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Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry have been developed from either forward or inverse modeling approaches. However, these models usually require extensive computer resources and lengthy computation. This paper discusses the use of the multi-layer perceptron (MLP) model, one of the artificial neural network (ANN) models widely adopted in engineering applications, to estimate the cooling load of a building. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing prestigious commercial building in Hong Kong that houses a mega complex and operates 24h a day. The paper also discusses the practical difficulties encountered in acquiring building-related data. In contrast to other studies that use ANN models to predict building cooling load, this paper includes the building occupancy rate as one of the input parameters used to determine building cooling load. The results demonstrate that the building occupancy rate plays a critical role in building cooling load prediction and significantly improves predictive accuracy. [Copyright &y& Elsevier]

Abstract: Hong Kong is located in a typical subtropical region. The buildings in Hong Kong are subjected to high cooling demands for their air-conditioning systems throughout most of the year, and their contribution toward the total energy consumption is about 40%. Therefore, energy efficiency in buildings is essential to reduce the global energy use and improve the local environmental sustainability. This paper provides an overall review of the building energy research and efforts in Hong Kong over the last decade. Various aspects and energy saving measures, including energy policy, energy audit, design, control, diagnosis, building performance evaluation and renewable energy systems, studied or used to enhance the energy efficiency in buildings are reviewed. A brief introduction of the Hong Kong Building Energy Codes (BEC) and Hong Kong Building Environmental Assessment Method (HK-BEAM) are also provided to present the efforts of the local government and community on energy efficiency in buildings. This review aims at providing building researchers and practitioners a better understanding of buildings energy saving opportunities and approaches in cities particularly in subtropical regions and taking further proper actions to promote buildings energy efficiency and conservation. [Copyright &y& Elsevier]

Due to the hot and humid weather, the majority of residential units in Hong Kong are equipped with window-type air-conditioners. However, the provisions made in the building envelope design for their installation are often inadequate, particularly in the clearances for intake and disposal of outdoor air for condenser cooling. Consequently, the air-conditioners would consume an unnecessarily high amount of electricity and at the same time output less cooling. The paper describes a study on the outdoor airflow around air-conditioners in residential buildings and the related thermal phenomena. The CFD code FLUENT was employed to predict the airflow patterns in 20 installation configurations of window-type air-conditioners, which embrace different shapes of clearances around the air-conditioners that are on the same story in a building. The results reveal that insufficient clearance spaces could cause a significant increase in the temperature of the outdoor air entering the air-conditioners, which would also be accompanied by a reduction in the airflow rate. The increase in the electricity consumption of the air-conditioners could exceed 45% for the case where the air-conditioners were drawing in the discharged hot condenser air from other air conditioners located at an opposite wall for condenser cooling. The presence of a sidewall, however, could cause the discharged hot air to move quicker away from the air-conditioner leading to a lower entering air temperature to its condenser. [Copyright &y& Elsevier]