Smart Electric Vehicle Charging via Adjustable Real-Time Charging Rates

This paper presents a plug-in electric vehicle (PEV) charging control algorithm, Adjustable Real-Time Valley Filling (ARVF), to improve PEV charging and minimize adverse effects from uncontrolled PEV charging on the grid. ARVF operates in real time, adjusts to sudden deviations between forecasted an...

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Main Authors: Theron Smith, Joseph Garcia, Gregory Washington
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/22/10962
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author Theron Smith
Joseph Garcia
Gregory Washington
author_facet Theron Smith
Joseph Garcia
Gregory Washington
author_sort Theron Smith
collection DOAJ
description This paper presents a plug-in electric vehicle (PEV) charging control algorithm, Adjustable Real-Time Valley Filling (ARVF), to improve PEV charging and minimize adverse effects from uncontrolled PEV charging on the grid. ARVF operates in real time, adjusts to sudden deviations between forecasted and actual baseloads, and uses fuzzy logic to deliver variable charging rates between 1.9 and 7.2 kW. Fuzzy logic is selected for this application because it can optimize nonlinear systems, operate in real time, scale efficiently, and be computationally fast, making ARVF a robust algorithm for real-world applications. In addition, this study proves that when the forecasted and actual baseload vary by more than 20%, its real-time capability is more advantageous than algorithms that use optimization techniques on predicted baseload data.
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spelling doaj.art-bd9b3bb79ac2481fbfe15ae238f6ff722023-11-22T22:21:34ZengMDPI AGApplied Sciences2076-34172021-11-0111221096210.3390/app112210962Smart Electric Vehicle Charging via Adjustable Real-Time Charging RatesTheron Smith0Joseph Garcia1Gregory Washington2Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697-3550, USADepartment of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697-3550, USAGeorge Mason University, Fairfax, VA 22030, USAThis paper presents a plug-in electric vehicle (PEV) charging control algorithm, Adjustable Real-Time Valley Filling (ARVF), to improve PEV charging and minimize adverse effects from uncontrolled PEV charging on the grid. ARVF operates in real time, adjusts to sudden deviations between forecasted and actual baseloads, and uses fuzzy logic to deliver variable charging rates between 1.9 and 7.2 kW. Fuzzy logic is selected for this application because it can optimize nonlinear systems, operate in real time, scale efficiently, and be computationally fast, making ARVF a robust algorithm for real-world applications. In addition, this study proves that when the forecasted and actual baseload vary by more than 20%, its real-time capability is more advantageous than algorithms that use optimization techniques on predicted baseload data.https://www.mdpi.com/2076-3417/11/22/10962fuzzy logicplug-in electric vehiclevalley fillingdistribution transformerelectric vehicle chargingsmart charging
spellingShingle Theron Smith
Joseph Garcia
Gregory Washington
Smart Electric Vehicle Charging via Adjustable Real-Time Charging Rates
Applied Sciences
fuzzy logic
plug-in electric vehicle
valley filling
distribution transformer
electric vehicle charging
smart charging
title Smart Electric Vehicle Charging via Adjustable Real-Time Charging Rates
title_full Smart Electric Vehicle Charging via Adjustable Real-Time Charging Rates
title_fullStr Smart Electric Vehicle Charging via Adjustable Real-Time Charging Rates
title_full_unstemmed Smart Electric Vehicle Charging via Adjustable Real-Time Charging Rates
title_short Smart Electric Vehicle Charging via Adjustable Real-Time Charging Rates
title_sort smart electric vehicle charging via adjustable real time charging rates
topic fuzzy logic
plug-in electric vehicle
valley filling
distribution transformer
electric vehicle charging
smart charging
url https://www.mdpi.com/2076-3417/11/22/10962
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