English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Electric vehicle charging facilities offer electric charge and parking tousers for a fee. Both parking availability and electric charge capacity areconstrained resources, and as the demand for charging facilities grows withincreasing electric vehicle adoption, so too does the potential for exceedingthese resource limitations. In this paper, we study how prices set by thecharging facility impact the likelihood that resource constraints are exceeded.Specifically, we present probabilistic bounds on the number of charging spotsand the total power supply needed at a facility based on the characteristics ofthe arriving vehicles. We assume the charging facility either offers a set ofdistinct and fixed charging rates to each user or allows the user to decide acharging deadline, from which a charging rate is determined. Users arriverandomly, requiring a random amount of charge. Additionally, each user has arandom impatience factor that quantifies their value of time, and a randomdesired time to stay at a particular location. Assuming rational user behavior,and with knowledge of the probability distribution of the random parameters, wepresent high-confidence bounds on the total number of vehicles parked at thestation and the aggregate power use of all vehicles actively charging. Wedemonstrate how these bounds can be used by a charging facility to determineappropriate prices and investigate through a Monte-Carlo simulation case studythe tightness of the bounds.

Resource Aware Pricing for Electric Vehicle Charging