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Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers

Electric vehicles (Evs) offer promising benefits in reducing emissions and enhancing energy security; however, accurately estimating their load presents a challenge in optimizing grid management and sustainable integration. Moreover, EV load estimation is context-specific, and generalized methods ar...

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Main Authors:	Almutairi, Abdulaziz, Albagami, Naif, Sultanh Almesned, Sultanh Almesned, Alrumayh, Omar, Malik, Hasmat
Format:	Article
Language:	English
Published:	MDPI 2023
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/107353/1/HasmatMalik2023_ElectricVehicleLoadEstimationatHome.pdf http://eprints.utm.my/107353/ http://dx.doi.org/10.3390/su152215878
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spelling	my.utm.1073532024-09-03T06:22:52Z http://eprints.utm.my/107353/ Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers Almutairi, Abdulaziz Albagami, Naif Sultanh Almesned, Sultanh Almesned Alrumayh, Omar Malik, Hasmat TK Electrical engineering. Electronics Nuclear engineering Electric vehicles (Evs) offer promising benefits in reducing emissions and enhancing energy security; however, accurately estimating their load presents a challenge in optimizing grid management and sustainable integration. Moreover, EV load estimation is context-specific, and generalized methods are inadequate. To address this, our study introduces a tailored three-step solution, focusing on the Middle East, specifically Saudi Arabia. Firstly, real survey data are employed to estimate driving patterns and commuting behaviors such as daily mileage, arrival/departure time at home and workplace, and trip mileage. Subsequently, per-unit profiles for homes and workplaces are formulated using these data and commercially available EV data, as these locations are preferred for charging by most EV owners. Finally, the developed profiles facilitate EV load estimations under various scenarios with differing charger ratios (L1 and L2) and building types (residential, commercial, mixed). Simulation outcomes reveal that while purely residential or commercial buildings lead to higher peak loads, mixed buildings prove advantageous in reducing the peak load of Evs. Especially, the ratio of commercial to residential usage of around 50% generates the lowest peak load, indicating an optimal balance. Such analysis aids grid operators and policymakers in load estimation and incentivizing EV-related infrastructure. This study, encompassing data from five Saudi Arabian cities, provides valuable insights into EV usage, but it is essential to interpret findings within the context of these specific cities and be cautious of potential limitations and biases. MDPI 2023-11 Article PeerReviewed application/pdf en http://eprints.utm.my/107353/1/HasmatMalik2023_ElectricVehicleLoadEstimationatHome.pdf Almutairi, Abdulaziz and Albagami, Naif and Sultanh Almesned, Sultanh Almesned and Alrumayh, Omar and Malik, Hasmat (2023) Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers. Sustainability (Switzerland), 15 (22). pp. 1-16. ISSN 2071-1050 http://dx.doi.org/10.3390/su152215878 DOI:10.3390/su152215878
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Almutairi, Abdulaziz Albagami, Naif Sultanh Almesned, Sultanh Almesned Alrumayh, Omar Malik, Hasmat Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers
description	Electric vehicles (Evs) offer promising benefits in reducing emissions and enhancing energy security; however, accurately estimating their load presents a challenge in optimizing grid management and sustainable integration. Moreover, EV load estimation is context-specific, and generalized methods are inadequate. To address this, our study introduces a tailored three-step solution, focusing on the Middle East, specifically Saudi Arabia. Firstly, real survey data are employed to estimate driving patterns and commuting behaviors such as daily mileage, arrival/departure time at home and workplace, and trip mileage. Subsequently, per-unit profiles for homes and workplaces are formulated using these data and commercially available EV data, as these locations are preferred for charging by most EV owners. Finally, the developed profiles facilitate EV load estimations under various scenarios with differing charger ratios (L1 and L2) and building types (residential, commercial, mixed). Simulation outcomes reveal that while purely residential or commercial buildings lead to higher peak loads, mixed buildings prove advantageous in reducing the peak load of Evs. Especially, the ratio of commercial to residential usage of around 50% generates the lowest peak load, indicating an optimal balance. Such analysis aids grid operators and policymakers in load estimation and incentivizing EV-related infrastructure. This study, encompassing data from five Saudi Arabian cities, provides valuable insights into EV usage, but it is essential to interpret findings within the context of these specific cities and be cautious of potential limitations and biases.
format	Article
author	Almutairi, Abdulaziz Albagami, Naif Sultanh Almesned, Sultanh Almesned Alrumayh, Omar Malik, Hasmat
author_facet	Almutairi, Abdulaziz Albagami, Naif Sultanh Almesned, Sultanh Almesned Alrumayh, Omar Malik, Hasmat
author_sort	Almutairi, Abdulaziz
title	Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers
title_short	Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers
title_full	Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers
title_fullStr	Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers
title_full_unstemmed	Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers
title_sort	electric vehicle load estimation at home and workplace in saudi arabia for grid planners and policy makers
publisher	MDPI
publishDate	2023
url	http://eprints.utm.my/107353/1/HasmatMalik2023_ElectricVehicleLoadEstimationatHome.pdf http://eprints.utm.my/107353/ http://dx.doi.org/10.3390/su152215878
_version_	1811681167769862144
score	13.222552

Electric vehicle load estimation at home and workplace in Saudi Arabia for grid planners and policy makers

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