[Paper Review] Design and Implementation of Low-Cost Electric Vehicles (Evs) Supercharger: A Comprehensive Review

Md Khaledur Rahman, Faysal Amin Tanvir+3 more|arXiv (Cornell University)|Feb 24, 2024

Electric Vehicles and Infrastructure20 citations

TL;DR

The paper proposes a probabilistic modeling method using smart meter data and an agent-based simulator to assess how cost-driven EV charging strategies impact a power distribution network, focusing on Frederiksberg's low voltage network with 40% EV adoption.

ABSTRACT

This article presents a probabilistic modeling method utilizing smart meter data and an innovative agent-based simulator for electric vehicles (EVs). The aim is to assess the effects of different cost-driven EV charging strategies on the power distribution network (PDN). We investigate the effects of a 40% EV adoption on three parts of Frederiksberg's low voltage distribution network (LVDN), a densely urbanized municipality in Denmark. Our findings indicate that cable and transformer overloading especially pose a challenge. However, the impact of EVs varies significantly between each LVDN area and charging scenario. Across scenarios and LVDNs, the share of cables facing congestion ranges between 5% and 60%. It is also revealed that time-of-use (ToU)-based and single-day cost-minimized charging could be beneficial for LVDNs with moderate EV adoption rates. In contrast, multiple-day optimization will likely lead to severe congestion, as such strategies concentrate demand on a single day that would otherwise be distributed over several days, thus raising concerns about how to prevent it. The broader implications of our research suggest that, despite initial worries primarily centered on congestion due to unregulated charging during peak hours, a transition to cost-based smart charging, propelled by an increasing awareness of time-dependent electricity prices, may lead to a significant rise in charging synchronization, bringing about undesirable consequences for the power distribution network (PDN).

Motivation & Objective

• Assess how different cost-driven EV charging strategies affect the power distribution network (PDN).
• Evaluate impacts of 40% EV adoption on Frederiksberg's low voltage distribution network (LVDN).
• Identify congestion risk across LVDN areas under various charging scenarios.
• Inform policy on time-of-use pricing and charging optimization to mitigate PDN congestion.

Proposed method

• Develop a probabilistic model using smart meter data.
• Build an agent-based simulator for EV charging scenarios.
• Analyze three LVDN areas in Frederiksberg under multiple charging strategies.
• Evaluate congestion exposure for cables and transformers.
• Compare ToU-based and cost-minimized single-day strategies.
• Assess risks of multi-day optimization concentrating demand.

Experimental results

Research questions

• RQ1 How do cost-driven EV charging strategies influence congestion and loading in Frederiksberg's LVDN under 40% EV adoption?
• RQ2 Which charging strategies (ToU-based, single-day minimizes cost, multi-day optimization) best mitigate PDN congestion in moderate adoption scenarios?
• RQ3 What portion of cables experience congestion under different scenarios and areas (5%–60%)?
• RQ4 What are the broader implications of shifting toward cost-based smart charging on synchronization and PDN reliability?

Key findings

• Congestion risk varies by LVDN area and charging scenario, with 5%–60% of cables facing congestion across scenarios.
• ToU-based and single-day cost-minimized charging can benefit LVDNs with moderate EV adoption.
• Multiple-day optimization is likely to cause severe congestion by concentrating demand on a single day.
• Wider shift to cost-based charging may increase charging synchronization, raising PDN concerns.