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Building air-conditioning and mechanical ventilation (ACMV) systems are responsible for significant energy consumption and yet, dissatisfaction with the thermal environment is prevalent among the occupants, revealing a widespread disparity between energy-efficiency and indoor thermal-comfort in buildings. This paper presents an indoor-climate control framework that bridges this gap between energy and comfort. The framework comprises two main components: a thermal-comfort prediction model,...

Accurate and reliable building energy predictions can bring significant benefits for energy conservations. With the development in smart buildings, massive amounts of building operational data are being collected and available for analysis. It is desired to develop big data-driven methods to fully realize the potential of building operational data in energy predictions. This paper investigates the usefulness of advanced recurrent neural network-based strategies for building energy...

The emerging Internet of Things (IoT) technology enables smart building management and operation to improve building energy efficiency and occupant thermal comfort. In this paper, we perform data analysis using the IoT generated building data to derive accurate thermal comfort model for smart building control. Deep neural network (DNN) is used to model the relationship between the controllable building operations and thermal comfort. As thermal comfort is determined by multiple comfort...

A novel dynamic model for the temperature inside buildings is presented, aiming to improve energy efficiency by providing predictive information on the heat demand. To analyse the performance and generalizability of the modelling approach, real measurement data was gathered from five different types of buildings. Easily available data from various sources was utilized. The chosen model structure leads to a minimal number of input variables and free parameters. Simulations with real data from...

Aiming at the prediction control for indoor temperature time-delay in variable air volume (VAV) air conditioning system, this paper presents an indoor temperature prediction control method based on Elman neural network multi-step prediction model. Firstly, this paper introduces basic control principles of pressure-dependent and pressure-independent VAV terminal through comparable analysis and points out significance of indoor temperature prediction control based on pressure-dependent VAV...

Energy optimization in buildings by controlling the Heating Ventilation and Air Conditioning (HVAC) system is being researched extensively. In this paper, a model-free actor-critic Reinforcement Learning (RL) controller is designed using a variant of artificial recurrent neural networks called Long-Short-Term Memory (LSTM) networks. Optimization of thermal comfort alongside energy consumption is the goal in tuning this RL controller. The test platform, our office space, is designed using...

The most prominent challenge in 21th century is global warming which seriously threats the mankind. Building sector with 40% of global energy consumption and GHG emission play a key role in this threat. In this regard, the impact of cooling systems cannot be ignored where along with ventilation and heating systems totally account for 60% of energy consumed in buildings. Passive cooling systems can be a promising alternative to reduce energy consumption. One of the oldest passive cooling...

The prediction of the air temperature (IT) and relative humidity (IH) in a building can help to reduce energy consumption for air conditioning. The purpose of this work was to apply the artificial neural network (ANNs) for an hourly prediction, 24–672h in advance of (IT) and (IH) in buildings found in hot-humid region. The inputs used in the model are 12 last values of indoor and outdoor air temperature and relative humidity. The experimental building is built with cement hallow block in...

The validity of existing thermal comfort models is examined for upper primary school children in classroom settings. This is of importance to enhance productivity in the learning environment and to improve the control of artificial heating and cooling, including the potential for energy savings. To examine the thermal perceptions of children aged 10–12 years in non-air-conditioned classrooms, three sets of field experiments were conducted in boys’ and girls’ primary schools in Shiraz, Iran....

The paper describes the application of a combined neuro-fuzzy model for indoor temperature dynamic and automatic regulation. The neural module of the model, an auto-regressive neural network with external inputs (NNARX), produces indoor temperature forecasts that are used to feed a fuzzy logic control unit that simulates switching the heating, ventilation and air conditioning (HVAC) system on and off and regulating the inlet air speed. To generate an indoor temperature forecast, the NNARX...

The paper refers to the development of a continuous time mathematical heating model for a building unit based on the first principles. The model is described in terms of the state space variables, and a lumped parameter approach is used to represent the room air temperature and air density using mass and energy balances. The one-dimensional heat equation in cartesian coordinates and spherical coordinates is discretized in order to describe the thermic characteristics of the layers of the...

This paper presents the optimization of chillers operating using artificial neural networks and genetic algorithms. For the needs of generating chiller models, an artificial neural network was used, trained with data collected from an actual chiller. For that purpose the basic characteristics of artificial neural networks are shown as well as the process of making specific chiller models used for testing the results of application of the genetic algorithm in usage optimization. The optimal...

The actual European energy context highlights the building sector as one of the largest sectors of energy consumption. Consequently, the “Energy Performance of Buildings Directive”, adopted in 2002 and focusing on energy use in buildings, requires all the EU members to enhance their building regulations and to introduce energy certification schemes, with the aim of both reducing energy consumption and improving energy efficiency. That is why carrying out an energy performance diagnosis is...

The present paper suggests a procedure for identification of suitable models for the heat dynamics of a building. Such a procedure for model identification is essential for better usage of readings from smart meters, which is expected to be installed in almost all buildings in the coming years. The models can be used for different purposes, e.g. control of the indoor climate, forecasting of energy consumption, and for accurate description of energy performance of the building. Grey-box models...