A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
A review of data-driven building energy consumption prediction studies
K Amasyali, NM El-Gohary - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy is the lifeblood of modern societies. In the past decades, the world's energy
consumption and associated CO 2 emissions increased rapidly due to the increases in …
consumption and associated CO 2 emissions increased rapidly due to the increases in …
Forecasting energy use in buildings using artificial neural networks: A review
During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …
have increased drastically due to a wide variety of factors including both technological and …
Short-term non-residential load forecasting based on multiple sequences LSTM recurrent neural network
R Jiao, T Zhang, Y Jiang, H He - IEEE Access, 2018 - ieeexplore.ieee.org
The energy consumption by non-residential consumers in China accounts for a significant
proportion of the total energy consumption in the society. Thus, accurate non-residential …
proportion of the total energy consumption in the society. Thus, accurate non-residential …
[HTML][HTML] Towards cross-commodity energy-sharing communities–A review of the market, regulatory, and technical situation
Meeting the energy goals of the European Union requires new ways of managing energy.
Decentralized energy management, cross-commodity energy production and usage …
Decentralized energy management, cross-commodity energy production and usage …
Comparison of short-term electrical load forecasting methods for different building types
The transformation of the energy system towards volatile renewable generation, increases
the need to manage decentralized flexibilities more efficiently. For this, precise forecasting of …
the need to manage decentralized flexibilities more efficiently. For this, precise forecasting of …
Short-term load forecasting in smart meters with sliding window-based ARIMA algorithms
Forecasting of electricity consumption for residential and industrial customers is an important
task providing intelligence to the smart grid. Accurate forecasting should allow a utility …
task providing intelligence to the smart grid. Accurate forecasting should allow a utility …
A simplified HVAC energy prediction method based on degree-day
A building heating, ventilation, and air-conditioning (HVAC) system consumes large
amounts of energy. Energy consumption prediction is an effective strategy for operation …
amounts of energy. Energy consumption prediction is an effective strategy for operation …
Review of Machine Learning Techniques for Power Quality Performance Evaluation in Grid-Connected Systems
In the current energy usage scenario, the demands on energy load and the tariffs on the
usage of electricity are two main areas that require a lot of attention. Energy forecasting is an …
usage of electricity are two main areas that require a lot of attention. Energy forecasting is an …
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 …