Thesis

Harmonic emissions in electric vehicle smart charging

Downloadable Content

Download PDF
Creator
Rights statement
Awarding institution
  • University of Strathclyde
Date of award
  • 2026
Thesis identifier
  • T17584
Person Identifier (Local)
  • 202151687
Qualification Level
Qualification Name
Department, School or Faculty
Abstract
  • Smart charging for Electric Vehicles (EVs) is increasingly recognized as a pivotal strategy for managing the challenges posed by large-scale EV adoption. It offers significant economic and operational benefits by mitigating grid congestion, deferring infrastructure upgrades, and enabling off-peak charging. Governments worldwide have responded by mandating smart charging capabilities in EV infrastructure, underlining its critical role in advancing sustainable energy systems. However, while extensive research has addressed the benefits of smart charging in load management and voltage regulation, its power quality implications, particularly the generation of harmonic emissions, remain relatively underexplored. As EV penetration increases, understanding and managing the harmonic impacts of smart charging on the power system is vital to maintaining grid stability and power quality. This thesis adopts a comprehensive approach encompassing four main stages: measurement, analysis, quantification, and solution development. First, in the measurement phase, a detailed experimental setup is conducted to capture harmonic emissions from eight commercially available EV models. Each vehicle is charged using smart chargers across a range of current levels, measured in 1A increments from the minimum to the maximum permissible charging current. Harmonic amplitudes and phase angles are recorded for both single and multi-EV charging setups, providing a high resolution dataset suitable for further analysis. Next, the analysis phase statistically examines current total harmonic distortion (THDI), dominant harmonic orders, and phase angle interactions. A consistent inverse relationship is observed between charging current and harmonic emissions, where lower charging rates led to higher THDI. Multi-EV scenarios demonstrate partial harmonic cancellation due to phase diversity, though worst-case configurations still reach THDI levels exceeding 25%, with half of the tested EVs violating individual harmonic order limits. These findings suggest that similar THDI values can hide significant differences in individual harmonic order profiles, highlighting the limitations of THDI as a sole compliance metric. In the quantification phase, a Monte Carlo simulation framework is developed to evaluate the probabilistic nature of harmonic emissions resulting from simultaneous multiple EV charging events. This allows the assessment of standard compliance risks under varying EV combinations and charging rates, incorporating uncertainties in real world operating conditions. The assessment also incorporates a comparison of harmonic emissions from both single and multiple EV charging scenarios against the thresholds for THDI and individual harmonic orders as defined in international power quality standards(e.g. IEC 61000 and IEEE 519). Additionally, the impact of harmonic-rich loading on the aging of distribution transformers is quantified. A thermal-electrical model based on IEEE C57.91 and IEEE C57.110 standards is applied to a 160 kVA distribution transformer evaluated under full-load conditions, which are achieved by varying the number of simultaneously charging EVs at fixed current levels. Results reveal that harmonic-induced losses significantly elevate hot-spot temperatures and aging acceleration factors, particularly at low charging currents, potentially reducing transformer lifespan to under 10 years in worst-case conditions. Based on these findings, a rule-based harmonics-averse EV charging strategy is proposed to guide system operators in prioritizing charging rates, such as 13 A, that balance transformer longevity and connection capacity. This strategy provides an actionable guideline for transformer protection in heavily loaded scenarios without requiring additional infrastructure. Finally, in addition to proposing a rule-based EV charging management strategy for heavily loaded networks to mitigate transformer aging, the solution phase also introduces a harmonics-aware smart charging optimization framework specifically designed for partially loaded networks, aiming to ensure power quality compliance while meeting energy delivery requirements. A Particle Swarm Optimization (PSO) algorithm is combined with a Water Filling mechanism to generate charging schedules that meet user demand while maintaining THDI below regulatory limits. Regression models linking charging power to THDI enable tractable, real-time enforcement of harmonic constraints. Results reveal that this strategy maintains compliance without compromising energy delivery and avoids the need for costly hardware interventions, such as active filters. This thesis contributes to the state of knowledge by bridging a critical gap between smart charging design and harmonic-aware grid operation. Through experimental evidence, probabilistic modelling, and rule-based and optimization-based control, it offers actionable insights into balancing charging demand, power quality, and asset longevity. The work also highlights shortcomings in existing harmonic standards when applied to smart, controllable loads. It recommends revising compliance protocols to accommodate the dynamic behaviour of smart charging and offers practical guidance to support utilities, regulators, and researchers in enabling scalable and reliable EV integration.
Advisor / supervisor
  • Bayram, İslam Şafak
  • Galloway, Stuart
Resource Type
DOI
Date Created
  • 2025

Relations

Items

Thumbnail Title Date Uploaded Visibility Actions
file details PDF of Thesis T17584 2026-02-16 Public Download