Review on deep learning applications in frequency analysis and control of modern power system

Y Zhang, X Shi, H Zhang, Y Cao, V Terzija - International Journal of …, 2022 - Elsevier
The penetration of renewable energy resources (RES) generation and the interconnection of
regional power grids in wide area and large scale have led the modern power system to …

[HTML][HTML] Reinforcement learning for electric vehicle applications in power systems: A critical review

D Qiu, Y Wang, W Hua, G Strbac - Renewable and Sustainable Energy …, 2023 - Elsevier
Electric vehicles (EVs) are playing an important role in power systems due to their significant
mobility and flexibility features. Nowadays, the increasing penetration of renewable energy …

Operation optimization approaches of electric vehicle battery swap** and charging station: A literature review

D Cui, Z Wang, P Liu, S Wang, DG Dorrell, X Li… - Energy, 2023 - Elsevier
The battery swap** mode (BSM) for an electric vehicle (EV) is an efficient way of
replenishing energy. However, there have been perceived operation-related issues related …

A survey of battery swap** stations for electric vehicles: Operation modes and decision scenarios

H Wu - IEEE Transactions on Intelligent Transportation …, 2021 - ieeexplore.ieee.org
The population of electric vehicles (EVs) has grown rapidly over the past decade due to the
development of EV technologies, battery materials, charger facilities, and public charging …

Electric vehicle charging service operations: A review of machine learning applications for infrastructure planning, control, pricing and routing

N Fescioglu-Unver, MY Aktaş - Renewable and Sustainable Energy …, 2023 - Elsevier
The majority of global road transportation emissions come from passenger and freight
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …

Learning to operate an electric vehicle charging station considering vehicle-grid integration

Z Ye, Y Gao, N Yu - IEEE transactions on smart grid, 2022 - ieeexplore.ieee.org
The rapid adoption of electric vehicles (EVs) calls for the widespread installation of EV
charging stations. To maximize the profitability of charging stations, intelligent controllers …

Deep-reinforcement-learning-based capacity scheduling for PV-battery storage system

B Huang, J Wang - IEEE Transactions on Smart Grid, 2020 - ieeexplore.ieee.org
Investor-owned photovoltaic-battery storage systems (PV-BSS) can gain revenue by
providing stacked services, including PV charging and frequency regulation, and by …

Application of artificial intelligence for EV charging and discharging scheduling and dynamic pricing: A review

Q Chen, KA Folly - Energies, 2022 - mdpi.com
The high penetration of electric vehicles (EVs) will burden the existing power delivery
infrastructure if their charging and discharging are not adequately coordinated. Dynamic …

Coordinated electric vehicle active and reactive power control for active distribution networks

Y Wang, D Qiu, G Strbac, Z Gao - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The deployment of renewable energy in power systems may raise serious voltage
instabilities. Electric vehicles (EVs), owing to their mobility and flexibility characteristics, can …

Two-stage self-scheduling of battery swap** station in day-ahead energy and frequency regulation markets

C Wu, X Lin, Q Sui, Z Wang, Z Feng, Z Li - Applied Energy, 2021 - Elsevier
Battery swap** stations (BSS) face two major problems in the frequency regulation
market: 1) battery degradation cost with the effect of regulation, and 2) the uncertainties in …