Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods
Fuente:
arXiv
Saved in:
| Main Authors: | Kyriakopoulos, Iason, Theodoridis, Yannis |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On Electric Vehicle Energy Demand Forecasting and the Effect of Federated Learning
by: Tritsarolis, Andreas, et al.
Published: (2026)
by: Tritsarolis, Andreas, et al.
Published: (2026)
Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting
by: Tziorvas, Antonios, et al.
Published: (2026)
by: Tziorvas, Antonios, et al.
Published: (2026)
On Vessel Location Forecasting and the Effect of Federated Learning
by: Tritsarolis, Andreas, et al.
Published: (2024)
by: Tritsarolis, Andreas, et al.
Published: (2024)
MoDE-Boost: Boosting Shared Mobility Demand with Edge-Ready Prediction Models
by: Tziorvas, Antonios, et al.
Published: (2026)
by: Tziorvas, Antonios, et al.
Published: (2026)
Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations
by: Zhang, Zongbao, et al.
Published: (2024)
by: Zhang, Zongbao, et al.
Published: (2024)
Coherent Hierarchical Probabilistic Forecasting of Electric Vehicle Charging Demand
by: Zheng, Kedi, et al.
Published: (2024)
by: Zheng, Kedi, et al.
Published: (2024)
FLP-XR: Future Location Prediction on Extreme Scale Maritime Data in Real-time
by: Theodoropoulos, George S., et al.
Published: (2025)
by: Theodoropoulos, George S., et al.
Published: (2025)
Forecasting Electric Vehicle Charging Station Occupancy: Smarter Mobility Data Challenge
by: Amara-Ouali, Yvenn, et al.
Published: (2023)
by: Amara-Ouali, Yvenn, et al.
Published: (2023)
A Scientific Machine Learning Approach for Predicting and Forecasting Battery Degradation in Electric Vehicles
by: Murgai, Sharv, et al.
Published: (2024)
by: Murgai, Sharv, et al.
Published: (2024)
A Generative Model Enhanced Multi-Agent Reinforcement Learning Method for Electric Vehicle Charging Navigation
by: Qi, Tianyang, et al.
Published: (2025)
by: Qi, Tianyang, et al.
Published: (2025)
Graph Neural Networks for Electricity Load Forecasting
by: Campagne, Eloi, et al.
Published: (2025)
by: Campagne, Eloi, et al.
Published: (2025)
Deriving Hematological Disease Classes Using Fuzzy Logic and Expert Knowledge: A Comprehensive Machine Learning Approach with CBC Parameters
by: Ameen, Salem, et al.
Published: (2024)
by: Ameen, Salem, et al.
Published: (2024)
Electrical Load Forecasting over Multihop Smart Metering Networks with Federated Learning
by: Rahman, Ratun, et al.
Published: (2025)
by: Rahman, Ratun, et al.
Published: (2025)
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
by: Dehrouyeh, Fatemeh, et al.
Published: (2025)
by: Dehrouyeh, Fatemeh, et al.
Published: (2025)
Out-of-Distribution-Aware Electric Vehicle Charging
by: Li, Tongxin, et al.
Published: (2023)
by: Li, Tongxin, et al.
Published: (2023)
Anomaly Detection in Electric Vehicle Charging Stations Using Federated Learning
by: C, Bishal K, et al.
Published: (2025)
by: C, Bishal K, et al.
Published: (2025)
DiffLoad: Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Model
by: Wang, Zhixian, et al.
Published: (2023)
by: Wang, Zhixian, et al.
Published: (2023)
Short-Term Electricity-Load Forecasting by Deep Learning: A Comprehensive Survey
by: Dong, Qi, et al.
Published: (2024)
by: Dong, Qi, et al.
Published: (2024)
Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach
by: Rahman, Ratun, et al.
Published: (2024)
by: Rahman, Ratun, et al.
Published: (2024)
Explainable Anomaly Detection for Electric Vehicles Charging Stations
by: Cederle, Matteo, et al.
Published: (2025)
by: Cederle, Matteo, et al.
Published: (2025)
Optimizing Electric Vehicle Charging Station Placement Using Reinforcement Learning and Agent-Based Simulations
by: Nguyen, Minh-Duc, et al.
Published: (2025)
by: Nguyen, Minh-Duc, et al.
Published: (2025)
Load Forecasting on A Highly Sparse Electrical Load Dataset Using Gaussian Interpolation
by: Biswas, Chinmoy, et al.
Published: (2025)
by: Biswas, Chinmoy, et al.
Published: (2025)
Forecasting Day-Ahead Electricity Prices in the Integrated Single Electricity Market: Addressing Volatility with Comparative Machine Learning Methods
by: Harkin, Ben, et al.
Published: (2024)
by: Harkin, Ben, et al.
Published: (2024)
TriForecaster: A Mixture of Experts Framework for Multi-Region Electric Load Forecasting with Tri-dimensional Specialization
by: Zhu, Zhaoyang, et al.
Published: (2025)
by: Zhu, Zhaoyang, et al.
Published: (2025)
Load Forecasting in the Era of Smart Grids: Opportunities and Advanced Machine Learning Models
by: Maneshni, Aurausp
Published: (2025)
by: Maneshni, Aurausp
Published: (2025)
Machine Learning and Deep Learning Models for Short Term Electricity Price Forecasting in Australia's National Electricity Market
by: Lu, Wei, et al.
Published: (2026)
by: Lu, Wei, et al.
Published: (2026)
Going Beyond Expert Performance via Deep Implicit Imitation Reinforcement Learning
by: Chrysomallis, Iason, et al.
Published: (2025)
by: Chrysomallis, Iason, et al.
Published: (2025)
Addressing Challenges in Time Series Forecasting: A Comprehensive Comparison of Machine Learning Techniques
by: Mortezanejad, Seyedeh Azadeh Fallah, et al.
Published: (2025)
by: Mortezanejad, Seyedeh Azadeh Fallah, et al.
Published: (2025)
Profiling Electric Vehicles via Early Charging Voltage Patterns
by: Marchiori, Francesco, et al.
Published: (2025)
by: Marchiori, Francesco, et al.
Published: (2025)
Forecasting Anonymized Electricity Load Profiles
by: Fernandez, Joaquin Delgado, et al.
Published: (2025)
by: Fernandez, Joaquin Delgado, et al.
Published: (2025)
Deep Reinforcement Learning-Based Optimization of Second-Life Battery Utilization in Electric Vehicles Charging Stations
by: Haghighi, Rouzbeh, et al.
Published: (2025)
by: Haghighi, Rouzbeh, et al.
Published: (2025)
Divide-Conquer Transformer Learning for Predicting Electric Vehicle Charging Events Using Smart Meter Data
by: Ke, Fucai, et al.
Published: (2024)
by: Ke, Fucai, et al.
Published: (2024)
Explainability-Driven Feature Engineering for Mid-Term Electricity Load Forecasting in ERCOT's SCENT Region
by: Bhupatiraju, Abhiram, et al.
Published: (2025)
by: Bhupatiraju, Abhiram, et al.
Published: (2025)
Using Low-Discrepancy Points for Data Compression in Machine Learning: An Experimental Comparison
by: Göttlich, Simone, et al.
Published: (2024)
by: Göttlich, Simone, et al.
Published: (2024)
A Comparative Study of Machine Learning Algorithms for Electricity Price Forecasting with LIME-Based Interpretability
by: Zhao, Xuanyi, et al.
Published: (2025)
by: Zhao, Xuanyi, et al.
Published: (2025)
Water and Electricity Consumption Forecasting at an Educational Institution using Machine Learning models with Metaheuristic Optimization
by: Alba, Eduardo Luiz, et al.
Published: (2024)
by: Alba, Eduardo Luiz, et al.
Published: (2024)
Modeling Electric Vehicle Car-Following Behavior: Classical vs Machine Learning Approach
by: Uddin, Md. Shihab, et al.
Published: (2025)
by: Uddin, Md. Shihab, et al.
Published: (2025)
Task-Aware Machine Unlearning and Its Application in Load Forecasting
by: Xu, Wangkun, et al.
Published: (2023)
by: Xu, Wangkun, et al.
Published: (2023)
Imitation Learning in the Deep Learning Era: A Novel Taxonomy and Recent Advances
by: Chrysomallis, Iason, et al.
Published: (2025)
by: Chrysomallis, Iason, et al.
Published: (2025)
Adaptive Ensemble Learning with Gaussian Copula for Load Forecasting
by: Yang, Junying, et al.
Published: (2025)
by: Yang, Junying, et al.
Published: (2025)
Similar Items
-
On Electric Vehicle Energy Demand Forecasting and the Effect of Federated Learning
by: Tritsarolis, Andreas, et al.
Published: (2026) -
Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting
by: Tziorvas, Antonios, et al.
Published: (2026) -
On Vessel Location Forecasting and the Effect of Federated Learning
by: Tritsarolis, Andreas, et al.
Published: (2024) -
MoDE-Boost: Boosting Shared Mobility Demand with Edge-Ready Prediction Models
by: Tziorvas, Antonios, et al.
Published: (2026) -
Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations
by: Zhang, Zongbao, et al.
Published: (2024)