Building Services Engineering Research & Technology

Experiments on different vent pipe diameters (nominal diameters of 100, 75 and 50 mm; DN100, DN75 and DN50, respectively) in a full-scale circuit vent building drainage system were conducted in a 60 -m high structure, and the wastewater discharge capacities as a function of vent pipe diameter were measured. Critical pipe pressures, water seal losses of sanitary fixtures and air flow rates were measured. The ultimate pressure values in pipes on lower floors were larger than those in pipes on higher floors using DN100 and DN75, which was opposite to the results with DN50. A positive correlation between the ultimate pressure values and floor heights, as well as between ultimate pressure values and water seal losses, was found for DN100 and DN75. The maximum discharge flow of the three systems using DN100, DN75 and DN50 vent pipes was 17.0 L/s, 14.0 L/s and 7.5 L/s, respectively. Nevertheless, in China, the maximum wastewater discharge capacity in a circuit vent system adopting a DN100 vent pipe connected to a DN100 drainage stack in tall residential buildings is 11.5 L/s according to the Code for Design of Building Water Supply and Drainage. Thus, the vent pipe diameter DN75 can fully meet the design requirements of drainage systems for high rise buildings in China. The engineering cost associated with material expenses for building drainage systems can be minimised by optimising the size of vent pipe based on required capacity rather than using a single size universally.

Practical application: The engineering cost associated with material expenses for building drainage systems can be minimised by optimising the size of vent pipe based on required capacity rather than using a single size universally.

Energy conservation, environmental protection, and intelligence are topics of interest in intelligent buildings. However, the energy requirement of various electrical equipment in intelligent buildings increases energy consumption. This study presents a neural network-based prediction and control system for the regulation of building environmental parameters. Neural network-based soft sensing technology can detect building environmental parameters through few sensors. The proposed system control algorithm can realize the adaptive adjustment of environmental parameters by using a neural network proportional–integral–derivative controller. Zigbee wireless communication is adopted as the information transmission medium to realize the environmental parameter measurement and network control. The soft sensing technique combined with Zigbee communication technology can effectively reduce energy consumption. The central control system analyzes the data coming from the network and regulates the environmental parameter through lifting temperature, ventilation, and switching curtains by using the neural network proportional–integral–derivative algorithm. The regulation of environmental parameters reduces unnecessary energy consumption. Finally, the effectiveness of the system is verified through simulations.

Practical applications : This work reports an energy saving scheme. The building communication system constructed by ZigBee can reduce energy consumption and can be easily expanded. The soft sensing technique based on artificial neural network can predict temperatures by using few sensors. The neural network proportional–integral–derivative control algorithm has good performance in the regulation of environmental parameters for a time-varying system. Building energy consumption can be reduced by conducting these measures.

Cleaning coils can be an efficient way to reduce the need for reparations and maintain the functionality of a ventilation system. This study builds upon existing knowledge concerning the contamination of heat exchangers. Through field measurements on coils and heat-recovery units, a laboratory experiment on a coil, and a generic calculation example, this study determines the impact of sustained contamination on heat-recovery units with regards to energy use. Field measurements made before and after cleaning of heat exchangers show an average increase in the pressure drop by 12% and decrease in the thermal exchange efficiency by 8.1% due to mass deposited on the surface of the heat exchangers. Results from a laboratory test show a correlation between the mass deposited on a coil and (1) the increase in pressure drop over the coil, as well as (2) a diminishing heat exchange. Accumulating contamination on heat-recovery units in residential and commercial buildings (over time) is then linked to increasing pressure drop and diminishing thermal efficiency. With models based on these links, energy loss over time is calculated based on a generic calculation example in a realistic scenario.

Practical application : The results from this study emphasize the need for maintenance of buildings with ventilation systems with coils, but more so those with heat-recovery units. The presented field measurements and laboratory study correlate energy loss with sustained accumulation of contaminants on coils and heat-recovery units. These results should serve as a recommendation to property owners considering maintenance of such units in their buildings.

Few studies have investigated the thermal environment of the work area hall in underground metro stations during winter. Two underground stations were chosen within Qingdao Metro Lines 2 and 3 to investigate the thermal environment in the work area hall in northern city metros in China. Air temperatures and wind velocity parameters were identified as key influencing factors and were continuously measured in the work area. The study found that the thermal environment fluctuates frequently in the work area throughout the day. Changes in temperatures and wind speeds were periodically caused by piston wind flowing from the platform level. To improve this heating situation in the work area in winter, the study proposes recycling waste heat from the power equipment rooms, using the air source but through the water cycle heat pump system. Insights from the study may help save energy and improve the thermal environment, and could be applied across metro stations in north China cities in winter.

Practical application : The thermal comfort of the working area in the metro station hall is extremely poor as indicated by a study of Qingdao Metro stations. This paper explores the application of a heat pump as a means of heating the working area to improve the cold and damp winter environment for the metro staff using waste heat from the machine rooms.

Due to the dust deposition on the surface of photovoltaic modules and the air pollution, the power generation performance of photovoltaic modules will be significantly affected. In order to quantitatively estimate the effect of air quality and dust deposition on the power generation performance of photovoltaic modules, a distributed photovoltaic system on a building roof in Shanghai is studied in this paper. Both artificial and natural dust deposition conditions are tested in terms of the influence of these factors on the power generation efficiency of photovoltaic modules. The variation of solar radiation intensity with PM2.5 concentration in Shanghai and the variation of photovoltaic module power generation capacity with PM2.5 concentration are tested and analyzed. The experimental results show that the surface dust of photovoltaic module reduces the power and efficiency of photovoltaic module. Experimental comparison between the dusty photovoltaic module and clean photovoltaic module shows that the dust on photovoltaic modules can reduce the power and efficiency significantly, where the highest power generation decrease is 35.226% and the highest power generation efficiency decrease is 5.546% as indicated in the experiments. Result shows that the amount of solar radiation is exponentially correlated to the PM2.5 concentration.

Practical application : The influence of air quality and dust deposition on the performance of distributed PV modules is of vital importance under severe particulate pollution in Shanghai. This research helps predict the degradation of the photovoltaic system power generation efficiency, and determine whether to clean up the dust on the photovoltaic system according to accumulated PM concentration. This reduces the cost of cleaning of the dust on photovoltaic system. This study provides theoretical and experimental basis for the design of the building roof mounted solar photovoltaic system according to the local haze condition.

The hybrid photovoltaic-thermal system has shown great progress. Electrical energy is produced from PV panels while thermal energy is produced via a working fluid carried through the panels. In this paper, the vertical PV/T is introduced using working fluids such as air and liquid, which serve to control the excess temperature of the PV panels as well as to collect heat to be made available as thermal energy. Installations of PV/T systems on building façades, as well as integration with other technologies such as heat pipe and heat pump are also discussed. Current studies of such building integration technologies are also explored, including the scale of application. This study aims to provide constructive information which can be used in future development of building facades for large-scale applications, to contribute to future sustainable development.

Practical application : This study helps researchers and engineers who are considering photovoltaic thermal systems for building façades to have better understanding of its effect on electrical and thermal energy – for space heating, fresh air supply and hot water supply – using an active building envelope.

Energy consumption forecasting for buildings plays a significant role in building energy management, conservation and fault diagnosis. Owing to the ease of use and adaptability of optimal solution seeking, data-driven techniques have proved to be accurate and efficient tools in recent years. This study provides a comprehensive review on the existing data-driven approaches for building energy forecasting, such as regression models, artificial neural networks, support vector machines, fuzzy models, grey models, etc. On this basis, the paper puts emphasis to the discussion on evolutionary algorithms hybridized models that combine evolutionary algorithms with regular data-driven models to improve prediction accuracy and robustness. Various combinations of such hybrid models are classified and their characteristics are analyzed. Finally, a detailed discussion on the advantages and challenges of current predictive models is provided.

Practical Application : Building energy consumption prediction is important for building energy management, efficiency and fault diagnosis. For existing buildings, multisourced, heterogeneous or inadequate data-driven models may lead to convergence problem or poor model accuracy. To this end, a state of art review on building energy forecasting technique is helpful for related professionals in the building industry.