PhD student Talal Khalid with Advisor K. Haran

Maximum-demand charges (MDCs) are a widely recognized barrier to the profitable operation of electric vehicle fast-charging facilities (EVFCFs) across the US. Under this structure, the sudden, massive peaks in power demand due to multiple EVs charging simultaneously, and the correspondingly high MDC, pose serious concerns to EVFCF’s economic and financial viability. To address this issue, multiple electric utility companies (EUCs) across the US have proposed EVFCF-specific electricity rate options that provide alternatives to MDCs. However, researchers, industry experts, and EV advocates have raised concerns about the success and sustainability of deploying the EUC proposed EVFCF-specific rates.
The research gap that this work aims to fill is to perform a comprehensive assessment of a location-particular application using offered solutions to the MDC issue, i.e., to determine the context and community optimal solution to the MDC issue, that will lead to an increase in EV adoption and EVFCF implementation. Using input from a set of stakeholders in Paducah, Kentucky, who are directly or indirectly impacted by the implementation of a particular EVFCF-specific rate option, this work assesses the applicability and sustainability of industry-proffered EVFCF-specific rate options in a particular setting. These stakeholders include:

The existing EVFCF operators in Paducah whose business profitability is adversely affected by the imposition of MDCs.
The incumbent electric utility, i.e., Paducah Power System (PPS), which proposes and implements EVFCF-specific rates.
Existing/potential EV users (businesses, residents, and visitors in Paducah) who pay/will pay the charging service price.

Residents and businesses in Paducah who are not necessarily EV owners/users, but their electric rate might be impacted due to the implementation of EVFCF-specific rates by PPS.
In our research, community interactions in the form of semi-structured, open-ended interviews and ethnographic observations, focus on assessing the key characteristics of EVFCF-specific rates that are sought by the above mentioned community stakeholders. Using causal loop analysis (see Figure 1), each industry-proffered EVFCF-specific rate option is then evaluated against those identified by stakeholders as desirable rate characteristics to determine the optimal EVFCF-specific rate option. The methodology developed and used in Paducah, we contend, can be implemented by other municipalities in the US to advance EV adoption by sustainably removing the key barrier of MDCs to EVFCF implementation. This research is funded by Professor Haran’s Grainger Fellowship Account.

Figure 1. Qualitative data analysis using causal loop diagram.