[HTML][HTML] Demand side management of electric vehicles in smart grids: A survey on strategies, challenges, modeling, and optimization

S Mohanty, S Panda, SM Parida, PK Rout, BK Sahu… - Energy Reports, 2022 - Elsevier
The shift of transportation technology from internal combustion engine (ICE) based vehicles
to electric vehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater …

[HTML][HTML] Assessment of charging technologies, infrastructure and charging station recommendation schemes of electric vehicles: A review

GF Savari, MJ Sathik, LA Raman, A El-Shahat… - Ain Shams Engineering …, 2023 - Elsevier
This article comprehensively reviews recent Electric Vehicle (EV) charging infrastructure,
technology, and issues related to charging station identification. A literature study on the …

Reinforcement learning for demand response: A review of algorithms and modeling techniques

JR Vázquez-Canteli, Z Nagy - Applied energy, 2019 - Elsevier
Buildings account for about 40% of the global energy consumption. Renewable energy
resources are one possibility to mitigate the dependence of residential buildings on the …

Reinforcement learning based EV charging management systems–a review

HM Abdullah, A Gastli, L Ben-Brahim - IEEE Access, 2021 - ieeexplore.ieee.org
To mitigate global warming and energy shortage, integration of renewable energy
generation sources, energy storage systems, and plug-in electric vehicles (PEVs) have been …

A review of optimal charging strategy for electric vehicles under dynamic pricing schemes in the distribution charging network

A Amin, WUK Tareen, M Usman, H Ali, I Bari, B Horan… - Sustainability, 2020 - mdpi.com
This study summarizes a critical review on EVs' optimal charging and scheduling under
dynamic pricing schemes. A detailed comparison of these schemes, namely, Real Time …

Reinforcement learning in sustainable energy and electric systems: A survey

T Yang, L Zhao, W Li, AY Zomaya - Annual Reviews in Control, 2020 - Elsevier
The dynamic nature of sustainable energy and electric systems can vary significantly along
with the environment and load change, and they represent the features of multivariate, high …

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' …

Charge scheduling optimization of plug-in electric vehicle in a PV powered grid-connected charging station based on day-ahead solar energy forecasting in Australia

F Titus, SB Thanikanti, S Deb, NM Kumar - Sustainability, 2022 - mdpi.com
Optimal charge scheduling of electric vehicles in solar-powered charging stations based on
day-ahead forecasting of solar power generation is proposed in this paper. The proposed …

Urban virtual power plant operation optimization with incentive-based demand response

K Zhou, N Peng, H Yin, R Hu - Energy, 2023 - Elsevier
Urban virtual power plant (VPP) shows great potential in alleviating urban power shortage or
power supply-demand imbalance. This study proposes a bi-layer optimization model …

Modified deep learning and reinforcement learning for an incentive-based demand response model

L Wen, K Zhou, J Li, S Wang - Energy, 2020 - Elsevier
Incentive-based demand response (DR) program can induce end users (EUs) to reduce
electricity demand during peak period through rewards. In this study, an incentive-based DR …