Machine learning for a sustainable energy future

Z Yao, Y Lum, A Johnston, LM Mejia-Mendoza… - Nature Reviews …, 2023 - nature.com
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it
demands advances—at the materials, devices and systems levels—for the efficient …

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 …

Blockchain based decentralized management of demand response programs in smart energy grids

C Pop, T Cioara, M Antal, I Anghel, I Salomie… - Sensors, 2018 - mdpi.com
In this paper, we investigate the use of decentralized blockchain mechanisms for delivering
transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of …

Incentive-based demand response for smart grid with reinforcement learning and deep neural network

R Lu, SH Hong - Applied energy, 2019 - Elsevier
Balancing electricity generation and consumption is essential for smoothing the power grids.
Any mismatch between energy supply and demand would increase costs to both the service …

Energy-saving behaviour as a demand-side management strategy in the developing world: the case of Bangladesh

I Khan - International Journal of Energy and Environmental …, 2019 - Springer
Although demand-side management (DSM) needs to be more customer centred, either with
or without smart technologies (eg smart grid), less attention has been paid to the developing …

[HTML][HTML] Scalable multi-agent reinforcement learning for distributed control of residential energy flexibility

F Charbonnier, T Morstyn, MD McCulloch - Applied Energy, 2022 - Elsevier
This paper proposes a novel scalable type of multi-agent reinforcement learning-based
coordination for distributed residential energy. Cooperating agents learn to control the …

[HTML][HTML] Coordination of resources at the edge of the electricity grid: Systematic review and taxonomy

F Charbonnier, T Morstyn, MD McCulloch - Applied Energy, 2022 - Elsevier
This paper proposes a novel taxonomy of coordination strategies for distributed energy
resources at the edge of the electricity grid, based on a systematic analysis of key literature …

Integrated energy transaction mechanisms based on blockchain technology

S Zhao, B Wang, Y Li, Y Li - Energies, 2018 - mdpi.com
With the rapid development of distributed renewable energy (DRE), demand response (DR)
programs, and the proposal of the energy internet, the current centralized trading of the …

[HTML][HTML] A systematic review of machine learning applications in the operation of smart distribution systems

T Matijašević, T Antić, T Capuder - Energy reports, 2022 - Elsevier
Due to climate changes happening in the past few years, the necessity for the integration of
renewable energy sources and other low-carbon technologies is ever-growing. With the …

Intelligent residential energy management system using deep reinforcement learning

A Mathew, A Roy, J Mathew - IEEE Systems Journal, 2020 - ieeexplore.ieee.org
The rising demand for electricity and its essential nature in today's world call for intelligent
home energy management systems that can reduce energy usage. This article aims a novel …