Assessing EV Charging Impacts on Power Distribution Systems: A Unified Co-Simulation Framework

TL;DR

This paper introduces a comprehensive, scalable co-simulation framework using OpenDSS and synthetic data to analyze the impacts of large-scale EV charging on urban distribution networks, aiding infrastructure planning.

Contribution

It presents a novel, modular co-simulation framework integrating high-fidelity synthetic data and geospatial visualization for detailed EV impact analysis on power distribution systems.

Findings

Identifies critical system components needing upgrades due to EV loads

Supports diverse simulation scenarios for planning

Enables targeted infrastructure reinforcement strategies

Abstract

The growing adoption of electric vehicles (EVs) is expected to significantly increase demand on electric power distribution systems, many of which are already nearing capacity. To address this, the paper presents a comprehensive framework for analyzing the impact of large-scale EV integration on distribution networks. Using the open-source simulator OpenDSS, the framework builds detailed, scalable models of electric distribution systems, incorporating high-fidelity synthetic data from the SMART-DS project. The study models three feeders from an urban substation in San Francisco down to the household level. A key contribution is the framework's ability to identify critical system components likely to require upgrades due to increased EV loads. It also incorporates advanced geospatial visualization through QGIS, which aids in understanding how charging demands affect specific grid areas, helping stakeholders target infrastructure reinforcements. To ensure realistic load modeling, the framework uses EV load profiles based on U.S. Department of Energy projections, factoring in vehicle types, charging behaviors, usage patterns, and adoption rates. By leveraging large-scale synthetic data, the model remains relevant for real-world utility planning. It supports diverse simulation scenarios, from light to heavy EV charging loads and distributed vs. centralized charging patterns, offering a practical planning tool for utilities and policymakers. Additionally, its modular design enables easy adaptation to different geographic regions, feeder setups, and adoption scenarios, making it suitable for future studies on evolving grid conditions.