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The occupants' presence, activities, and behaviour can significantly impact the building's performance and energy efficiency. Currently, heating, ventilation, and airconditioning (HVAC) systems are often run based on assumed occupancy levels and fixed schedules, or manually set by occupants based on their comfort needs. However, the unpredictability and variability of occupancy patterns can lead to over/under the conditioning of space when using such approaches, affecting indoor air quality...

Personal thermal comfort models are crucial for the future of human-in-the-loop HVAC control in energy-efficient buildings. Individual comfort models, compared to average population responses, can provide the personalization required for successful control. In this work, we frame the thermal preference prediction task as a multivariate, multi-class classification problem and use deep learning and time-series-based approach for thermal preference prediction. We combine l1 regularization with...

Building Energy prediction has emerged as an active research area due to its potential in improving energy efficiency in building energy management systems. Essentially, building energy prediction belongs to the time series forecasting or regression problem, and data-driven methods have drawn more attention recently due to their powerful ability to model complex relationships without expert knowledge. Among those methods, artificial neural networks (ANNs) have proven to be one of the most...

A large part of energy consumption in homes, offices and commercial spaces is related to Heating, Ventilation and Air-conditioning (HVAC) devices. The effective parameter on the consumption of HVAC systems is internal heat gains that arise from occupants, electric equipment and lighting. In order to reduce the energy consumption of these systems, internal heat gains should be predicted accurately. Since there are few investigations performed on the prediction of internal heat gains, in this...

This paper presents a detailed analysis to optimize natural ventilation performance in educational buildings to minimize the probability of viral infection (POI) and avoid draught discomfort. A whole building energy simulation tool has been coupled with the Wells–Riley equation to predict the probability of infection and Fanger’s draught equation to estimate the draught risk for classroom environments. Several parameters have been investigated, including window opening fraction (WOF),...

Monitoring the thermal comfort of building occupants is crucial for ensuring sustainable and efficient energy consumption in residential buildings. Existing studies have addressed the monitoring of thermal comfort through questionnaires and activities involving occupants. However, few studies have considered disabled people in the monitoring of thermal comfort, despite the potential for impairments to present thermal requirements that are significantly different from those of an occupant...

The development of deep learning (DL) technology provides an opportunity for accurate prediction and effective control of complex building systems. However, despite the high prediction performance of DL models, few studies integrate DL with the model predictive control (MPC) algorithm for improving building management. In this study, a DL-based MPC framework using encoder-decoder recurrent neural network is developed for real-time control of building thermal environment to exploit the...

Thermal comfort is a critical component of indoor environments, especially in schools where learning is the main objective. However, thermal comfort comes at a price that many schools are unable to afford. Therefore, it is critical to determine a method to lower the energy costs of a building while still maintaining occupant thermal comfort. The objective of this study is to investigate how three indoor environmental parameters of air speed, humidity, and air temperature influence energy and...

Increased thermal comfort in buildings is consuming large amounts of energy around the world, especially in hot arid and semi-arid regions. Finding and adapting ways to naturally cool buildings should be a priority for researchers in the subject. For centuries the Middle East cultures have used wind towers to cool their buildings and they have proved to be a cost-effective, easy to implement and reliable solution for passive cooling that requires almost negligible energy to operate. The...

A simplified modelling framework for the prediction of the indoor environment, energy use and socioeconomic consequences of improving air quality and temperature in school buildings is suggested. The framework combines established models for infiltration and different modes of ventilation to estimate yearly distributions of the classroom temperature and CO2 concentration. These distributions are used as input to a prediction of pupil performance of schoolwork, their attendance at school, and...

Heating, ventilation, and air conditioning (HVAC) are extremely energy consuming, accounting for 40% of total building energy consumption. It is crucial to design some energy-efficient building thermal comfort control strategy which can reduce the energy consumption of the HVAC while maintaining the comfort of the occupants. However, implementing such a strategy is challenging, because the changes of the thermal states in a building environment are influenced by various factors. The...

Undoubtedly, the steady increase in the number of elderly people is not to be underestimated. These demographic changes call attention to new challenges regarding adequate aging-in-place strategies. Since the majority of the senior population spend up to 90% of their time indoors, appropriate and comfortable housing represents an important foundation for such strategies. In this respect, different types of data gathered from sensors, connected devices, and Internet of Things (IoT)...

Buildings consume about 40 % of globally-produced energy. A notable amount of this energy is used to provide sufficient comfort levels to the building occupants. Moreover, given recent increases in global temperatures as a result of climate change and the associated decrease in comfort levels, providing adequate comfort levels in indoor spaces has become increasingly important. However, striking a balance between reducing building energy use and providing adequate comfort levels is a...

Optimal control of heating, ventilation and air conditioning systems (HVACs) aims to minimize the energy consumption of equipment while maintaining the thermal comfort of occupants. Traditional rule-based control methods are not optimized for HVAC systems with continuous sensor readings and actuator controls. Recent developments in deep reinforcement learning (DRL) enabled control of HVACs with continuous sensor inputs and actions, while eliminating the need of building complex thermodynamic...

Climate change is one of the most important issues for humanity. To defuse this problem, it is considered necessary to improve energy efficiency, make energy sources cleaner, and reduce energy consumption in urban areas. The Japanese government has recommended an air conditioner setting of 28◦C in summer and 20◦C in winter since 2005. The aim of this setting is to save energy by keeping room temperatures constant. However, it is unclear whether this is an appropriate temperature for workers...