A novel power flow control unit for V2G and G2V mode of electric vehicles
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Devika Harikumar
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Rajeev Thankappan Nair
Abstract
The increasing need for renewable energy and storage solutions, driven by the depletion of traditional energy sources, highlights the importance of integrating electric vehicles (EVs) as part of the energy storage system. The failure of distribution transformers during peak EV charging times in Kerala, India, highlights a significant issue related to judicious management of charging and discharging of Electric vehicles during peak time. The paper presents a novel control unit for EVs that supports both electric vehicle modes. The work focuses on designing and analyzing a Dual Active Bridge (DAB) based advanced charging system for G2V and V2G mode operation. A control scheme for managing power flow with bidirectional capability is developed based on the battery’s State-of-Charge (SoC) and the charging time slot during the day. The novelty of the work is the combined Time-of-Use (ToU) and State-of-Charge (SoC) based control algorithm for power flow management. The performance of the controller in both operating modes is thoroughly evaluated and validated, providing a robust foundation for its implementation. The system model is created in MATLAB/Simulink, and the effectiveness of the power flow control algorithm is tested through hardware-in-the-loop (HIL) experiments using OPAL-RT and TMS320F28379D microcontrollers. The proposed SoC and ToU-based power management strategy is economically efficient because it capitalizes on the pricing difference between off-peak and peak periods. With high charging/discharging efficiency, the combination of SoC and ToU-based tariffs proves profitable and sustainable, offering significant cost savings and financial returns in the long run. The intelligent power flow control unit will offer a practical solution to the peak demand challenges in utility due to uncoordinated EV charging.
Funding source: NAMPEt
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: Devika Harikumar.: Conceptualization, Methodology, Software, Investigation, Validation, Writing – original draft. Narendramudra Narendran Geetha: Conceptualization, Methodology, Investigation, Editing. Rajeev Thankappan Nair: Conceptualization, Supervision, Resources, Writing – review & editing.
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Use of Large Language Models, AI and Machine Learning Tools: Not applicable.
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Conflict of interest: No conflict of interest.
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Research funding: The work is supported under National Mission on Power Electronics Technology Phase-III (NaMPET-III), MeitY, India, No. 25(6)/2020-ESDA dtd 23-03-2021.
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Data availability: Data will be made available on request.
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