Forecasting energy use in buildings using artificial neural networks: A review
J Runge, R Zmeureanu - Energies, 2019 - mdpi.com
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 …
Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective
Abstract Model predictive control (MPC) has shown great potential in improving building
performance and saving energy. However, after over 20 years of research, it is yet to be …
performance and saving energy. However, after over 20 years of research, it is yet to be …
Vector field-based support vector regression for building energy consumption prediction
Building energy consumption prediction plays an irreplaceable role in energy planning,
management, and conservation. Data-driven approaches, such as artificial neural networks …
management, and conservation. Data-driven approaches, such as artificial neural networks …
Electricity load forecasting by an improved forecast engine for building level consumers
Y Liu, W Wang, N Ghadimi - Energy, 2017 - Elsevier
For optimal power system operation, electrical generation must follow electrical load
demand. So, short term load forecast (STLF) has been proposed by researchers to tackle the …
demand. So, short term load forecast (STLF) has been proposed by researchers to tackle the …
Data-driven model predictive control using random forests for building energy optimization and climate control
Abstract Model Predictive Control (MPC) is a model-based technique widely and
successfully used over the past years to improve control systems performance. A key factor …
successfully used over the past years to improve control systems performance. A key factor …
Optimal control of HVAC and window systems for natural ventilation through reinforcement learning
Natural ventilation is a green building strategy that improves building energy efficiency,
indoor thermal environment, and air quality. However, in practice, it is not always clear when …
indoor thermal environment, and air quality. However, in practice, it is not always clear when …
Quantifying flexibility of commercial and residential loads for demand response using setpoint changes
This paper presents a novel demand response estimation framework for residential and
commercial buildings using a combination of EnergyPlus and two-state models for …
commercial buildings using a combination of EnergyPlus and two-state models for …
[HTML][HTML] A new approach to seasonal energy consumption forecasting using temporal convolutional networks
There has been a significant increase in the attention paid to resource management in smart
grids, and several energy forecasting models have been published in the literature. It is well …
grids, and several energy forecasting models have been published in the literature. It is well …
Investigating natural ventilation potentials across the globe: Regional and climatic variations
Y Chen, Z Tong, A Malkawi - Building and Environment, 2017 - Elsevier
Natural ventilation (NV) that reduces building energy consumption and improves indoor
environment has become a key solution to achieving sustainability in the building industry …
environment has become a key solution to achieving sustainability in the building industry …
A review on energy consumption optimization techniques in IoT based smart building environments
In recent years, due to the unnecessary wastage of electrical energy in residential buildings,
the requirement of energy optimization and user comfort has gained vital importance. In the …
the requirement of energy optimization and user comfort has gained vital importance. In the …