The rise of electric vehicles—2020 status and future expectations

M Muratori, M Alexander, D Arent, M Bazilian… - Progress in …, 2021 - iopscience.iop.org
Electric vehicles (EVs) are experiencing a rise in popularity over the past few years as the
technology has matured and costs have declined, and support for clean transportation has …

Assessing the value of electric vehicle managed charging: a review of methodologies and results

MB Anwar, M Muratori, P Jadun, E Hale… - Energy & …, 2022 - pubs.rsc.org
Driven by technological progress and growing global attention for sustainability, the
adoption of electric vehicles (EVs) is on the rise. Large-scale EV adoption would both disrupt …

[HTML][HTML] Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption

S Powell, GV Cezar, L Min, IML Azevedo, R Rajagopal - Nature Energy, 2022 - nature.com
Electric vehicles will contribute to emissions reductions in the United States, but their
charging may challenge electricity grid operations. We present a data-driven, realistic model …

Residential load forecasting based on LSTM fusing self-attention mechanism with pooling

H Zang, R Xu, L Cheng, T Ding, L Liu, Z Wei, G Sun - Energy, 2021 - Elsevier
Day-ahead residential load forecasting is crucial for electricity dispatch and demand
response in power systems. Electrical loads are characterized by volatility and uncertainty …

Impact of uncoordinated plug-in electric vehicle charging on residential power demand

M Muratori - Nature Energy, 2018 - nature.com
Electrification of transport offers opportunities to increase energy security, reduce carbon
emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new …

A review on peak load shaving strategies

M Uddin, MF Romlie, MF Abdullah, S Abd Halim… - … and Sustainable Energy …, 2018 - Elsevier
In this study, a significant literature review on peak load shaving strategies has been
presented. The impact of three major strategies for peak load shaving, namely demand side …

Demand response for home energy management using reinforcement learning and artificial neural network

R Lu, SH Hong, M Yu - IEEE Transactions on Smart Grid, 2019 - ieeexplore.ieee.org
Ever-changing variables in the electricity market require energy management systems
(EMSs) to make optimal real-time decisions adaptively. Demand response (DR) is the latest …

Smart operations of smart grids integrated with distributed generation: A review

S Kakran, S Chanana - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
In last few years, many countries in the world have shown huge interest in smart grid
technology. They are facing many challenges in the process of deployment of this …

A systematic review of occupant behavior in building energy policy

S Hu, D Yan, E Azar, F Guo - Building and Environment, 2020 - Elsevier
Buildings play a dominant role in global efforts towards energy consumption reduction,
greenhouse gas (GHG) emission mitigation, as well as global clean energy transition …

A deep learning method for short-term residential load forecasting in smart grid

Y Hong, Y Zhou, Q Li, W Xu, X Zheng - IEEE Access, 2020 - ieeexplore.ieee.org
Residential demand response is vital for the efficiency of power system. It has attracted
much attention from both academic and industry in recent years. Accurate short-term load …