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DATA

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Pecan Street Inc. is a local 501(c)(3) that specializes in producing, analyzing, and sharing data on energy and water consumption practices as well as verifying new “smart home” technologies, electricity pricing, electric vehicle infrastructure, solar energy tech, and energy storage tech. On their company website, Pecan Street Inc. brags about having the largest utility consumption data port in the world and claims to “provide access to the world’s best data on consumer energy and water consumption behavior.” Their data source is a group of over 1000 volunteers that live in the Mueller community, a mixed use residential and commercial zone with its own microgrid that has the highest density of solar panels-plus-electric vehicles in the state of Texas. It was for this reason that the Mueller Community was chosen as one of the Austin locations for a federally funded experiment in energy storage. The project, named Austin SHINES, was co-funded by the DOE’s SunShot Initiative (during Obama’s administration) and the Texas Commission for Environmental Quality to test the efficiency of solar-plus-storage systems at different scales (household, residential/commercial, and utility scales). On October 4, 2018, Pecan Street posted a blog announcing that they had finally “crossed into the Big Data realm. With the acquisition of a few new project servers, [they] have surpassed one petabyte of data storage availability at Pecan Street.”

            According to their website, the data produced at Pecan Street is helping develop technology that can actually increase grid stability while also increasing its efficiency and capacity to incorporate distributed renewable energy resources: “Distributed storage, automated demand response, improved lighting ballasts, power supplies and grid control products can all mitigate or eliminate existing electricity challenges if they are developed using data that details the issues correctly.” Critical data scholars, however, have argued that data always require the presence of human experts to animate them (Gliteman 2013). But how, if at all, is this analytic commitment altered by the development of the “internet-of-things,” where humans are able to set parameters on smart-technology and smart-contracts, running on blockchain, so that these devices respond to data by themselves in real time?