Future Trends in Smart Green IoV: Vehicle-to-Everything in the Era of Electric Vehicles

IEEE Open Journal of Vehicular Technology, Journal Year: 2024, Volume and Issue: 5, P. 278 - 297

Published: Jan. 1, 2024

The electrification of the transportation sector is an important step to ensure a sustainable system. It offers promising solution reduce oil consumption, decrease Greenhouse Gas (GHG) emissions, improve air quality, increase efficiency, and it can play role in integration renewable energy resources into electric grid. However, one biggest bottlenecks vehicles requirement for various charging infrastructure options. Three technologies have emerged as game-changers: Dynamic Wireless Charging (DWC), Battery Swapping Stations, Fast Stations (FCSs). These advancements potential adoption Electric Vehicles (EVs) by addressing critical challenges such range anxiety downtime issues EV users. primary focus this work on FCS, which currently represents most readily available option market. To optimal utilization infrastructure, address related routing EVs nearest FCS that meet requirements, wait time, duration cost. Vehicle-to-Everything (V2X) Internet (IoV) will enhancing FCS. Additionally, coordination demand essential achieve grid load balancing prevent overload. main paper present vision future trends Smart Green IoV era V2X connectivity, integration, vehicular networking, data security, services.

Language: Английский

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A Review of Bidirectional Charging Grid Support Applications and Battery Degradation Considerations

Energies, Journal Year: 2024, Volume and Issue: 17(6), P. 1320 - 1320

Published: March 9, 2024

Electric vehicles (EVs) are crucial in mitigating global emissions by replacing internal combustion engines. The capacity of EV batteries, coupled with their charging infrastructure, offers the added advantage supplying flexible demand and providing response benefits to power grid, which is essential as overall increases. EVs ready for vehicle-to-everything (V2X) applications chargers that support them enhance this flexibility allowing varied storage applications. However, fully harness these benefits, it vital consider drivers’ habits optimize discharging controls minimize battery life impact. This study examines various V2X North America effects on longevity, considering patterns. Additionally, investigates advanced aging-aware optimization algorithms managing bidirectional charging.

Language: Английский

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Integrated energy system modeling perspectives for future decarbonization pathways based on sector coupling, life-cycle emissions and vehicle-to-grid integration

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 215, P. 115620 - 115620

Published: March 18, 2025

Language: Английский

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Optimal Anti-Icing and De-Icing Coordination Scheme for Resilience Enhancement in Distribution Networks Against Ice Storms

IEEE Transactions on Smart Grid, Journal Year: 2024, Volume and Issue: 15(4), P. 3486 - 3498

Published: Feb. 21, 2024

Ice storms can cause serious damage to power distribution systems, thus the development of effective anti-icing and de-icing strategies is great significance. In this article, an optimal coordinated operation scheme proposed enhance resilience systems against ice storms, which based on ice-melting capacity lines. Firstly, a comprehensive risk analysis for in provided. Then, novel critical condition initiation weather forecast deviation potential load loss systems. On basis, optimization model networks with intelligent soft open point energy storage established, aims at minimizing overall loss. Considering double overloading methods, flow limit violation function used reasonably allocate proportion various risks. Finally, method verified IEEE 33-node network.

Language: Английский

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Feasibility of Vehicle-to-Grid (V2G) Implementation in Japan: A Regional Analysis of the Electricity Supply and Demand Adjustment Market

Energy, Journal Year: 2024, Volume and Issue: unknown, P. 133317 - 133317

Published: Oct. 1, 2024

Language: Английский

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Artificial Intelligence Optimization for User Prediction and Efficient Energy Distribution in Electric Vehicle Smart Charging Systems

Energies, Journal Year: 2024, Volume and Issue: 17(22), P. 5772 - 5772

Published: Nov. 19, 2024

This paper presents an advanced AI-based optimization framework for Electric Vehicle (EV) smart charging systems, focusing on efficient energy distribution to meet dynamic user demand. The study leverages machine learning models such as Random Forest, Support Vector Regression (SVR), Gradient Boosting Regressor, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) forecast demand optimize allocation. Among the models, XGBoost demonstrated superior predictive performance, achieving lowest Mean Absolute Error (MAE) Root Square (RMSE), making it most effective real-time prediction in scenarios. introduces proportional priority-based allocation strategies distribute available effectively, with a focus minimizing shortfalls balancing supply Results from model reduced error by 15% compared other significantly improving station’s ability efficiently. proposed AI enhances station operations, supports grid stability, promotes sustainability context of increasing EV adoption.

Language: Английский

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Electric Vehicles and Energy Communities: Vehicle-to-Grid Opportunities and a Sustainable Future

Energies, Journal Year: 2025, Volume and Issue: 18(4), P. 854 - 854

Published: Feb. 12, 2025

Renewable energy sources and independence are becoming increasingly important worldwide, reducing emissions optimizing use high on the EU’s agenda. In this context, electric hybrid vehicles could not only be a means of transport but also an active part grid. This paper analyzes one year empirical data vehicle using linear programing method that allows optimization return under different settings. The aim study is to determine contribution can make stability grid functioning communities. It compares distribution used in EU presents current range V2G-capable models. results show effective storage devices, especially at fleet level. V2G technology influence development battery production contribute expansion secondary markets by enabling recycling degraded batteries for buildings or renewable systems. article summarizes opportunities challenges technology, particular its role grids sustainable transport.

Language: Английский

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A hybrid Bayesian network-based deep learning approach combining climatic and reliability factors to forecast electric vehicle charging capacity

Heliyon, Journal Year: 2025, Volume and Issue: 11(4), P. e42483 - e42483

Published: Feb. 1, 2025

Language: Английский

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Harnessing the Power of Large Language Models for Sustainable and Intelligent Transportation Systems in the Electric Vehicle Era

Lecture notes in intelligent transportation and infrastructure, Journal Year: 2025, Volume and Issue: unknown, P. 85 - 113

Published: Jan. 1, 2025

Language: Английский

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ResiDualNet: A novel electric vehicle charging data imputation technique to enhance load forecasting accuracy

Building Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 26, 2025

Language: Английский

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