相关论文: Context-Aware Agentic Power Resources Optimisation…
As electric vehicles (EVs) are increasingly adopted as platforms for connected and automated vehicles (CAVs), enhancing their energy efficiency becomes critical. With the emergence of vehicle-to-vehicle (V2V) communication, cooperative…
This paper presents evS2CP, an optimization-based framework for simultaneous speed and charging planning designed for connected electric vehicles (EVs). With EVs emerging as competitive alternatives to internal combustion engine vehicles,…
We study how high charging rate demands from electric vehicles (EVs) in a power distribution grid may collectively cause poor dynamic performance, and propose a price incentivization strategy to steer customers to settle for lesser charging…
Driven by growing concerns over air quality and energy security, electric vehicles (EVs) has experienced rapid development and are reshaping global transportation systems and lifestyle patterns. Compared to traditional gasoline-powered…
In order to foster electric vehicle (EV) adoption, there is a strong need for designing and developing charging stations that can accommodate different customer classes, distinguished by their charging preferences, needs, and technologies.…
Electric vehicles (EVs) are an eco-friendly alternative to vehicles with internal combustion engines. Despite their environmental benefits, the massive electricity demand imposed by the anticipated proliferation of EVs could jeopardize the…
We study carbon-aware smart charging in a fossil-dominated grid by coupling a simplified hydro-thermal-renewable dispatch model with a tractable linear charging scheduler. The case study is informed by Vietnam's regional data. Thermal units…
The rapid growth of electric vehicles (EVs) requires more effective charging infrastructure planning. Infrastructure layout not only determines deployment cost, but also reshapes charging behavior and influences overall system performance.…
This study presents a hierarchical, network-level traffic flow control framework for mixed traffic consisting of Human-driven Vehicles (HVs), Connected and Automated Vehicles (CAVs). The framework jointly optimizes vehicle-level eco-driving…
Multi-agent large language model (LLM) systems have shown strong potential in complex reasoning and collaborative decision-making tasks. However, most existing coordination schemes rely on static or full-context routing strategies, which…
The rapid electrification of transportation, driven by stringent decarbonization targets and supportive policies, poses significant challenges for distribution system operators (DSOs). When numerous electric vehicles (EVs) charge…
The advancement towards 6G technology leverages improvements in aerial-terrestrial networking, where one of the critical challenges is the efficient allocation of transmit power. Although existing studies have shown commendable performance…
The rapid adoption of electric vehicles (EVs) introduces complex spatiotemporal demand management challenges for charging station operators (CSOs), exacerbated by demand imbalances, behavioral heterogeneity, and system uncertainty.…
The increasing number of Electric Vehicles (EVs) have led to rising energy demands which aggregates the burden on grid supply. A few solutions have been proposed to reduce grid load, for example, using storage systems for storing surplus…
The extraordinary electric vehicle (EV) popularization in the recent years has facilitated research studies in alleviating EV energy charging demand. Previous studies primarily focused on the optimizations over charging stations (CS) profit…
In this paper, we investigate flexible power transfer among electric vehicles (EVs) from a cooperative perspective in an EV system. First, the concept of cooperative EV-to-EV (V2V) charging is introduced, which enables active cooperation…
In recent years, multi-access edge computing (MEC) is a key enabler for handling the massive expansion of Internet of Things (IoT) applications and services. However, energy consumption of a MEC network depends on volatile tasks that…
Coordinating robotic swarms in dynamic and communication-constrained environments remains a fundamental challenge for collective intelligence. This paper presents a novel framework for event-triggered organization, designed to achieve…
In this paper, a distributed trilayer multi-agent framework is proposed for optimal electric vehicle charging scheduling (EVCS). The framework reduces the negative effects of electric vehicle charging demand on the electrical grids. To…
The transition to Electric Vehicles (EVs) demands intelligent, congestion-aware infrastructure planning to balance user convenience, economic viability, and traffic efficiency. We present a joint optimisation framework for EV Charging…