Related papers: Bilevel Optimization for Improved Flexibility Aggr…
Accurately evaluating the real-time flexibility of electric vehicles (EVs) is necessary for EV aggregators to offer ancillary services. However, regulation-caused uncertain state-of-charge and random departure behavior complicate the…
Combinatorial distribution system optimization problems, such as scheduling electric vehicle (EV) charging during evacuations, present significant computational challenges. These challenges stem from the large numbers of constraints,…
This paper proposes a framework for the procurement of flexibility reserve from aggregated storage fleets. It allows for arbitrary tree structures of aggregation hierarchy, as well as easily implementable disaggregation via broadcast…
We study electric vehicle (EV) fleet and charging infrastructure planning in a spatial setting. With customer requests arriving continuously at rate $\lambda$ throughout the day, we determine the minimum number of vehicles and chargers for…
Shared electric vehicles (SEVs) have emerged as a promising solution to contribute to sustainable urban mobility. However, ensuring the efficient operation and effective battery management of SEV systems remains a complex challenge. This…
Decarbonisation, decentralisation, and intermittency are driving the development of flexibility markets towards shorter market time units (MTU). Shorter MTUs and shorter gate closures lower the entrance barriers of demand side aggregators…
This paper considers an aggregator of Electric Vehicles (EVs) who aims to learn the aggregate power of his/her fleet while also participating in the electricity market. The proposed approach is based on a data-driven inverse optimization…
The advent of autonomous driving and electrification is enabling the deployment of Electric Autonomous Mobility-on-Demand (E-AMoD) systems, whereby electric autonomous vehicles provide on-demand mobility. Crucially, the design of the…
The widespread adoption of electric vehicles (EVs) has significantly increased demand on both transportation and power systems, posing challenges to their stable operation. To support the growing need for EV charging, both fixed charging…
We propose a simple empirical scaling law that describes load forecasting accuracy at different levels of aggregation. The model is justified based on a simple decomposition of individual consumption patterns. We show that for different…
In this paper, we introduce a quantitative framework to optimize electric vehicle (EV) battery capacities, considering two criteria: upfront vehicle cost and charging inconvenience cost. For this purpose, we (1) develop a comprehensive…
An increase in greenhouse gases emission from the transportation sector has led companies and the government to elevate and support the production of electric vehicles (EV). With recent developments in urbanization and e-commerce,…
Electric vehicles (EVs) and renewable energy sources (RES) are vital components of sustainable energy systems, yet their uncoordinated integration can pose substantial challenges to grid stability, such as unmanaged peak loads and energy…
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…
With the rising popularity of electric vehicles (EVs), modern service systems, such as ride-hailing delivery services, are increasingly integrating EVs into their operations. Unlike conventional vehicles, EVs often have a shorter driving…
This paper explores the impact of electric vehicles (EVs) on traffic congestion and energy consumption by proposing an integrated bi-level framework comprising of: a) a dynamic micro-scale traffic simulation suitable for modelling current…
The increasing penetration of electric vehicles (EVs) can provide substantial electricity to the grid, supporting the grids' stability. The state space model (SSM) has been proposed as an effective modeling method for power prediction and…
The first of this two-paper series proposes and elaborates a concept of electric vehicle (EV)-based e-mobility system. To this end, models designed to reap the benefits of EVs' flexibility in the literature almost exclusively consider…
In this paper, we propose a robust optimization model that addresses both the cost-efficiency and fast charging requirements for electric vehicles (EVs) at charging stations. By combining elements from traditional cost-minimization models…
Electrical vehicle (EV) raises to promote an eco-sustainable society. Nevertheless, the "range anxiety" of EV hinders its wider acceptance among customers. This paper proposes a novel solution to range anxiety based on a federated-learning…