Multi-period charging infrastructure planning under uncertainty: Challenges and opportunities

Q Ye, P Bansal, B Adey - Sustainable Cities and Society, 2024 - Elsevier
Long-term charging infrastructure planning is imperative to sustain the rapid adoption of
electric vehicles (EVs) in line with climate goals. While the literature on spatial planning of …

Routing and scheduling of mobile power sources for distribution system resilience enhancement

S Lei, C Chen, H Zhou, Y Hou - IEEE Transactions on Smart …, 2018 - ieeexplore.ieee.org
Mobile power sources (MPSs), including electric vehicle fleets, truck-mounted mobile energy
storage systems, and mobile emergency generators, have great potential to enhance …

Photovoltaic power forecasting with a hybrid deep learning approach

G Li, S Xie, B Wang, J Xin, Y Li, S Du - IEEE access, 2020 - ieeexplore.ieee.org
Solar energy is the key to clean energy, which can generate large amounts of electricity for
the future smart grid. Unfortunately, the randomness and intermittency of solar energy …

Deterministic and probabilistic forecasting of photovoltaic power based on deep convolutional neural network

H Wang, H Yi, J Peng, G Wang, Y Liu, H Jiang… - Energy conversion and …, 2017 - Elsevier
The penetration of photovoltaic (PV) energy into modern electric power and energy systems
has been gradually increased in recent years due to its benefits of being abundant …

Deep-learning-based probabilistic forecasting of electric vehicle charging load with a novel queuing model

X Zhang, KW Chan, H Li, H Wang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
With the emerging electric vehicle (EV) and fast charging technologies, EV load forecasting
has become a concern for planners and operators of EV charging stations (CSs). Due to the …

Recurrent neural networks based photovoltaic power forecasting approach

G Li, H Wang, S Zhang, J Xin, H Liu - Energies, 2019 - mdpi.com
The intermittency of solar energy resources has brought a big challenge for the optimization
and planning of a future smart grid. To reduce the intermittency, an accurate prediction of …

Deep belief network based ensemble approach for cooling load forecasting of air-conditioning system

G Fu - Energy, 2018 - Elsevier
Due to the high energy consumption in buildings, cooling load forecasting plays a crucial
role in the planning, control and operation of heating, ventilating and air-conditioning …

Collaborative planning of regional integrated energy system in the era of EV penetration: A comprehensive review

Q Yang, Y Ruan, F Qian, H Meng, Y Yao, T Xu… - Sustainable Cities and …, 2024 - Elsevier
The widespread adoption of electric vehicles (EVs) significantly increases the uncertainty
and complexity of regional integrated energy system (RIES), leading to substantial changes …

Electric vehicle charging station planning with dynamic prediction of elastic charging demand: A hybrid particle swarm optimization algorithm

X Bai, Z Wang, L Zou, H Liu, Q Sun… - Complex & Intelligent …, 2022 - Springer
This paper is concerned with the electric vehicle (EV) charging station planning problem
based on the dynamic charging demand. Considering the dynamic charging behavior of EV …

Economic planning approach for electric vehicle charging stations integrating traffic and power grid constraints

X Huang, J Chen, H Yang, Y Cao… - IET generation …, 2018 - Wiley Online Library
Large‐scale electric vehicle (EV) charging will bring new challenges to coordination of grid
and transportation. To facilitate large‐scale EV applications, optimal locating and sizing of …