As a weak link in energy efficient buildings, the building glass windows have been developing towards energy saving, comfort and adjustability. The dynamic windows and static windows have the ...disadvantages of instability as well as low spectral flexibility and poor seasonal adaptation respectively, to solve the above problems, this study proposes a novel semi-dynamic fluidic window filled with ATO/water nanofluids to bridge the gap between dynamic windows and static windows, and its performance has been experimentally studied. Firstly, the operating principle of the novel spectrally selective windows with overturn function is depicted during summer and winter operating periods. Meanwhile, the indoor light/thermal environment is discussed with the effect of volume concentrations ATO nanofluids, by comparative experiments. Results indicated that the inner/outer surface temperature with spectrally selective windows is higher than that with common windows, and the inner surface temperature difference of two cases can reach 1.3 °C, 4.7 °C, 10.1 °C and 6.8 °C, with volume concentration of 100 ppm, 200 ppm, 500 ppm and 1000 ppm respectively. Meanwhile, heat absorption of nanofluids delays the time of indoor peak temperature and increases the indoor air temperature during the afternoon and evening period, with a delay time of 33 min at 1000 ppm volume concentration. Additionally, it is found that with volume concentration increases, indoor illuminance significantly decreases, and the optimal concentrations of 100 ppm or 200 ppm are recommended for operation during winter time.
This paper reviews the most used thermal comfort models and indicators with their variants, discussing their usage in control problems referring to energy management in indoor applications. The first ...part addresses the recent literature referring to the thermal comfort concepts, models of human thermal comfort, thermal comfort models and indicators, thermal comfort standards, control systems, optimisation methods, and practical assessments. Then, the ambient and personal parameters used to represent thermal comfort and thermal sensation are recalled. The following part reviews the definitions and usage of a number of thermal comfort indices, mainly related to the Predicted Mean Vote (PMV), the Actual Mean Vote (AMV), and the Predicted Percentage Dissatisfied (PPD), with their modifications and variants, indicating a number of applications to different situations in indoor environments. The last part reviews the thermal comfort models used to define control strategies in indoor applications, discussing the characteristics and parameters of models based on artificial neural networks, autoregressive variants, fuzzy control, and hybrid models combining different approaches. The characteristics of these models and their usage to predict the indoor air temperature and the PMV index are discussed with reference to the identification of the several inputs used in relevant literature contributions.
This paper presents a comprehensive review of the significant studies exploited Artificial Neural Networks (ANNs) in BEA (Building Energy Analysis). To achieve a full coverage of the relevant studies ...to the scope of the research, a three-decade time span of the publishing date of the existing studies was taken into account. The review focuses on the studies utilized ANN to analyze the energy-related issues associated with buildings in major areas, including modeling of water heating and cooling systems, heating and cooling loads prediction, modeling heating ventilation air conditioning systems, indoor air temperature prediction, and building energy consumption prediction. Moreover, the findings of the abundant reviewed studies along with the potential future research to be carried out are discussed elaborately. Regarding the comprehensive review conducted, it is found out that the majority of studies focused on building energy consumption and indoor air temperature prediction. Additionally, it is observed that there has been a growing interest in the application of newly-developed ANNs to BEA areas, such as general regression neural network and recurrent neural network, due to their abilities in improving the modeling and prediction of buildings energy analysis. It is believed that this thorough review paper is useful for the researchers and scientific engineers working on the application of AI-based techniques to the building-energy-related areas to find out the relevant references and current state of the field.
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•Artificial Neural Networks (ANNs) are used to predict comfort parameters.•Hourly indoor air temperature and relative humidity in building were predicted one day to one month in ...advance in hot-humid region.•ANN model performances are characterized by mean square error and the coefficient of correlation.•The experimental building is built with cement hallow block in the town of Douala-Cameroon.
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 Douala-Cameroon. IT and IH were collected for 24 months. The experimental data were used to determine the optimal ANN structure with levenberg-marquardt algorithm using Matlab software. The optimal structure was the multilayer perceptron (MLP) with 36 input variables, 10 hidden neurons and two neurons in the output layer. The activation functions were respectively the hyperbolic tangent in the hidden layer and the linear function in the output layer. Moreover, the IT and IH results simulated by using the ANN model were strongly correlated with the experimental data, with the coefficient of correlation of 0.9850 for IT and 0.9853 for IH. These results testified that ANN can be used for hourly IT and IH prediction.
This paper presents wind-tunnel experiments of cross-ventilative cooling in a generic isolated building with an interior heated side wall. Two different sizes of openings are considered: large and ...small openings. Particle image velocimetry (PIV) is used to determine velocities in the vertical centerplane. Air temperatures in the vertical centerplane are measured using negative temperature coefficient (NTC) sensors. Surface temperatures on the heated wall are measured using an infrared camera. Surface heat fluxes are obtained using heat flux sensors. In both cases the indoor airflow is dominated by the jet through the openings, with higher velocities in the building with large openings. The air temperatures measured with small openings are up to 7.5 % larger than those with large openings. The surface heat fluxes are up to 20 % higher in the building with large openings. The interior convective heat transfer coefficients vary considerably across the heated wall for both opening sizes and can be very different (up to 5 times higher) from those obtained by existing internal convective heat transfer coefficient correlations. The measurement results give insight into the complexity of ventilative cooling and can be used to validate computational fluid dynamics (CFD) simulations of cross-ventilative cooling.
•Wind tunnel experiments on ventilative cooling in a building with heated wall.•The experiments are carried out for two different opening sizes (large and small).•Overall, larger temperatures are measured for case with small openings.•Heat flux varies considerably across the heated wall for both cases.•Comparison of CHTC from measurements with CHTC from correlations from literature.
This study presents a case study of public buildings using a novel deep learning method to forecast indoor air temperature. The aim is to explore the potential of long short-term memory (LSTM) model ...in forecasting indoor temperature, and a novel LSTM model modified by error correction model is established. The performance of the two models is compared with popular prediction methods in the building field.
Results show that the proposed novel LSTM model has slight advantages in level indoor temperature prediction performance comparing with other common machine learning methods. However, it outperforms other models including original LSTM in terms of directional prediction accuracy, and accurately predicts the indoor temperature variation trend. This work is enlightening and may have a further reference to the feasibility study of indoor air temperature prediction model.
•We proposed a novel deep learning method for indoor temperature prediction.•Error correction model was used to revise the LSTM model.•The method was compared with three common used machine learning models.•The method showed outstanding effect on improving the performance of indoor temperature prediction.
A differentiated thermal environment with different air temperature and radiant temperature can influence human thermal comfort levels when compared to the uniform thermal environment. The ...environment with the difference between indoor surface temperature and air temperature is the non-uniform thermal environment. However, existing research on the non-uniform thermal environment mainly focused on the impact of radiant environment on human thermal sensation, and few studies have focused on methods to improve the thermal comfort in the non-uniform thermal environment. In order to investigate the improvement of thermal comfort due to air velocity (va) in the non-uniform thermal environment, 20 subjects were recruited, and climate chamber was used in order to create air temperature and radiant temperature differential thermal environment (Δt = 0 °C, Δt = 5 °C, Δt = 10 °C, and va = 0 m/s, va = 0.6 m/s, va = 1.2 m/s). Furthermore, questionnaire survey combined with the physiological experiments was used, and the influence of va on thermal comfort in a hot environment was discussed. The results showed that increasing va can improve thermal comfort and reduce thermal discomfort caused by the difference between radiant temperature and air temperature. When va = 1.2 m/s, the percentage of thermal dissatisfaction can be reduced by a maximum of 20% (compared to when va = 0.6 m/s). Moreover, when va increased to 1.2 m/s, the limit value of acceptable operating temperature increased by 2 °C (compared to when va = 0.6 m/s). The results of this study will be useful in providing a theoretical basis for the design of the parameters of the indoor non-uniform thermal environment.
•Combined effects of radiant temperature and air velocity on comfort were studied.•High air velocity could improve thermal comfort in a non-uniform environment.•High air velocity increased the deviation between thermal neutral and comfort.•The air velocity was less sensitive with warmer thermal sensation.
•A dynamic model successfully validated for modelling residential buildings equipped with EAHE is developed.•The building indoor conditions in summer can be significantly enhanced by using EAHE and ...insulation.•The insulated light buildings are more effective than the insulated heavy buildings in hot and arid climate.•Effect of building materials, including insulation materials, combined with that of EAHE is also investigated.•Due to its influence, the building geometrical aspect is a parameter which should be carefully chosen.
This paper aims to investigate the impact of the thermal insulation on the cooling effectiveness of the Earth-to-Air Heat Exchanger systems under hot and arid climate. For that, the dynamic behaviour of two identical buildings submitted to the same exterior solicitations and equipped with an EAHE is presented in detail. To achieve the objective of this study, two transient models are developed; one for modelling the EAHE and the other for describing the thermal behaviour of buildings. The set of differential equations corresponding to different components of the system is solved using the technique of Complex Finite Fourier Transform. The findings indicate that when the insulated building is equipped with an EAHE, the effect of the thermal insulation will be combined with that of EAHE and the resulting effect will be more important, so that the reduction in the indoor air maximal temperature can be greater than 11°C and the reduction rate in the amplitude of the indoor air temperature increases until 91%. In addition, it is found that the thermal performances of the building outer walls represented usually by the decrement factor and the time-lag can be more improved using insulation layers within these components. On the other hand, the investigation conducted on the effect of the building materials showed that in Saharan climate, the light buildings such as those constructed with autoclaved aerated concrete blocks are more performing compared to the heavy buildings in which the outer walls must be judiciously insulated with a material of high thermal resistance. However, it is shown that the insulation with air cavities is an effective and economic solution for the light buildings in hot and arid regions.
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•An evaluation method for heating solutions in rural households was adopted.•Field case studies examining four possible clean heating solutions were conducted.•Techno-economic ...performances of four clean heating solutions were evaluated.•Biomass pellet boiler and air-to-air heat pump could be prioritized in rural areas.
The combustion of raw coal leads to severe environmental pollution; however, many people in Northern rural China still use coal as a primary heat source. How to select clean heating technologies that can replace raw coal is essential, but still unclear; therefore, it is crucial to evaluate the existing heating systems to find out the answer. Herein, we selected four possible substitution solutions, including shaped coal heating boiler, biomass pellet heating boiler, low ambient temperature air-to-water heat pump, and low ambient temperature air-to-air heat pump, to conduct field tests and compare with raw coal as the baseline. We assessed the indoor air temperature, energy conservation effect, environmental impact, and economic impact of these solutions. Results indicated that biomass pellet for heating and low ambient temperature air-to-air heat pump possess the potential for dissemination. Herein, the biomass pellet heating boiler is the best solution in rural areas with rich biomass resources, while the low ambient temperature air-to-air heat pump is deemed suitable in rural areas that lack access to biomass or have flexible heating demands. This study evaluated the possible clean heating solutions in Northern rural China, which might be useful for other countries facing similar environmental problems.
Traditional air-conditioning systems are energy intensive and contribute to higher operational costs especially in summer. This paper examines and compares the performance of two cooling systems in a ...room: one with a cooling tower connected thermally activated building system (TABS) combined with a fan coil unit (FCU), and the other with a conventional inverter split air-conditioner (AC). Natural ventilation adversely affected indoor air temperatures in TABS room while integrating FCU operation reduced the temperature by 5 °C and AC provided the most comfortable temperature. Thermal comfort survey of three occupants showed significant inconsistencies with Fanger model particularly for TABS with FCU and TABS without ventilation cases, as occupants felt comfortable indicating the positive effect of only sensible cooling. Energy consumption studies show that TABS in closed condition and with natural ventilation as the most energy efficient with AC being least efficient of the four systems. In terms of overall comfort and energy consumption for continuous operation throughout the day, TABS integrated with FCU was deemed the best option.
