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The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [ABSTRACT FROM AUTHOR]

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 paper, three predictive models, namely multiple regression model, Levenberg–Marquardt back-propagation (LM-BP) model and similar days method based on combined weights, have been deployed. By assessing the influential factors on internal heat gains, fundamental theories, structures, equations and parameters of these models are thoroughly proposed. To examine the prediction techniques, an office building in China was considered. It was found that all the proposed models have high accuracy; however, the LM-BP neural network showed the most precision among other models with RMSE = 15.59, MAE = 10.16 and MAPE = 6.35. This model had a higher agreement with the actual internal heat gains compared to the predetermined working programs in the ASHRAE standard 90.1. The proposed models used in this study can lead to providing a theoretical base for scholars and engineers to improve the predictive control of HVAC systems, which plays an important role in enhancing thermal comfort, saving energy of residential buildings. [ABSTRACT FROM AUTHOR]

Abstract: A number of radiant heating/cooling systems have been applied in Mainland China in recent years for its improved thermal comfort and inherent energy saving potential. Because the systems require relatively higher temperatures for cooling and lower temperatures for heating, many natural low-grade energy sources can be directly or indirectly used. However, because of a lack of information about prior practical projects, a number of difficulties in design, construction and management of the systems have been encountered, and energy efficiency is not necessarily achieved in all situations. This paper reviews the practical applications in four major projects involving different building types located in different climatic cities and presents the associated considerations in system design. Other factors affecting the energy efficiency of the systems are identified, such as the spatial convection and radiation heat transfer processes in indoor environments and the envelope thermal properties. Further studies are needed to achieve system optimization and to realize the full energy saving potentials of radiant systems by developing analytical design methods and monitoring the actual energy use of such systems in completed projects. [Copyright &y& Elsevier]

Abstract: In Hong Kong, conventional air-conditioning (AC) systems cause a high energy consumption and poor indoor thermal comfort. This paper investigated the AC load profiles of three typical local commercial buildings, i.e. office, hotel and retail, and examined the energy consumption of liquid desiccant cooling system (LDCS) for these buildings. Simulation results showed that the cooling load contributed to more than 98% of total annual load, with high latent load proportion from March to September. The high reheating ratio, i.e. from 60% to 90%, is found to be the main reason for the poor thermal comfort. Therefore, the LDCS which could handle sensible and latent loads separately was proposed. However, the electricity-driven LDCS was found not suitable for local commercial buildings. significant energy saving could be achieved by the solar-assisted LDCS system with thermal storage, when the installation area for solar collectors is larger than the minimum required one, i.e. 9.7m2/(kWm−2) for office and 12.7m2/(kWm−2) for hotel buildings. Energy saving of different system types with different installation areas was also studied. The solar-assisted LDCS shows more energy saving in winter but less in summer. Results and conclusions can be useful for researchers and local engineers. [Copyright &y& Elsevier]

Abstract: A traditional Chinese heating system, the Chinese Kang, is used by 175 million people in detached houses in the rural regions of China, especially in Northeast China. This system utilizes biomass such as corn stalks, straw, corncob and energy plants as the heat sources. The objective of this paper is to establish a set of models to simulate the energy performance of the Kang heating system in one Chinese detached house. An experimental field study was carried out to collect practical parameters in a newly constructed Chinese detached house. The dynamic performance of the Kang heating system was simulated by using IDA-ICE 4.0 embedded with an empirical model built in the field study. The results show that the simulation can obtain good overall agreement with the field measurement results. It was confirmed that the Kang model created by IDA-ICE 4.0 is capable of simulating the performance of the Kang system and of calculating energy consumption in the detached house. Moreover, the result reveals that the thermal environment in the present Chinese detached house is still poor during the severe cold season if only the Kang system is used to heat the whole house. [ABSTRACT FROM AUTHOR]

[Display omitted] • Coal combustion, ASHP, solar heating, gas furnace and electric heating are compared. • Thermal comfort, economic, energy consumption and environmental benefit are evaluated. • Different PMV-PPD are set, and the design thermal index is amended. • The optimal heating mode of rural buildings in cold areas is found. In recent years, space heating modes are diversified. In the early stage of space heating design, we should reasonably evaluate and optimize the heating mode in order to get a better heating effect. In the past, the evaluation of different heating modes was mostly single evaluation. In this paper, the thermal comfort, economic, energy consumption and environmental benefit are comprehensively evaluated. Four heating modes in the "Coal to electricity" project of China are compared with coal combustion. The modes are ASHP (Air Source Heat Pump), solar heating, gas furnace and electric heating. Based on PMV-PPD, a more reasonable design thermal index of 35.18 W/m2 is obtained. The matched capacity and operation of heating system are optimized. The results show that ASHP combined with floor radiation heating is the best space heating mode in cold areas of China. The comprehensive rate of the four evaluations is 89.64%, and its thermal comfort is the best. For a 120 m2 house in Lanzhou, after the transformation of traditional coal burning heating mode, the static payback period is 6.9 years. The actual energy consumption reduction of society is 2,769 kg/year. The reduction of CO 2 emissions is 4,014 kg/year. [ABSTRACT FROM AUTHOR]