Search

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 today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact on the required cooling load of buildings, practices currently adopted in modeling the presence and activity of people in buildings do not reflect the complexity of the impact occupants have on building cooling load. In contrast to previous artificial neural network (ANN) models, most of which employ a fixed schedule or historic load data to represent building occupancy in simulating building cooling load, this paper introduces two input parameters, dynamic occupancy area and rate and uses it to mimic building cooling load. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing grade A mega office buildings in Hong Kong with tenants including many multi-national financial companies that require 24-h air conditioning seven days a week. The dynamic changes that occur in the occupancy of these buildings therefore make it very difficult to forecast building cooling load by means of a fixed time schedule. The performance of simulation results demonstrate that building occupancy data play a critical role in building cooling load prediction and that their use significantly improves the predictive accuracy of cooling load models. [Copyright &y& Elsevier]

Climate change may seriously affect the energy consumption of buildings by influencing their air conditioning loads, especially the ventilation loads which vary directly with the local weather conditions. Research on how the ventilation load responds to climate change is of great significance, especially in coastline subtropical regions like Hong Kong. This paper investigated the impacts of climate change on buildings' ventilation load and building energy use in Hong Kong with the hourly meteorological data from 1950 to 2007. Results have been well validated by the simulation of a typical local hotel building during this period. The results show that climate warming increases both sensible and latent parts of the cooling ventilation load. The latent part, which occupies ∼80% of the total ventilation load, increases at a higher rate, about twice of that of the sensible one. Furthermore, it is found that the urban heat island (UHI) effect causes a much higher growth rate of the ventilation load at night, which is about three times compared with that in the daytime. The latent part of the cooling ventilation load at night, which is found to be the most sensitive component to the climate change, plays a most significant role in the energy consumption increase. The possible measures were thus suggested to avoid negative changes of the ventilation load. Besides, reducing the UHI effect by better urban planning also significantly benefits the local buildings with a long air-conditioning operation time. [ABSTRACT FROM AUTHOR]

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: The ground-coupled heat pump (GCHP) system is becoming attractive for air-conditioning in some moderate-weather regions due to its high energy efficiency and reliable operation capability. However, when the technology is used in buildings where there is only cooling load in hot-weather areas like Hong Kong, the heat rejected into the ground by the GCHP systems will accumulate around the ground heat exchangers (GHE). This heat accumulation will result in degradation of system performance and increment of system operating costs. This problem can be resolved by using the hybrid ground-coupled heat pump (HGCHP) system, which uses supplemental heat rejecters to reject the accumulated heat. This paper presents a practical hourly simulation model of the HGCHP system by modeling the heat transfer process of the system’s main components. The computer program based on this hourly simulation model can be used to calculate the hour-by-hour operation data of the HGCHP system. As a case study, both a HGCHP system and a traditional GCHP system are designed for a hypothetic private residential building located in Hong Kong, and the economic comparisons are conducted between these two types of systems. The simulation results show that the HGCHP system can effectively solve the heat accumulation problem and reduce both the initial costs and operating costs of the air-conditioning system in the building. [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]

A habitable dwelling should be safe, comfortable, and adequately ventilated. In many densely populated cities, the housing demand of citizens is met by clusters of high-rise residential towers. When buildings are closely sited, the influence of adjacent buildings on the availability of cross-ventilation becomes a critical building design consideration. This paper reports on the results of computational fluid dynamics (CFD) simulation studies on such effects based on estate models that comprised an array of building blocks. The result shows that cross-ventilation in buildings downstream of other buildings would be much reduced, especially when the buildings were aligned facing the wind direction and when the spaces between buildings were small. Shortening the upstream buildings and laying out the buildings in a staggered pattern would significantly improve cross-ventilation in the downstream buildings. [ABSTRACT FROM AUTHOR]

Abstract: Near-extreme outside dry- and wet-bulb temperatures are essential for the design of building HVAC systems. Coincident design temperatures currently defined by ASHRAE and CIBSE may not fully allow engineers to design an HVAC system that can match a risk level desired for the problem at hand. A rational method is therefore presented in this paper for the proper selection of coincident climate design conditions, which is based on the theory of probability. An average statistic risk level has been proved to be approximately equal to the annual percentile of coincident dry- and wet-bulb temperatures for HVAC systems whose thermal time constant is less than 1h. An algorithm is also developed to determine the contours of equal risk. Representative coincident design dry- and wet-bulb temperatures are obtained through statistic analysis of the 15 years of weather records in Hong Kong. These rationally derived outside design temperatures are compared with the coincident dry- and wet-bulb temperatures currently defined by ASHRAE and CIBSE. [Copyright &y& Elsevier]

Based on the data collected in recent surveys, models have been established to represent the energy characteristics of living and dining rooms and bedrooms in typical residential buildings in Hong Kong, in respect of the layout and construction; the density and pattern of occupation; the power intensities and operating patterns of lighting and appliances; and air-conditioner operation patterns. With the help of computer simulation, the impacts of varying these characteristics on the annual space cooling load have been evaluated, which allowed representative internal load patterns for residential units to be defined. These are essential data for predicting energy use in residential buildings, which, in turn, is an indispensable part of studies on ways to assess and minimise energy use in such buildings. This paper presents the building model and the internal load and air-conditioner operation patterns established in the study. [Copyright &y& Elsevier]