an apples-to-apples comparison for technologies. The database provides a distribution of cost data for individual cost categories across technologies, as well as provides “levelized” costs per unit of electricity, gallon of gasoline equivalent and mile driven. These levelized costs allow private and public decision makers to easily compare different technologies. These data also enable innovation, as entrepreneurs and researchers can understand the existing individual factors affecting energy costs, and target their investments and innovations to outperform the status quo.
While the database is valuable, its impact could be magnified with several enhancements. First, energy cost data changes with many factors over time - innovations bring costs down, while material and other price fluctuations can move costs up or down. As each year passes, the database could provide insight on how close actual cost data are to previous projections, and the reasons for any discrepancy. This could improve energy cost forecasting, which would assist entrepreneurs planning energy innovations. Second, as government entities and institutions purchase new energy technologies, they could automatically report their costs to this database, which would increase efficiency and inform public and private energy R&D and capital investments. Finally, an API would allow developers to include these data in research sites, apps, new visualizations or analyses. Up-to-date, trusted and detailed cost information for energy technologies can enable the disruptive innovation needed as the 100+ year old U.S. energy system plans for the next century.
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