Sizing capacities of renewable generation, transmission, and energy storage for low-carbon power systems: A distributionally robust optimization approach
To decrease carbon dioxide emission, a high penetration level of renewable energy will be
witnessed over the world in the future. By then, energy storage will play an important role in …
witnessed over the world in the future. By then, energy storage will play an important role in …
Photovoltaic sizing assessment for microgrid communities under load shifting constraints and endogenous electricity prices: A Stackelberg approach
Renewable energy resources are crucial for decarbonizing the energy sector. Distributed
energy resources, such as renewable generation by microgrids, aid the transition to net-zero …
energy resources, such as renewable generation by microgrids, aid the transition to net-zero …
The impact of electromobility in public transport: An estimation of energy consumption using disaggregated data in Santiago, Chile
Electromobility in public transport has become a promising way to reduce environmental
pollution. Several contributions have sought to estimate the energy consumption of buses in …
pollution. Several contributions have sought to estimate the energy consumption of buses in …
[HTML][HTML] Multi-agent reinforcement learning for electric vehicle decarbonized routing and scheduling
Low-carbon transitions require joint efforts from electricity grid and transport network, where
electric vehicles (EVs) play a key role. Particularly, EVs can reduce the carbon emissions of …
electric vehicles (EVs) play a key role. Particularly, EVs can reduce the carbon emissions of …
Optimising electric vehicle charging station placement using advanced discrete choice models
S Lamontagne, M Carvalho… - INFORMS Journal …, 2023 - pubsonline.informs.org
We present a new model for finding the optimal placement of electric vehicle charging
stations across a multiperiod time frame so as to maximise electric vehicle adoption. Via the …
stations across a multiperiod time frame so as to maximise electric vehicle adoption. Via the …
Leveraging real-world data sets for qoe enhancement in public electric vehicles charging networks
This work targets enhancing the quality of charging experience in Electric Vehicle (EV)
Public Charging Infrastructure (PCI) networks. The estimation uncertainty of waiting times at …
Public Charging Infrastructure (PCI) networks. The estimation uncertainty of waiting times at …
A long-term congestion management framework through market zone configuration considering collusive bidding in joint spot markets
The zonal market (ZM) adopted in Europe, in contrast to the nodal market (NM), reconciles
the inconsistency between physical networks and administrative management. However, the …
the inconsistency between physical networks and administrative management. However, the …
Distributed electric vehicle assignment and charging navigation in cyber-physical systems
With a large-scale penetration of electric vehicles (EVs) in the transportation sector, it
becomes challenging to guide all EVs heading to the suitable fast-charging stations (FCSs) …
becomes challenging to guide all EVs heading to the suitable fast-charging stations (FCSs) …
Multi-Agent Graph Reinforcement Learning Method for Electric Vehicle on-Route Charging Guidance in Coupled Transportation Electrification
Y Li, S Su, M Zhang, Q Liu, X Nie… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This paper proposes a multi-agent deep graph reinforcement learning-based EV on-route
charging guidance strategy, aiming at minimizing the charging cost for EV drivers in an …
charging guidance strategy, aiming at minimizing the charging cost for EV drivers in an …
[HTML][HTML] Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges
This paper presents a comprehensive and detailed investigation of electric bus transit
systems, focusing on their feasibility in harsh environmental areas. The aspects that …
systems, focusing on their feasibility in harsh environmental areas. The aspects that …