Analyzing Long-Term and High Instantaneous Power Consumption of Buildings from Smart Meter Big Data with Deep Learning and Knowledge Graph Techniques
RG Wang, WJ Ho, KC Chiang, YC Hung, JK Tai… - Energies, 2023 - mdpi.com
In the context of the growing emphasis on energy conservation and carbon reduction, the
widespread deployment of smart meters in residential and commercial buildings is …
widespread deployment of smart meters in residential and commercial buildings is …
Deep learning assisted buildings energy consumption profiling using smart meter data
The exponential growth in population and their overall reliance on the usage of electrical
and electronic devices have increased the demand for energy production. It needs precise …
and electronic devices have increased the demand for energy production. It needs precise …
Modern Developments and Analysis of Household Electricity Utilization by Applying Smart Meter and its Findings
Y Mao, E Shiju, C Zhu - Energy, 2024 - Elsevier
The efficient utilization of household electricity is pivotal in the context of rising energy
demands and environmental concerns. This study addresses the critical issue of electricity …
demands and environmental concerns. This study addresses the critical issue of electricity …
Facilitating energy-efficient operation of smart building using data-driven approaches
The building operations and control have become automated with the help of information
and communication technologies (ICT) leading to a new paradigm shift ie Smart Buildings …
and communication technologies (ICT) leading to a new paradigm shift ie Smart Buildings …
Smart building energy management using deep learning based predictions
The prediction of electricity consumption in a building is critical for recognizing the
possibilities for energy savings as a part of the digitalization of the built environment. This …
possibilities for energy savings as a part of the digitalization of the built environment. This …
Predicting household electric power consumption using multi-step time series with convolutional LSTM
Energy consumption prediction has become an integral part of a smart and sustainable
environment. With future demand forecasts, energy production and distribution can be …
environment. With future demand forecasts, energy production and distribution can be …
Predicting residential energy consumption using wavelet decomposition with deep neural network
DD Eneyew, MAM Capretz… - 2020 19th IEEE …, 2020 - ieeexplore.ieee.org
Electricity consumption is accelerating due to economic and population growth. Hence,
energy consumption prediction is becoming vital for overall consumption management and …
energy consumption prediction is becoming vital for overall consumption management and …
Predicting Smart Office Electricity Consumption in Response to Weather Conditions Using Deep Learning
This study investigates the intricate relationship between electricity consumption in smart
office environments, temporal elements such as time, and external factors such as weather …
office environments, temporal elements such as time, and external factors such as weather …
GUI energy demand forecast using LSTM deep learning model in python platform
B Rohith, T Santhosh, RB Alfred… - 2021 Innovations in …, 2021 - ieeexplore.ieee.org
This article proposes a technique for power distribution in the smart grid. This concept is
based on a deep learning technique that employs the long short-term memory (LSTM) …
based on a deep learning technique that employs the long short-term memory (LSTM) …
BiGTA-Net: A hybrid deep learning-based electrical energy forecasting model for building energy management systems
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 …
precise short-term load forecasting (STLF) in energy management systems to improve …