A Review on Integration of Electric Vehicle in Smart Grid: Operational modes, Issues and Challenges

Sharma, Bhawini; Maherchandani, Jai Kumar

doi:10.1109/iccci54379.2022.9740940

Cited by 4 publications

(2 citation statements)

References 41 publications

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“…Thus, the novel vehicle-to-home (V2H) technology is appealing due to its ability to reduce electricity prices in the home. In addition, when the SG is overloaded, V2H technology transfers the peak load and supplies constant emergency lighting [9].…”

Section: Introductionmentioning

confidence: 99%

A Reinforcement Learning Approach for Integrating an Intelligent Home Energy Management System with a Vehicle-to-Home Unit

2023

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These days, users consume more electricity during peak hours, and electricity prices are typically higher between 3:00 p.m. and 11:00 p.m. If electric vehicle (EV) charging occurs during the same hours, the impact on residential distribution networks increases. Thus, home energy management systems (HEMS) have been introduced to manage the energy demand among households and EVs in residential distribution networks, such as a smart micro-grid (MG). Moreover, HEMS can efficiently manage renewable energy sources, such as solar photovoltaic (PV) panels, wind turbines, and vehicle energy storage. Until now, no HEMS has intelligently coordinated the uncertainty of smart MG elements. This paper investigated the impact of PV solar power, MG storage, and EVs on the maximum solar radiation hours. Several deep learning (DL) algorithms were utilized to account for the uncertainties. A reinforcement learning home centralized photovoltaic (RL-HCPV) scheduling algorithm was developed to manage the energy demand between the smart MG elements. The RL-HCPV system was modelled according to several constraints to meet household electricity demands in sunny and cloudy weather. Additionally, simulations demonstrated how the proposed RL-HCPV system could incorporate uncertainty, and efficiently handle the demand response and how vehicle-to-home (V2H) can help to level the appliance load profile and reduce power consumption costs with sustainable power production. The results demonstrated the advantages of utilizing RL and V2H technology as potential smart building storage technology.

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Section: Introductionmentioning

confidence: 99%

A Reinforcement Learning Approach for Integrating an Intelligent Home Energy Management System with a Vehicle-to-Home Unit

2023

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“…Thus, to reduce the burden of developing such a new infrastructure; (1) EV batteries can be charged using the surplus energy from local RESs [85], and (2) EV charging/discharging activities can be controlled as part of P2P energy trading [28,62]. Furthermore, P2P trading can increase RESs self-consumption and reduce energy costs by using EVs as extra storage for the RESs surplus energy from households/neighbours and discharge that energy when required such as during high tariff periods [67].…”

Section: Ev Challenges and Solutionsmentioning

confidence: 99%

Forecast-based Energy Management Systems

Al-Sorour

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Smart Vehicle-to-Home (V2H) Platform Enabled Home Energy Management System (HEMS) for Backup Supply

Mohamed,

Zulkefli,

Sagar

et al. 2023

2023 IEEE Green Technologies Conference (GreenTech)

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A Review on Integration of Electric Vehicle in Smart Grid: Operational modes, Issues and Challenges

Cited by 4 publications

References 41 publications

A Reinforcement Learning Approach for Integrating an Intelligent Home Energy Management System with a Vehicle-to-Home Unit

A Reinforcement Learning Approach for Integrating an Intelligent Home Energy Management System with a Vehicle-to-Home Unit

Forecast-based Energy Management Systems

Smart Vehicle-to-Home (V2H) Platform Enabled Home Energy Management System (HEMS) for Backup Supply

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