Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
Energy sustainable paradigms and methods for future mobile networks: A survey
In this survey, we discuss the role of energy in the design of future mobile networks and, in
particular, we advocate and elaborate on the use of energy harvesting (EH) hardware as a …
particular, we advocate and elaborate on the use of energy harvesting (EH) hardware as a …
Data-driven probabilistic power flow analysis for a distribution system with renewable energy sources using Monte Carlo simulation
GE Constante-Flores… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper investigates the effect of uncertainty in the allocation of photovoltaic (PV)
generation, solar irradiance, and its impact on the power flow in a distribution network. The …
generation, solar irradiance, and its impact on the power flow in a distribution network. The …
Energy sharing and frequency regulation in energy network via mixed H2/H∞ control with Markovian jump
In this paper, the problem of mixed optimization for energy sharing and frequency regulation
in a typical energy network scenario where energy routers (ERs) interconnected AC …
in a typical energy network scenario where energy routers (ERs) interconnected AC …
PV panel modeling with improved parameter extraction technique
An accurate model of the PV panel is useful to predict its behavior at all operating points for
various applications. However, most of the manufacturers provide datasheet values at only …
various applications. However, most of the manufacturers provide datasheet values at only …
Switch-on/off policies for energy harvesting small cells through distributed Q-learning
The massive deployment of small cells (SCs) represents one of the most promising solutions
adopted by 5G cellular networks to meet the foreseen huge traffic demand. The high number …
adopted by 5G cellular networks to meet the foreseen huge traffic demand. The high number …
Optimal adaptive random multiaccess in energy harvesting wireless sensor networks
N Michelusi, M Zorzi - IEEE transactions on communications, 2015 - ieeexplore.ieee.org
Wireless sensors can integrate rechargeable batteries and energy-harvesting (EH) devices
to enable long-term, autonomous operation, thus requiring intelligent energy management …
to enable long-term, autonomous operation, thus requiring intelligent energy management …
Distributed Q-learning for energy harvesting heterogeneous networks
We consider a two-tier urban Heterogeneous Network where small cells powered with
renewable energy are deployed in order to provide capacity extension and to offload macro …
renewable energy are deployed in order to provide capacity extension and to offload macro …
Energy efficient deployment and orchestration of computing resources at the network edge: a survey on algorithms, trends and open challenges
Mobile networks are becoming energy hungry, and this trend is expected to continue due to
a surge in communication and computation demand. Multi-access Edge Computing (MEC) …
a surge in communication and computation demand. Multi-access Edge Computing (MEC) …
Energy modeling and adaptive sampling algorithms for energy‐harvesting powered nodes with sampling rate limitations
E Gindullina, L Badia… - Transactions on Emerging …, 2020 - Wiley Online Library
This article explores the implementation of different sampling strategies for a practical
energy‐harvesting wireless device (sensor node) powered by a rechargeable battery. We …
energy‐harvesting wireless device (sensor node) powered by a rechargeable battery. We …