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Abstract This study examines the amount of money that designers and developers are willing to pay to improve different aspects of the environmental performance of exterior envelopes by using office [...]

Surveys have been conducted to obtain information about the building design and energy end-use characteristics of high-rise residential buildings in Hong Kong. The building design characteristics data obtained include the floor areas of residential flats, the ratios of the areas of bedrooms and living and dining rooms to the total flat area, the window-to-wall area ratios, the types of fenestration, and the external-shading devices in facades of residential buildings. The energy data obtained include the household energy and electricity uses, and the type and quantity of appliances used in residential units. The saturation rates of various domestic appliances and their utilisation patterns, and the annual energy use for air-conditioning and water heating in residential units in Hong Kong have been estimated based on the collected data. [Copyright &y& Elsevier]

• The performances of physical and Bayesian approach for sensor bias detection were evaluated. • The superior performance of Bayesian model in handling cases with incomplete data was explained. • Effects of the prior belief with or without being updated were discussed. Together with the thermo-physical relationships among the flow rates and temperatures of water in a piping system, the Bayesian method was employed to develop a model for detection and evaluation of biases of water flow and temperature sensors in a central chiller plant. The model can handle biases of multiple sensors occurring simultaneously and can remain functional when the coverage of the available measurements is incomplete. A series of case studies was done to verify the performance of the model and for comparison with the conventional method that is based solely on the thermo-physical relationships. The cases studied involved the use of synthetic plant operating data and actual operating records of an existing chiller plant. In this paper, the theoretical basis of the model is outlined, and explanations are given for the superior performance of the Bayesian method in handling cases with data that cannot fully cover the required range of operating chiller patterns. Results of the cases unveiled the effects of the prior belief with or without being updated during the estimation process, and of biases occurring in steps at the same time and at different times, as well as those that would increase with time. Furthermore, the case studies showed that the Bayesian method was able to detect sensor biases of a magnitude of ± 0.5 °C or lower. [ABSTRACT FROM AUTHOR]

Highlights: [•] A method to evaluate the probability of saving shortfall for energy performance contracting projects is proposed. [•] Two calibrated building energy models are developed using EnergyPlus. [•] The influential parameters affecting the chiller plant energy use are identified. [•] The probability distributions functions are developed using empirical data. [•] A case study is analysed to illustrate the methodology. [Copyright &y& Elsevier]