[HTML][HTML] Energy, thermal comfort, and indoor air quality: Multi-objective optimization review
The reliance on optimization techniques for robust assessments of environmental and
energy-saving solutions has been largely driven by the increasing need to comply with …
energy-saving solutions has been largely driven by the increasing need to comply with …
Forecasting methods in energy planning models
KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
[HTML][HTML] Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
Energy prediction models are used in buildings as a performance evaluation engine in
advanced control and optimisation, and in making informed decisions by facility managers …
advanced control and optimisation, and in making informed decisions by facility managers …
[HTML][HTML] Predictive modelling for solar thermal energy systems: A comparison of support vector regression, random forest, extra trees and regression trees
Predictive analytics play an important role in the management of decentralised energy
systems. Prediction models of uncontrolled variables (eg, renewable energy sources …
systems. Prediction models of uncontrolled variables (eg, renewable energy sources …
Integrated supply–demand energy management for optimal design of off-grid hybrid renewable energy systems for residential electrification in arid climates
The growing research interest in hybrid renewable energy systems (HRESs) has been
regarded as a natural and yet critical response to address the challenge of rural …
regarded as a natural and yet critical response to address the challenge of rural …
[HTML][HTML] Tree-based ensemble methods for predicting PV power generation and their comparison with support vector regression
The variability of renewable energy resources, due to the characteristic weather fluctuations,
introduces uncertainty in generation output that are greater than the conventional energy …
introduces uncertainty in generation output that are greater than the conventional energy …
Fault detection diagnostic for HVAC systems via deep learning algorithms
Because of high detection accuracy, deep learning algorithms have recently become the
focus of increased attention for fault detection diagnostic (FDD) analysis of heat, ventilation …
focus of increased attention for fault detection diagnostic (FDD) analysis of heat, ventilation …
An explainable one-dimensional convolutional neural networks based fault diagnosis method for building heating, ventilation and air conditioning systems
G Li, Q Yao, C Fan, C Zhou, G Wu, Z Zhou… - Building and …, 2021 - Elsevier
Due to the frequently changed outdoor weather conditions and indoor requirements,
heating, ventilation and air conditioning (HVAC) experiences faulty operations inevitably …
heating, ventilation and air conditioning (HVAC) experiences faulty operations inevitably …
[HTML][HTML] A zone-level, building energy optimisation combining an artificial neural network, a genetic algorithm, and model predictive control
Buildings account for a substantial proportion of global energy consumption and global
greenhouse gas emissions. Given the growth in smart devices and sensors there is an …
greenhouse gas emissions. Given the growth in smart devices and sensors there is an …
Simulation optimisation towards energy efficient green buildings: Current status and future trends
The increasing global importance of climate change has been clearly recognised in the last
few years. The building industry contributed to a large proportion of the global energy use …
few years. The building industry contributed to a large proportion of the global energy use …