[HTML][HTML] A deep learning architecture for power management in smart cities

Q Xin, M Alazab, VG Díaz, CE Montenegro-Marin… - Energy Reports, 2022 - Elsevier
Sustainable energy management is an inexpensive approach for improved energy use.
However, the research used does not focus on cutting-edge technology possibilities in an …

Renewable energy systems energy modeling using deep learning techniques

SP Sharma, DK Yadav - 2023 2nd International Conference for …, 2023 - ieeexplore.ieee.org
Communities using Sustainable Energy Systems (RES) seek to meet their electrical needs
while reducing their reliance on public utilities by integrating renewable energy sources …

Household-level energy forecasting in smart buildings using a novel hybrid deep learning model

D Syed, H Abu-Rub, A Ghrayeb, SS Refaat - IEEE Access, 2021 - ieeexplore.ieee.org
Forecasting of energy consumption in Smart Buildings (SB) and using the extracted
information to plan and operate power generation are crucial elements of the Smart Grid …

A Novel Deep Learning‐Based Data Analysis Model for Solar Photovoltaic Power Generation and Electrical Consumption Forecasting in the Smart Power Grid

CF Mbey, FG Yem Souhe… - … Intelligence and Soft …, 2024 - Wiley Online Library
With the installation of solar panels around the world and the permanent fluctuation of
climatic factors, it is, therefore, important to provide the necessary energy in the electrical …

An intelligent power distribution service architecture using cloud computing and deep learning techniques

W Zhang, G Wulan, J Zhai, L Xu, D Zhao, X Liu… - Journal of Network and …, 2018 - Elsevier
Smart management of power consumption for green living is important for sustainable
development. Existing approaches could not provide a complete solution for both smart …

An efficient deep learning framework for intelligent energy management in IoT networks

T Han, K Muhammad, T Hussain… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Green energy management is an economical solution for better energy usage, but the
employed literature lacks focusing on the potentials of edge intelligence in controllable …

BiGTA-Net: A hybrid deep learning-based electrical energy forecasting model for building energy management systems

D So, J Oh, I Jeon, J Moon, M Lee, S Rho - Systems, 2023 - mdpi.com
The growth of urban areas and the management of energy resources highlight the need for
precise short-term load forecasting (STLF) in energy management systems to improve …

Energy demand forecasting using deep learning

B Hrnjica, AD Mehr - Smart cities performability, cognition, & security, 2020 - Springer
Our cities face non-stop growth in population and infrastructures and require more energy
every day. Energy management is the key success for the smart cities concept since …

Computer‐assisted demand‐side energy management in residential smart grid employing novel pooling deep learning algorithm

PR Jeyaraj, ERS Nadar - International Journal of Energy …, 2021 - Wiley Online Library
Demand‐side energy management increases the unpredictability and ambiguity of
forecasting the load profiles of residential energy management. The energy management …

Renewable energy power generation forecasting using deep learning method

DA Widodo, N Iksan, ED Udayanti - IOP Conference Series …, 2021 - iopscience.iop.org
Abstract Smart Micro Grid in household areas aims to meet electricity needs through the
integration between state power plant with renewable energy sources so that the electricity …