Related papers: V2Sim: An Open-Source Microscopic V2G Simulation P…
Fluctuations in electricity tariffs induced by the sporadic nature of demand loads on power grids has initiated immense efforts to find optimal scheduling solutions for charging and discharging plug-in electric vehicles (PEVs) subject to…
Forecasting the flexibility potential of Vehicle-to-Everything (V2X) systems is important for the future of energy networks, where the integration of renewable energy sources and electric vehicles poses significant challenges. In this…
The rapid growth of EVs and the subsequent increase in charging demand pose significant challenges for load grid scheduling and the operation of EV charging stations. Effectively harnessing the spatiotemporal correlations among EV charging…
Testing cloud-controlled intelligent connected vehicles (ICVs) requires simulation environments that faithfully emulate both vehicle behavior and realistic communication latencies. This paper proposes a latency-aware co-simulation platform…
With the increasing of electric vehicle (EV) adoption in recent years, the impact of EV charging activities to the power grid becomes more and more significant. In this article, an optimal scheduling algorithm which combines smart EV…
The rapid expansion of electric vehicles (EVs) has rendered the load forecasting of electric vehicle charging stations (EVCS) increasingly critical. The primary challenge in achieving precise load forecasting for EVCS lies in accounting for…
Due to various green initiatives, renewable energy will be massively incorporated into the future smart grid. However, the intermittency of the renewables may result in power imbalance, thus adversely affecting the stability of a power…
Simultaneous Localization and Mapping (SLAM) technology has been widely applied in various robotic scenarios, from rescue operations to autonomous driving. However, the generalization of SLAM algorithms remains a significant challenge, as…
The power grid is the foundation of modern society, however extreme weather events have increasingly caused widespread outages. Enhancing grid resilience is therefore critical to maintaining secure and reliable operations. In disaster…
The provision of reliable and efficient communication is a key requirement for the deployment of autonomous cars as well as for future Intelligent Transportation Systems (ITSs) in smart cities. Novel communications technologies will have to…
The increasing adoption of electric vehicles has spurred significant interest in Vehicle-to-Grid technology as a transformative approach to modern energy systems. This paper presents a systematic review of V2G systems, focusing on their…
Sim-to-real gap has long posed a significant challenge for robot learning in simulation, preventing the deployment of learned models in the real world. Previous work has primarily focused on domain randomization and system identification to…
This paper presents optimization models for electric Mobility-as-a-Service systems, whereby electric vehicles not only provide on-demand mobility, but also perform charging and Vehicle-to-Grid (V2G) operations to enhance the fleet operator…
Vehicle-to-everything (V2X) is a modern vehicular technology that improves conventional vehicle systems in traffic and communications. V2X communications demand energyefficient and high-reliability networking because of massive vehicular…
Mobile energy storage devices (MESDs) operate as medium- or large-sized batteries that can be loaded onto electric trucks and connected to charging stations to provide various ancillary services for distribution grids. This paper proposes a…
This paper presents an enhanced electric vehicle demand response system based on large language models, aimed at optimizing the application of vehicle-to-grid technology. By leveraging an large language models-driven multi-agent framework…
This paper presents a framework for processing EV charging load data in order to forecast future load predictions using a Recurrent Neural Network, specifically an LSTM. The framework processes a large set of raw data from multiple…
Traffic propagation simulation is crucial for urban planning, enabling congestion analysis, travel time estimation, and route optimization. Traditional micro-simulation frameworks are limited to main roads due to the complexity of urban…
As the realization of vehicular communication such as vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) is imperative for the autonomous driving cars, the understanding of realistic vehicle-to-everything (V2X) models is needed.…
Deploying real-time control on large-scale fleets of electric vehicles (EVs) is becoming pivotal as the share of EVs over internal combustion engine vehicles increases. In this paper, we present a Vehicle-to-Grid (V2G) algorithm to…