A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine
Residential electricity consumption accounts for a large proportion of the primary energy
consumption in China. Building energy management can effectively improve energy …
consumption in China. Building energy management can effectively improve energy …
[HTML][HTML] Ensemble prediction approach based on learning to statistical model for efficient building energy consumption management
With the development of modern power systems (smart grid), energy consumption prediction
becomes an essential aspect of resource planning and operations. In the last few decades …
becomes an essential aspect of resource planning and operations. In the last few decades …
[HTML][HTML] Improving electric energy consumption prediction using CNN and Bi-LSTM
The electric energy consumption prediction (EECP) is an essential and complex task in
intelligent power management system. EECP plays a significant role in drawing up a …
intelligent power management system. EECP plays a significant role in drawing up a …
Evolutionary deep learning-based energy consumption prediction for buildings
Today's energy resources are closer to consumers due to sustainable energy and advanced
technology. To that end, ensuring a precise prediction of energy consumption at the …
technology. To that end, ensuring a precise prediction of energy consumption at the …
[HTML][HTML] An ensemble energy consumption forecasting model based on spatial-temporal clustering analysis in residential buildings
Due to the availability of smart metering infrastructure, high-resolution electric consumption
data is readily available to study the dynamics of residential electric consumption at finely …
data is readily available to study the dynamics of residential electric consumption at finely …
Forecasting residential electricity consumption using a hybrid machine learning model with online search data
F Gao, H Chi, X Shao - Applied Energy, 2021 - Elsevier
Accurate forecasting of residential electricity consumption plays an important role in
formulating energy plans and ensuring the safety of power system operations. In order to …
formulating energy plans and ensuring the safety of power system operations. In order to …
Short-term energy forecasting framework using an ensemble deep learning approach
M Ishaq, S Kwon - IEEE Access, 2021 - ieeexplore.ieee.org
Industrial and building sectors demand efficient smart energy strategies, techniques of
optimization, and efficient management for reducing global energy consumption due to the …
optimization, and efficient management for reducing global energy consumption due to the …
Deep learning for estimating building energy consumption
To improve the design of the electricity infrastructure and the efficient deployment of
distributed and renewable energy sources, a new paradigm for the energy supply chain is …
distributed and renewable energy sources, a new paradigm for the energy supply chain is …
A hybrid teaching-learning artificial neural network for building electrical energy consumption prediction
Numerous data-driven models have been successfully adopted for electrical energy
consumption forecasting at building and larger scales. When the data set for forecasting is …
consumption forecasting at building and larger scales. When the data set for forecasting is …
Accurate forecasting of building energy consumption via a novel ensembled deep learning method considering the cyclic feature
Short-term forecasting of building energy consumption (BEC) is significant for building
energy reduction and real-time demand response. In this study, we propose a new method …
energy reduction and real-time demand response. In this study, we propose a new method …