Energy-cost allocation systems apportion heating and/or cooling costs among the individual apartments in centrally-metered buildings based on various measures of relative energy use or thermal comfort. The most commonly used systems measure one or more parameters related to the thermal output of the terminal elements. In this paper, a new method for energy-cost allocation purposes was developed and studied. Taking advantage of the theory of frequency response, the individual apartments’ energy consumption for cooling in summer may be calculated using several parameters that include indoor and outdoor temperatures and the values of solar radiant-intensity. Experiments were done in this study, which indicates that the method of frequency response is fairly good in calculating the energy use of cooling.

A dynamic model that describes the cooling coils’ thermal qualities is developed and solved using the method of classical control theory. The dynamic relationships are obtained between the coil’s heat exchange and its five important parameters that include inlet air temperature, inlet air humidity, inlet water temperature, airflow rate and water flow rate. Experiments have been done to validate the model. Afterwards, simulations are made by the model to analyze the dynamic heat exchange of coils when some perturbations occur under different initial conditions. Then, some useful conclusions are drawn based on the analysis.

This study mainly explored the thermal comfort from the perspective of physiology. Three physiological parameters, including skin temperature (local and mean), electrocardiograph (ECG) and electroencephalogram (EEG), were investigated to see how they responded to the ambient temperature and how they were related to the thermal comfort sensation. A total of four ambient temperatures (21℃, 24℃ , 26℃ and 29℃ ) were created, while the other thermal conditions including the air velocity (about 0.05±0.01 m/s) and the air humidity (about 60±5 m/s) were kept as stable as possible throughout the experiments. Twenty healthy students were tested with questionnaire investigation under those thermal environments. The statistical analysis shows that the skin temperature (local and mean), the ratio of LFnorm to HFnorm of ECG and the global relative power of the different EEG frequency bands will be sensitive to the ambient temperatures and the thermal sensations of the subjects. It is suggested that the three physiological parameters should be considered all together in the future study of thermal comfort.

his paper mainly concerned about the dynamic response model of wet cooling coils that is developed by the Laplace transform method. The theoretic equations are firstly established based on the theory of energy conservation. Then, the transfer functions on the transient responses of wet cooling coils have been deduced using the method of Laplace transform. The transfer functions reveal the dynamic relation- ships between the inlet variables and the outlet ones of the cooling coils. Partial-fraction method and Newton–Raphson method are both used in the inversion of the transfer functions from the s-domain to s-domain. To make the dynamic model of wet cooling coils more adaptive, RBFNN method is employed to determine the coefficients of heat and mass transfer. Experiments have been done and manifested that the coefficients of heat and mass transfer by RBFNN will be of great value to the validity of the transient response model of wet cooling coils in this study.

Predicting the next-24-hour load in a building is essential for the optimal control of heating, ventilating and air-conditioning (HVAC) systems that use thermal/cool storage technology and also for cost and energy reduction of the non-storage systems. To fully integrate the advantages of several models and improve the accuracy of forecasting load, the application of the combined forecasting method to hourly load forecasting is presented in this paper. The method of Analytic Hierarchy Process (AHP) is employed to deduce the weights of each model. A case study shows that the combined forecasting model based on AHP may be better than the individual ones in predicting the building’s hourly load for the future hours.