Buchumschlag

Impact of Lead Time on Aggregate EV Flexibility for Congestion Management Services

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Panda, Nanda Kishor, Palensky, Peter, Tindemans, Simon H.
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Systems and Control
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Quantifying the Aggregate Flexibility of Electric Vehicles Charging Stations for Dependable Congestion Management Products -- A Dutch Case Study
von: Panda, Nanda Kishor, et al.
Veröffentlicht: (2024)

Aggregate Peak EV Charging Demand: The Impact of Segmented Network Tariffs
von: Panda, Nanda Kishor, et al.
Veröffentlicht: (2024)

Efficient Quantification and Representation of Aggregate Flexibility in Electric Vehicles
von: Panda, Nanda Kishor, et al.
Veröffentlicht: (2023)

nkpanda97/leadtime-flexibility-tradeoff: Supporting code for the paper: Impact of Lead Time on Aggregate EV Flexibility for Congestion Management Services.
von: Nanda Kishor Panda
Veröffentlicht: (2025)

Stable Training of Probabilistic Models Using the Leave-One-Out Maximum Log-Likelihood Objective
von: Bölat, Kutay, et al.
Veröffentlicht: (2023)

GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments
von: Orfanoudakis, Stavros, et al.
Veröffentlicht: (2025)

Stochastic Mean Field Game for Strategic Bidding of Consumers in Congested Distribution Networks
von: Silani, Amirreza, et al.
Veröffentlicht: (2024)

Risk-Based PV-Rich Distribution System Planning Using Generative AI
von: Kefale, Habtemariam Aberie, et al.
Veröffentlicht: (2026)

Linear Aggregate Model for Realizable Dispatch of Homogeneous Energy Storage
von: Elsaadany, Mazen, et al.
Veröffentlicht: (2025)

Risk-based approach to the Optimal Transmission Switching problem
von: Jeanson, Benoît, et al.
Veröffentlicht: (2025)

Polymatroidal Representations of Aggregate EV Flexibility Considering Network Constraints
von: Mukhi, Karan, et al.
Veröffentlicht: (2025)

Representative Days and Hours with Piecewise Linear Transitions for Power System Planning
von: Moradi-Sepahvand, Mojtaba, et al.
Veröffentlicht: (2023)

Physics-Informed Reinforcement Learning for Large-Scale EV Smart Charging Considering Distribution Network Voltage Constraints
von: Orfanoudakis, Stavros, et al.
Veröffentlicht: (2025)

Coordinated Deliverable Energy Flexibility from EV Aggregators in Distribution Networks
von: Baharvandi, Arash, et al.
Veröffentlicht: (2025)

Scalable quantile predictions of peak loads for non-residential customer segments
von: Shi, Shaohong, et al.
Veröffentlicht: (2025)

One Model to Forecast Them All and in Entity Distributions Bind Them
von: Bölat, Kutay, et al.
Veröffentlicht: (2025)

Scalable Iterative Algorithm for Solving Optimal Transmission Switching with De-energization
von: Jeanson, Benoît, et al.
Veröffentlicht: (2025)

A Compensation Mechanism for EV Flexibility Services using Discrete Utility Functions
von: Giraldo, Juan S., et al.
Veröffentlicht: (2022)

Feedback Enhancement of Time Series Aggregation for Power System Expansion Planning
von: Zhang, Ruiqi, et al.
Veröffentlicht: (2025)

Extreme value distributions of peak loads for non-residential customer segments
von: Shi, Shaohong, et al.
Veröffentlicht: (2025)

Congestion-Sensitive Grid Aggregation for DC Optimal Power Flow
von: Stöckl, Benjamin, et al.
Veröffentlicht: (2025)

Probabilistic Flexibility Aggregation of DERs for Ancillary Services Provision
von: Jacobs, Matthieu, et al.
Veröffentlicht: (2025)

EnergyDiff: Universal Time-Series Energy Data Generation using Diffusion Models
von: Lin, Nan, et al.
Veröffentlicht: (2024)

System-Level Impacts of Flexible Data Center Load Scheduling on Cost, Emissions, and Transmission Congestion
von: Mazumder, Akibul Hasan, et al.
Veröffentlicht: (2026)

Congestion Reduction in EV Charger Placement Using Traffic Equilibrium Models
von: Kara, Semih, et al.
Veröffentlicht: (2025)

Impact of Work Schedule Flexibility on EV Hosting Capacity: Insights from Analyzing Field Data
von: Iorio, Marco, et al.
Veröffentlicht: (2026)

Safe Imitation Learning-based Optimal Energy Storage Systems Dispatch in Distribution Networks
von: Hou, Shengren, et al.
Veröffentlicht: (2024)

Comparative Analysis of Zero-Shot Capability of Time-Series Foundation Models in Short-Term Load Prediction
von: Lin, Nan, et al.
Veröffentlicht: (2024)

Predictive Control of EV Overnight Charging with Multi-Session Flexibility
von: Wieberneit, Felix, et al.
Veröffentlicht: (2025)

Federated Aggregation of Demand Flexibility
von: Dong, Yifan, et al.
Veröffentlicht: (2025)

Distributed Reinforcement Learning using Local Smart Meter Data for Voltage Regulation in Distribution Networks
von: Liu, Dong, et al.
Veröffentlicht: (2025)

Power flow and optimal power flow using quantum and digital annealers: a computational scalability analysis
von: Kaseb, Zeynab, et al.
Veröffentlicht: (2025)

Model-Free Privacy Preserving Power Flow Analysis in Distribution Networks
von: Liu, Dong, et al.
Veröffentlicht: (2025)

Two-Stage Robust Optimal Operation of Distribution Networks Considering Renewable Energy and Demand Asymmetric Uncertainties
von: Xiong, Zhisheng, et al.
Veröffentlicht: (2024)

Risk-Aware Congestion Management with Capacity Limitation Contracts and Redispatch
von: van der Holst, Bart, et al.
Veröffentlicht: (2025)

Optimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks
von: Orfanoudakis, Stavros, et al.
Veröffentlicht: (2025)

Analyzing the Impact of EV Battery Charging on the Distribution Network
von: Aziz, Sahil, et al.
Veröffentlicht: (2026)

Integrated Learning and Optimization for Congestion Management and Profit Maximization in Real-Time Electricity Market
von: Pervez, Imran, et al.
Veröffentlicht: (2024)

Understanding Risk and Revenue in the Nordic 15-minute mFRR market: An EV Aggregation Study
von: Hagström, Theodor, et al.
Veröffentlicht: (2025)

On future power system digital twins: A vision towards a standard architecture
von: Zomerdijk, Wouter, et al.
Veröffentlicht: (2024)