Research graph
References from Risk-aware probabilistic EV parking time forecasting for operationally robust V2G scheduling. Local targets link to admitted publications; unresolved targets remain external evidence.
Energy transition towards electric vehicle technology: recent advancements
10.1016/j.egyr.2025.02.029 · 2025 · External reference
Global EV outlook 2023: catching up with climate ambitions
10.1787/cbe724e8-en · 2023 · External reference
Electric vehicle charging optimization to minimize marginal greenhouse gas emissions from power generation
10.1016/j.apenergy.2020.115517 · 2020 · External reference
EV smart charging: how tariff selection influences grid stress and carbon reduction
10.1016/j.apenergy.2023.121482 · 2023 · External reference
Optimal E-fleet charging station design with V2G capability
2023 · External reference
Bidding strategies in energy and reserve markets for an aggregator of multiple EV fast charging stations with battery storage
10.1109/tits.2020.3019608 · 2021 · External reference
Adaptive co-planning of building-integrated photovoltaics and vehicle-to-grid infrastructure under phase-out policy incentives: a two-stage multi-objective optimization framework
10.1016/j.apenergy.2026.127981 · 2026 · External reference
Integration of wind and solar power in Europe: assessment of flexibility requirements
10.1016/j.energy.2014.02.109 · 2014 · External reference
Flexibility potential of electric vehicle charging: a trip chain analysis under bi-criterion stochastic dynamic user equilibrium
10.1016/j.adapen.2025.100240 · 2025 · External reference
Spatial-temporal graph convolutional-based recurrent network for electric vehicle charging stations demand forecasting in energy market
10.1109/tsg.2024.3368419 · 2024 · External reference
A review on hybrid electric vehicles architecture and energy management strategies
10.1016/j.rser.2015.09.036 · 2016 · External reference
Adaptive charging networks: a framework for smart electric vehicle charging
10.1109/tsg.2021.3074437 · 2021 · External reference
Review of real-time electricity markets for integrating distributed energy resources and demand response
10.1016/j.apenergy.2014.10.048 · 2015 · External reference
Dynamic rolling horizon optimization for network-constrained V2X value stacking of electric vehicles under uncertainties
10.1016/j.renene.2025.122668 · 2025 · External reference
Optimal dispatch of a multi-energy system microgrid under uncertainty: a renewable energy community in Austria
10.1016/j.apenergy.2023.120913 · 2023 · External reference
Prediction of EV charging behavior using machine learning
10.1109/access.2021.3103119 · 2021 · External reference
Prediction of electric vehicle charging duration time using ensemble machine learning algorithm and Shapley additive explanations
10.1002/er.8219 · 2022 · External reference
Unresolved reference
2021 · External reference
Improving smart charging prioritization by predicting electric vehicle departure time
10.1109/tits.2020.2988648 · 2021 · External reference
Unresolved reference
2019 · External reference
Unresolved reference
2024 · External reference
An equivalent time-variant storage model to harness EV flexibility: forecast and aggregation
10.1109/tii.2018.2865433 · 2019 · External reference
Unresolved reference
2018 · External reference
Charging demand of plug-in electric vehicles: forecasting travel behavior based on a novel rough artificial neural network approach
10.1016/j.jclepro.2019.04.345 · 2019 · External reference
Unresolved reference
2024 · External reference
Day-ahead capacity estimation and power management of a charging station based on queuing theory
10.1109/tii.2019.2906650 · 2019 · External reference
Boosting grid efficiency and resiliency by releasing V2G potentiality through a novel rolling prediction-decision framework and deep-LSTM algorithm
10.1109/jsyst.2020.3001630 · 2021 · External reference
Electric vehicle charging demand forecasting using deep learning model
10.1080/15472450.2021.1966627 · 2022 · External reference
Day-ahead prediction of electric vehicle charging demand based on quadratic decomposition and dual attention mechanisms
10.1016/j.apenergy.2024.125198 · 2025 · External reference
Electric vehicles plug-in duration forecasting using machine learning for battery optimization
10.3390/en13164208 · 2020 · External reference
Ensemble machine learning-based algorithm for electric vehicle user behavior prediction
10.1016/j.apenergy.2019.113732 · 2019 · External reference
Forecasting flexibility of charging of electric vehicles: tree and cluster-based methods
10.1016/j.apenergy.2023.121969 · 2024 · External reference
Probabilistic forecasts of time and energy flexibility in battery electric vehicle charging
10.1016/j.apenergy.2020.114525 · 2020 · External reference
Online learning models for vehicle usage prediction during COVID-19
10.1109/tits.2024.3361676 · 2024 · External reference
Customized uncertainty quantification of parking duration predictions for EV smart charging
10.1109/jiot.2023.3299201 · 2023 · External reference
Support vector regression with asymmetric loss for optimal electric load forecasting
10.1016/j.energy.2021.119969 · 2021 · External reference
A reliable evaluation metric for electrical load forecasts in V2G scheduling considering statistical features of EV charging
10.1109/tsg.2024.3392910 · 2024 · External reference
Value-oriented data-driven approach for electrical load forecasting apt to facilitate vehicle-to-grid scheduling
10.1109/tii.2025.3552704 · 2025 · External reference
Unresolved reference
2022 · External reference
Hybrid machine learning forecasting for online MPC of work place electric vehicle charging
10.1109/tsg.2023.3296014 · 2024 · External reference
Integrated deep learning framework for electric vehicles’ flexibility forecasting and optimal dispatch
10.1016/j.apenergy.2026.127821 · 2026 · External reference
Unresolved reference
2012 · External reference
Comparison of electric vehicle load forecasting across different spatial levels with incorporated uncertainty estimation
10.1016/j.energy.2023.129213 · 2023 · External reference
Regression quantiles
10.2307/1913643 · 1978 · External reference
An efficient k-means clustering algorithm: analysis and implementation
10.1109/tpami.2002.1017616 · 2002 · External reference
Deep learning framework for day-ahead optimal charging scheduling of electric vehicles in parking lot
10.1016/j.apenergy.2023.121614 · 2023 · External reference
A practical scheme to involve degradation cost of Lithium-ion batteries in vehicle-to-grid applications
10.1109/tste.2016.2558500 · 2016 · External reference
A method for generating complete EV charging datasets and analysis of residential charging behaviour in a large Norwegian case study
2023 · External reference
A review of feature selection methods based on mutual information
10.1007/s00521-013-1368-0 · 2014 · External reference
Efficient agglomerative hierarchical clustering
10.1016/j.eswa.2014.09.054 · 2015 · External reference
A robust EM clustering algorithm for gaussian mixture models
10.1016/j.patcog.2012.04.031 · 2012 · External reference
DBSCAN revisited, revisited: why and how you should (still) use DBSCAN
10.1145/3068335 · 2017 · External reference
Unresolved reference
2020 · External reference
An improved index for clustering validation based on Silhouette index and Calinski-Harabasz index
10.1088/1757-899x/569/5/052024 · 2019 · External reference
Hybrid inception-embedded deep neural network ResNet for short and medium-term PV-wind forecasting
2023 · External reference
Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture
10.1016/j.apenergy.2023.121607 · 2023 · External reference
A systematic review for transformer-based long-term series forecasting
10.1007/s10462-024-11044-2 · 2025 · External reference
Unresolved reference
External reference
Tracking emissions in the US electricity system
10.1073/pnas.1912950116 · 2019 · External reference
Economic efficiency of alternative border carbon adjustment schemes: a case study of California carbon pricing and the Western North American power market
10.1016/j.enpol.2021.112463 · 2021 · External reference
Do notifications affect households’ willingness to pay to avoid power outages? Evidence from an experimental stated-preference survey in California
10.1016/j.tej.2024.107385 · 2024 · External reference
Prediction of electric vehicle charging duration time using ensemble machine learning algorithm and Shapley additive explanations
10.1002/er.8219 · ExternalCitation · doi-reference
A review of feature selection methods based on mutual information
10.1007/s00521-013-1368-0 · ExternalCitation · doi-reference
A systematic review for transformer-based long-term series forecasting
10.1007/s10462-024-11044-2 · ExternalCitation · doi-reference
Flexibility potential of electric vehicle charging: a trip chain analysis under bi-criterion stochastic dynamic user equilibrium
10.1016/j.adapen.2025.100240 · ExternalCitation · doi-reference
Review of real-time electricity markets for integrating distributed energy resources and demand response
10.1016/j.apenergy.2014.10.048 · ExternalCitation · doi-reference
Ensemble machine learning-based algorithm for electric vehicle user behavior prediction
10.1016/j.apenergy.2019.113732 · ExternalCitation · doi-reference
Probabilistic forecasts of time and energy flexibility in battery electric vehicle charging
10.1016/j.apenergy.2020.114525 · ExternalCitation · doi-reference
Electric vehicle charging optimization to minimize marginal greenhouse gas emissions from power generation
10.1016/j.apenergy.2020.115517 · ExternalCitation · doi-reference
Optimal dispatch of a multi-energy system microgrid under uncertainty: a renewable energy community in Austria
10.1016/j.apenergy.2023.120913 · ExternalCitation · doi-reference
EV smart charging: how tariff selection influences grid stress and carbon reduction
10.1016/j.apenergy.2023.121482 · ExternalCitation · doi-reference
Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture
10.1016/j.apenergy.2023.121607 · ExternalCitation · doi-reference
Deep learning framework for day-ahead optimal charging scheduling of electric vehicles in parking lot
10.1016/j.apenergy.2023.121614 · ExternalCitation · doi-reference
Forecasting flexibility of charging of electric vehicles: tree and cluster-based methods
10.1016/j.apenergy.2023.121969 · ExternalCitation · doi-reference
Day-ahead prediction of electric vehicle charging demand based on quadratic decomposition and dual attention mechanisms
10.1016/j.apenergy.2024.125198 · ExternalCitation · doi-reference
Integrated deep learning framework for electric vehicles’ flexibility forecasting and optimal dispatch
10.1016/j.apenergy.2026.127821 · ExternalCitation · doi-reference
Adaptive co-planning of building-integrated photovoltaics and vehicle-to-grid infrastructure under phase-out policy incentives: a two-stage multi-objective optimization framework
10.1016/j.apenergy.2026.127981 · ExternalCitation · doi-reference
Energy transition towards electric vehicle technology: recent advancements
10.1016/j.egyr.2025.02.029 · ExternalCitation · doi-reference
Integration of wind and solar power in Europe: assessment of flexibility requirements
10.1016/j.energy.2014.02.109 · ExternalCitation · doi-reference
Support vector regression with asymmetric loss for optimal electric load forecasting
10.1016/j.energy.2021.119969 · ExternalCitation · doi-reference
Comparison of electric vehicle load forecasting across different spatial levels with incorporated uncertainty estimation
10.1016/j.energy.2023.129213 · ExternalCitation · doi-reference
Economic efficiency of alternative border carbon adjustment schemes: a case study of California carbon pricing and the Western North American power market
10.1016/j.enpol.2021.112463 · ExternalCitation · doi-reference
Efficient agglomerative hierarchical clustering
10.1016/j.eswa.2014.09.054 · ExternalCitation · doi-reference
Charging demand of plug-in electric vehicles: forecasting travel behavior based on a novel rough artificial neural network approach
10.1016/j.jclepro.2019.04.345 · ExternalCitation · doi-reference
A robust EM clustering algorithm for gaussian mixture models
10.1016/j.patcog.2012.04.031 · ExternalCitation · doi-reference
Dynamic rolling horizon optimization for network-constrained V2X value stacking of electric vehicles under uncertainties
10.1016/j.renene.2025.122668 · ExternalCitation · doi-reference
A review on hybrid electric vehicles architecture and energy management strategies
10.1016/j.rser.2015.09.036 · ExternalCitation · doi-reference
Do notifications affect households’ willingness to pay to avoid power outages? Evidence from an experimental stated-preference survey in California
10.1016/j.tej.2024.107385 · ExternalCitation · doi-reference
Tracking emissions in the US electricity system
10.1073/pnas.1912950116 · ExternalCitation · doi-reference
Electric vehicle charging demand forecasting using deep learning model
10.1080/15472450.2021.1966627 · ExternalCitation · doi-reference
An improved index for clustering validation based on Silhouette index and Calinski-Harabasz index
10.1088/1757-899x/569/5/052024 · ExternalCitation · doi-reference
Prediction of EV charging behavior using machine learning
10.1109/access.2021.3103119 · ExternalCitation · doi-reference
Customized uncertainty quantification of parking duration predictions for EV smart charging
10.1109/jiot.2023.3299201 · ExternalCitation · doi-reference
Boosting grid efficiency and resiliency by releasing V2G potentiality through a novel rolling prediction-decision framework and deep-LSTM algorithm
10.1109/jsyst.2020.3001630 · ExternalCitation · doi-reference
An equivalent time-variant storage model to harness EV flexibility: forecast and aggregation
10.1109/tii.2018.2865433 · ExternalCitation · doi-reference
Day-ahead capacity estimation and power management of a charging station based on queuing theory
10.1109/tii.2019.2906650 · ExternalCitation · doi-reference
Value-oriented data-driven approach for electrical load forecasting apt to facilitate vehicle-to-grid scheduling
10.1109/tii.2025.3552704 · ExternalCitation · doi-reference
Improving smart charging prioritization by predicting electric vehicle departure time
10.1109/tits.2020.2988648 · ExternalCitation · doi-reference
Bidding strategies in energy and reserve markets for an aggregator of multiple EV fast charging stations with battery storage
10.1109/tits.2020.3019608 · ExternalCitation · doi-reference
Online learning models for vehicle usage prediction during COVID-19
10.1109/tits.2024.3361676 · ExternalCitation · doi-reference
An efficient k-means clustering algorithm: analysis and implementation
10.1109/tpami.2002.1017616 · ExternalCitation · doi-reference
Adaptive charging networks: a framework for smart electric vehicle charging
10.1109/tsg.2021.3074437 · ExternalCitation · doi-reference
Hybrid machine learning forecasting for online MPC of work place electric vehicle charging
10.1109/tsg.2023.3296014 · ExternalCitation · doi-reference
Spatial-temporal graph convolutional-based recurrent network for electric vehicle charging stations demand forecasting in energy market
10.1109/tsg.2024.3368419 · ExternalCitation · doi-reference
A reliable evaluation metric for electrical load forecasts in V2G scheduling considering statistical features of EV charging
10.1109/tsg.2024.3392910 · ExternalCitation · doi-reference
A practical scheme to involve degradation cost of Lithium-ion batteries in vehicle-to-grid applications
10.1109/tste.2016.2558500 · ExternalCitation · doi-reference
DBSCAN revisited, revisited: why and how you should (still) use DBSCAN
10.1145/3068335 · ExternalCitation · doi-reference
Global EV outlook 2023: catching up with climate ambitions
10.1787/cbe724e8-en · ExternalCitation · doi-reference
Regression quantiles
10.2307/1913643 · ExternalCitation · doi-reference
Electric vehicles plug-in duration forecasting using machine learning for battery optimization
10.3390/en13164208 · ExternalCitation · doi-reference
