Combining Ad Hoc Text Mining and Descriptive Analytics to Investigate Public EV Charging Prices in the United States

David Trinko, Emily Porter, Jamie Dunckley, Thomas Bradley and Timothy Coburn
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David Trinko: Department of Systems Engineering, Colorado State University, Fort Collins, CO 80523, USA
Emily Porter: Electric Power Research Institute, Palo Alto, CA 94304, USA
Jamie Dunckley: Electric Power Research Institute, Palo Alto, CA 94304, USA
Thomas Bradley: Department of Systems Engineering, Colorado State University, Fort Collins, CO 80523, USA
Timothy Coburn: Department of Systems Engineering, Colorado State University, Fort Collins, CO 80523, USA

Energies, 2021, vol. 14, issue 17, 1-26

Abstract: Electric vehicle (EV) charging infrastructure is present all over the United States, but charging prices vary greatly, both in amount and in the methods by which they are assessed. For this paper, we interpret and analyze charging price information from PlugShare, a crowd-sourced EV charging data platform. Because prices in these data exist in a semi-structured textual format, an ad hoc text mining approach is used to extract quantitative price information. Descriptive analytics of the processed dataset demonstrate how the prices of EV charging vary with charging level (Direct Current Fast Charging versus Level 2), geographic location, network provider, and location type. Our research indicates that a great deal of diversity and flexibility exists in structuring the prices of EV charging to enable incentives for shaping charging behaviors, but that it has yet to be widely standardized or utilized. Comparisons with estimates of the levelized cost of EV charging illustrate some of the challenges associated with operating and using these stations.

Keywords: ad hoc text mining; descriptive analytics; data wrangling; EV charging cost; level 2 charging; DC fast charging; spatial variation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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