LAPSE:2023.27248
Published Article

LAPSE:2023.27248
Quantifying the Flexibility of Electric Vehicles in Germany and California—A Case Study
April 4, 2023
Abstract
The adoption of electric vehicles is incentivized by governments around the world to decarbonize the mobility sector. Simultaneously, the continuously increasing amount of renewable energy sources and electric devices such as heat pumps and electric vehicles leads to congested grids. To meet this challenge, several forms of flexibility markets are currently being researched. So far, no analysis has calculated the actual flexibility potential of electric vehicles with different operating strategies, electricity tariffs and charging power levels while taking into account realistic user behavior. Therefore, this paper presents a detailed case study of the flexibility potential of electric vehicles for fixed and dynamic prices, for three charging power levels in consideration of Californian and German user behavior. The model developed uses vehicle and mobility data that is publicly available from field trials in the USA and Germany, cost-optimizes the charging process of the vehicles, and then calculates the flexibility of each electric vehicle for every 15 min. The results show that positive flexibility is mostly available during either the evening or early morning hours. Negative flexibility follows the periodic vehicle availability at home if the user chooses to charge the vehicle as late as possible. Increased charging power levels lead to increased amounts of flexibility. Future research will focus on the integration of stochastic forecasts for vehicle availability and electricity tariffs.
The adoption of electric vehicles is incentivized by governments around the world to decarbonize the mobility sector. Simultaneously, the continuously increasing amount of renewable energy sources and electric devices such as heat pumps and electric vehicles leads to congested grids. To meet this challenge, several forms of flexibility markets are currently being researched. So far, no analysis has calculated the actual flexibility potential of electric vehicles with different operating strategies, electricity tariffs and charging power levels while taking into account realistic user behavior. Therefore, this paper presents a detailed case study of the flexibility potential of electric vehicles for fixed and dynamic prices, for three charging power levels in consideration of Californian and German user behavior. The model developed uses vehicle and mobility data that is publicly available from field trials in the USA and Germany, cost-optimizes the charging process of the vehicles, and then calculates the flexibility of each electric vehicle for every 15 min. The results show that positive flexibility is mostly available during either the evening or early morning hours. Negative flexibility follows the periodic vehicle availability at home if the user chooses to charge the vehicle as late as possible. Increased charging power levels lead to increased amounts of flexibility. Future research will focus on the integration of stochastic forecasts for vehicle availability and electricity tariffs.
Record ID
Keywords
charging strategy, electric vehicle, electricity pricing, flexibility, flexibility market, home energy management system, Optimization
Subject
Suggested Citation
Zade M, You Z, Kumaran Nalini B, Tzscheutschler P, Wagner U. Quantifying the Flexibility of Electric Vehicles in Germany and California—A Case Study. (2023). LAPSE:2023.27248
Author Affiliations
Zade M: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany [ORCID]
You Z: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany
Kumaran Nalini B: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany [ORCID]
Tzscheutschler P: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany [ORCID]
Wagner U: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany [ORCID]
You Z: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany
Kumaran Nalini B: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany [ORCID]
Tzscheutschler P: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany [ORCID]
Wagner U: Chair of Energy Economy and Application Technology, TUM Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany [ORCID]
Journal Name
Energies
Volume
13
Issue
21
Article Number
E5617
Year
2020
Publication Date
2020-10-27
ISSN
1996-1073
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Original Submission
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PII: en13215617, Publication Type: Journal Article
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LAPSE:2023.27248
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https://doi.org/10.3390/en13215617
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