Development and Implementation of an Electric Vehicle Emulator for Enhanced Microgrid Management Studies

The integration of Electric Vehicles (EVs) into microgrids presents unique challenges and opportunities for optimizing energy management and ensuring system stability. In this context, utilizing real-world devices for testing is crucial for accurately assessing and enhancing microgrid management features. This paper introduces a novel EV emulator algorithm specifically designed for microgrid studies involving real-world equipment. The emulator accurately simulates EV behavior, including dynamic load profiles, state-of-charge (SoC) variations, and charging/discharging patterns, allowing researchers to conduct detailed analyses of EV impacts on microgrid operations. Our algorithm interfaces seamlessly with actual microgrid components, enabling real-time interaction and assessment of various scenarios such as peak load shaving, renewable energy integration, and demand response strategies.

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Publication Details

Published
2025-02-10
DOI
https://doi.org/10.1109/tpec63981.2025.10907168
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
Field-Weighted Citation Impact
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article

Development and Implementation of an Electric Vehicle Emulator for Enhanced Microgrid Management Studies

Stephen Bayne, Rajendra P. Shrestha, Argenis Bilbao, Joshua MacFie et al.
Electric and Hybrid Vehicle Technologies
article

Development and Implementation of an Electric Vehicle Emulator for Enhanced Microgrid Management Studies

Stephen Bayne, Rajendra P. Shrestha, Argenis Bilbao, Joshua MacFie, Sanka Liyanage, Manohar Chamana, Pedro Eisenkraemer, Larissa S. Del Rio
article en

Abstract

The integration of Electric Vehicles (EVs) into microgrids presents unique challenges and opportunities for optimizing energy management and ensuring system stability. In this context, utilizing real-world devices for testing is crucial for accurately assessing and enhancing microgrid management features. This paper introduces a novel EV emulator algorithm specifically designed for microgrid studies involving real-world equipment. The emulator accurately simulates EV behavior, including dynamic load profiles, state-of-charge (SoC) variations, and charging/discharging patterns, allowing researchers to conduct detailed analyses of EV impacts on microgrid operations. Our algorithm interfaces seamlessly with actual microgrid components, enabling real-time interaction and assessment of various scenarios such as peak load shaving, renewable energy integration, and demand response strategies.

Texas Tech University (US), Renewable Energy Systems (United States) (US)
Openalex Percentile: Top 97%
Electric and Hybrid Vehicle Technologies
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Development and Implementation of an Electric Vehicle Emulator for Enhanced Microgrid Management Studies — Stephen Bayne, Rajendra P. Shrestha, et al. · (2025) | TGRS Research Map | TGRS