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• Automatic MiC envelopes and layout generation by a novel SSG-MOO method. • Multi-objective optimization formulation for passive MiC design. • A pilot MiC study in Hong Kong produced 5 selected Pareto optima out of 625. • Up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement against the baseline. • A multi-level analysis of results and design strategies for practitioners. Modular-integrated Construction (MiC) is an emerging construction technique promoted in the building sector for high productivity and low waste emission in the construction phase; yet, the standardized modules also bring new challenges, such as balancing passive energy efficiency and spatial daylight autonomy, to the operational phase. This paper proposes a Symmetric Skeleton Grammar-based Multi-Objective Optimization (SSG-MOO) method to formulate parametric MiC envelopes and detailed layout, with the two objective functions being energy efficiency and interior daylight performance in the operational phase. Pareto optima of the SSG-MOO, computed by the Non-dominated Sorting Genetic Algorithm II, are generally verified and analyzed in three levels, i.e., MOO's solution space, SSG layout, and MiC design parameters. A case study of MiC residential building in Hong Kong demonstrated the SSG-MOO method through five new passive MiC designs (i.e., spatial reorganization of three architectural modules, and parameter tuning of the envelops and corridors), achieving up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement compared to the baseline design. The contribution of this paper is two-fold, including a novel and sound SSG-MOO formulation for parametric MiC designs, and offering time-efficient and evidence-based design tactics for MiC designers and industrial practitioners to push boundaries of MiC. [ABSTRACT FROM AUTHOR]

In this paper, we estimate the energy efficiency of educational buildings with the case study of buildings in City University of Hong Kong by constructing an energy demand stochastic frontier model. The model is estimated by using the university statistical data from 2011 to 2015. For the consistent frequency of data among the variables, we have adopted the quadratic-match sum method to convert annual university report data into a monthly dataset. Our result shows the average energy efficiency is 0.87, implying that 13% of total energy consumption can be saved. We then calculate how much of the energy saving potential has been achieved by constructing the performance score, which increases from 0.08 to 0.17. It implies that the campus performs more efficiently in saving energy over time. We further develop econometric decomposition analysis based on the energy demand frontier model to identify the factors affecting energy consumption. It suggests that research activities account for a large share of overall energy consumption. Analysis on energy end-use shows university should improve efficiency in lab instrument as it is least efficient among the four usages. We expect this paper can provide the fundamental and methodological guideline for university-scale energy efficiency estimation. • Estimating energy efficiency of educational buildings needs to consider the composition of research related factors. • Energy efficiency of campus building presents increasing tendency with seasonal cycle over time. • Research related variables affect significantly on energy efficiency of educational buildings. • Energy use in lab instrument needs to be effectively managed to save energy. [ABSTRACT FROM AUTHOR]

Buildings are responsible for about 92% of the total energy end-use in Hong Kong, of which above 70% is from the commercial sector. Most of the buildings in Hong Kong are high-rise, and approximately 15% of the total building stock is commercial buildings. Despite the considerable improvement in the understanding of the life cycle energy use of office buildings, there is still a lack of research into the life cycle energy demand of high-rise office buildings. Such knowledge is however essential for facilitating building energy conservation in the high-rise urban environment. The aim of this paper is to investigate the life cycle energy use of high-rise office buildings. The research was carried out through a critical literature review and case studies of ten real-life high-rise office buildings in Hong Kong. Results show that the life cycle energy consumption is 51.78–73.64 GJ/m 2 over the 50-year study period. Building operation consumes 78–89% and the rest (i.e. 11–22%) is taken by the embodied energy. Despite the distinction in terms of the amount of embodied energy between high-rise buildings and low-rise counterparts, no clear correlation is found between building height and embodied energy intensity. Moreover, energy use for material manufacturing and transport should be prioritised in reducing the embodied energy, of which the transport energy needs to be taken into extra consideration for the case of Hong Kong. The findings should inform construction industry participants of the significant potential in reducing the embodied energy of high-rise office buildings. The paper profiles the life cycle energy use of high-rise office buildings and should be important for the policy formulation towards the holistic energy conservation in high-rise buildings over their lifespans. [ABSTRACT FROM AUTHOR]

Electricity consumption in cities is steadily increasing. Using a life cycle approach and fuel mix data from power companies’ sustainability reports, this paper analyzes greenhouse gas (GHG) emissions from electricity consumption in Hong Kong. The results show that coal contributed on an average 74.3 percent, liquefied natural gas 25.1 percent, and oil 0.6 percent of the thermal energy consumed for generating electricity in Hong Kong between 2002 and 2015. Besides, Hong Kong imported an average of 7.96 billion kWh per year net electricity from a nuclear power plant in Shenzhen. During this period, GHG emissions from annual electricity consumption ranged between 27.0 and 34.1 million tons (MT) and the emission factor ranged between 702 and 792 g CO 2 -eq/kWh. Hong Kong’s gross domestic product (GDP) increased steadily from USD 176 billion in 2002 to USD 297 billion by 2015. As a result, Hong Kong’s electricity productivity increased from 4.62 to 6.75 USD/kWh while GHG emission from electricity consumption per GDP decreased from 0.153 to 0.104 MT CO 2 -eq/USD billion. Hong Kong’s annual electricity consumption was predicted over the short-term period (2016–2020) and medium term (up to year 2030). Electricity consumption is likely to increase to 44.63 billion kWh by 2030 while GHG emissions from electricity consumption would increase to 33.92 MT of CO 2 -eq. The implications are discussed at the end of the paper. [ABSTRACT FROM AUTHOR]

Energy consumption of lift systems is one key issue in modern high-rise buildings, drawing property owners' attention and accounting for 6% of total electricity consumption by end-use in Hong Kong. A Benchmarking Energy Performance Indicator (BEPI), , measured in J.kg−1.m−1 and proposed by the first author of this paper for lift installations is mentioned in the Technical Guidelines of the Building Energy Code , as one emerging good engineering practice. BEPI is a fair parameter for comparing energy performance of lifts irrespective of their brand, model, travel, speed, capacity and control. It considers energy performance due to both the motor drive efficiency and traffic control intelligence. However, one main obstacle to make it statutory is the lacking of a generic monitor able to retrieve three sets of real time data (normally unavailable on an existing lift) to compute the BEPI, namely energy consumption, instantaneous car load and traveling distance, and to collect ample data statistically reliable enough to determine an acceptable threshold value. This paper describes the development of a proof-of-concept prototype BEPI monitor by giving full technical details on the rationale and history of development, the hardware components, software framework, and updated numerical results of one implementation inside the headquarters of Electrical & Mechanical Services Department (EMSD) of HKSAR. Experiences in installing and calibrating those external sensors that make the whole system non-disturbing to normal lift operation, as well as the procedures in computing the BEPI, are discussed in greater details. It has been shown that the BEPI is traffic dependent but the weekly average of it is relatively stable, confirming it may be robust enough for benchmarking purpose. The solution described in this paper may help roll out the monitoring of BEPI for all lifts inside and outside Hong Kong. [ABSTRACT FROM AUTHOR]

Inter-building effect (IBE), which refers to the shading effect from surrounding buildings, plays an important role in building energy use in high-density cities. However, it is customary to neglect the IBE during energy simulation. Four issues are observed on previous research: 1) it has been controversial whether the IBE significantly affects energy consumption, 2) most studies used low-rise or medium-rise residential buildings as references, 3) most studies were conducted with hypothesised buildings, 4) most studies did not consider window blinds effect on IBE. These issues inhibit the theoretical understanding of high-rise building energy performance in cities and jeopardise the achievement of accurate simulation. This paper thus aims to investigate the IBE on the energy use of high-rise office buildings in Hong Kong as a typical high-density city. The IBE of ten selected real-life office buildings in their real-life communities was analysed. Four scenarios were compared, namely, simulation of building with both IBE and window blinds (base case), simulation of building with IBE but no window blinds, simulation of isolated building with window blinds, and simulation of isolated building without window blinds. The results show that the IBE influences the total energy use by up to 13.1%. Compared with the base case, heating, ventilation, air-conditioning (HVAC) and the lighting consumption deviation with different scenarios fluctuated largely, ranging from −11.8% to 18.8% in HVAC consumption, and from 0.1% to −27.6% in lighting consumption. An offset effect was found between the decreased lighting consumption and the increased HVAC consumption. From the floor-level analysis, with real communities, lighting energy use decreased with height among all the buildings generally. A multi-variant regression model was established to evaluate the relationship between IBE variables and building energy deviation caused by IBE. In addition, the results conclude that shading blinds cannot be overlooked when examining IBE on building energy use. These findings reveal the importance of considering IBE on building energy consumption in high-density contexts on a case-by-case basis. [ABSTRACT FROM AUTHOR]

Abstract: Currently one of the most promising power solutions for remote rural areas and isolated islands which are far away from utility grid is the stand-alone solar photovoltaic (PV) renewable energy system or hybrid solar–wind power system. This paper presents the investigation results of a real remote solar PV project on an island in Hong Kong. The stand-alone PV system, rated at 19.8kWp, is established on a remote island for power generation to local residents. Power on this island was originally supplied by diesel generators and this new solar energy system has significantly reduced fuel costs and alleviated environmental pollution. The on-site entire system’s operating data was collected for one whole year in 2011, and the energy performance of the PV array, inverters, battery bank and the entire PV system were analyzed in terms of daily energy balance, normalized performance parameters and overall system energy utilization ratio. The results from this long term system monitoring and its evaluation enables a detailed inspection of system operating performance with respect to the technical issues, which provides a useful reference for future applications of solar photovoltaics in remote islands. [Copyright &y& Elsevier]

• A POE-integrated simulation method is proposed to address energy occupant behavior. • Opening windows and operating AC were found to co-exist which affects simulation accuracy. • The new method improves energy simulation accuracy by 14% for domestic areas. • The method improves energy simulation accuracy by 16% for total building areas. Occupant behavior plays a critical role in building energy consumption, particularly in residential buildings. However, occupant behavior is complicated and varies significantly from case to case. Also, energy modeling of high-rise buildings is far less explored than that of low- or medium-rise buildings. This paper aims to improve accuracy in building energy simulation by utilizing Post Occupancy Evaluation (POE) data to calibrate energy model. Drawing on a review of the literature of occupant behavior and building energy modeling, the paper provides a calibration method of integrating POE data into an energy model, which is demonstrated using a real-life typical 40-storey residential building in Hong Kong. The developed method addresses seven updated input parameters, namely, schedule, devices, air-conditioners, windows, lights, domestic hot water, and cooking. By comparing the two energy modeling processes, i.e. with and without POE input, and their resultant estimated energy consumption, the paper quantifies the impact of occupant behavior on building energy consumption. Annual metered data together with energy bills obtained from the POE were utilized to validate the models. The results show that the use of the developed POE-integrated method helped to improve accuracy in energy consumption prediction by 14% for the total building floor area and by 16% for the total residential area. From examining the impacts of the seven input parameters, the paper reveals the key energy use sensitive occupant behaviors within high-rise residential buildings in Hong Kong. These include: the number of residents in each unit; adoption of window type and split type of air-conditioners; window and air condition operation modes; cooking time on weekdays and weekends; and time spent on hot water showering. The developed method can assist building designers and services engineers to estimate building energy use more accurately and provides a scenario analysis tool for clients and facility managers to develop effective energy conservation strategies. [ABSTRACT FROM AUTHOR]

• M ultiple sources of uncertainties for battery electric vehicle routing. • Max imization of energy consumption reliability and travel time reliability. • An exact solution algorithm for determining all non-dominated paths efficiently. • Computational experiments on a real case in Hong Kong for the entire road network. This paper proposes a bi-objective reliable path-finding algorithm for routing battery electric vehicles on a road network, with vehicles' energy consumption uncertainty and travel time uncertainty. A bi-objective stochastic optimization problem is proposed and formulated to simultaneously maximize energy consumption reliability (ECR) and travel time reliability (TTR). ECR is defined as the probability of finishing a trip without exhausting a given battery energy budget, while TTR is the on-time arrival probability with the travel time budget. In this study, the proposed optimization problem is decomposed into two sub-problems: (1) finding K most reliable paths for maximizing the TTR objective and (2) finding the most reliable path for optimizing the ECR objective. Then, a novel ranking algorithm is proposed to exactly solve the formulated optimization problem. A case study is carried out on Hong Kong's road network to demonstrate the efficacy and efficiency of the proposed algorithm for real-world applications. [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: Energy consumption by passenger transport in Hong Kong increased rapidly in the past decades and in 2008 it accounted for 19.7% of total energy use. Improving energy efficiency has been widely regarded as an effective way for reducing energy use in the transport sector. However, the expected energy savings from energy efficiency improvement are likely to be discounted due to the existence of rebound effect. This paper employs econometric models to estimate the direct rebound effect for private passenger transport in Hong Kong. We find that the magnitudes of the direct rebound effect are respectively 45% and 35% for 1993–2009 and 2002–2009, which indicates that there was a declining trend in the direct rebound effect for passenger transport over time. It also indicates that the direct rebound effect needs to be taken into consideration in assessing the impact of energy efficiency measures on reducing energy use in Hong Kong. [Copyright &y& Elsevier]

Abstract: The shading-type BIPV claddings can act as power generators as well as external shading devices and insulation panels. There is little available information about the impacts of orientations and inclinations on the combined energy effects of the shading-type BIPV claddings, including the power output of PV modules, the cooling load reduction of windows and concrete walls. It is worth studying the effects of different shading-type BIPV cladding designs on the total energy saving in order to maximize the system’s energy performance. By considering the meteorological conditions in Hong Kong, the energy effect of the shading-type BIPV claddings with different surface azimuth angles, in terms of electricity generation and cooling energy consumption reduction is analyzed in this paper. Based on the investigations, the optimum design of the shading-type BIPV claddings for different orientations can be achieved. [Copyright &y& Elsevier]

Abstract: In metropolitan cities like Hong Kong where land value is high, highrise commercial and residential buildings with “central core” design are developed. The lift lobbies in the buildings are usually located in the centre of the building to free up peripheral areas to provide valuable exterior view. The lift lobbies have no window provisions and electric lighting is switched on for 24h continuously consuming non-renewable energy. Different types of light guides/light pipes have been proven to be capable to transfer daylight into deep floor plan during both clear sky and overcast periods. However, the thickness of light guide requires 3m headroom clearance for installation whilst the headroom of the highrise buildings is usually limited to 2.8m in order to build more storeys. In this research, a remote source lighting system (RSL) is introduced to illuminate the enclosed lift lobbies. The system composed of prismatic light pipe and optic fiber to address the problem of limited headroom. Simulation of the system was carried out and reported in the paper, indicating that this lighting system can solve the energy consumption problem in the lift lobby in terms of renewable energy use and natural lighting application. This research concentrates on highrise residential buildings. [Copyright &y& Elsevier]

Abstract: The concern on climate change leads to growing demand for minimization of energy use. As building is one of the largest energy consuming sectors, it is essential to study the impact of climate change on building energy performance. In this regard, building energy simulation software is a useful tool. A set of appropriate typical weather files is one of the key factors towards successful building energy simulation. This paper reports the work of developing a set of weather data files for subtropical Hong Kong, taking into the effect of future climate change. Projected monthly mean climate changes from a selected General Circulation Model for three future periods under two emission scenarios were integrated into an existing typical meteorological year weather file by a morphing method. Through this work, six sets of future weather files for subtropical Hong Kong were produced. A typical office building and a residential flat were modeled using building simulation program EnergyPlus. Hourly building energy simulations were carried out. The simulated results indicate that there will be substantial increase in A/C energy consumption under the impact of future climate change, ranging from 2.6% to 14.3% and from 3.7% to 24% for office building and residential flat, respectively. [Copyright &y& Elsevier]

Abstract: It becomes popular to use computer simulation technique to evaluate the performance of energy utilizations in buildings. The hourly weather data as simulation input is a crucial factor for the successful energy system simulation, and obtaining an accurate set of weather data is necessary to represent the long-term typical weather conditions throughout a year. This paper introduces a stochastic approach, which is called the first order multivariate Markov chain model, to generate the annual weather data for better evaluating and sizing different energy systems. The process for generating the weather data time series from the multivariate Markov transition probability matrices is described using 15-years actual hourly weather data of Hong Kong. The ability of this new model for retaining the statistical properties of the generated weather data series is examined and compared with the current existing TMY and TRY data. The main statistical properties used for this purpose are mean value, standard deviation, maximum value, minimum value, frequency distribution probability and persistency probability of the weather data sequence. The comparison between the observed weather data and the synthetically generated ones shows that the statistical characteristics of the developed set of weather data are satisfactorily preserved and the developed set of weather data can predict and evaluate different energy systems more accurately. [Copyright &y& Elsevier]

Abstract: The shading-type building-integrated photovoltaic (BIPV) claddings can act as power generators as well as external shading devices of a building, which reduce the energy consumption of the building. However, there is little information about energy impacts of different tilt angles of the shading-type BIPV claddings. By considering the typical meteorological conditions of Hong Kong, the energy performance of the shading-type BIPV claddings, in terms of the electricity generation and the cooling load reduction, is analyzed in this paper. The optimum tilt angle of PV modules for maximum electricity generation is found to be 20° instead of local latitude. Combining electricity generation and cooling load reduction, it can be concluded that the optimum tilt angles for the first type of the shading-type BIPV claddings vary from 30° to 50°, while the optimum tilt angle for the second type is 0°. [Copyright &y& Elsevier]

Abstract: A benchmark study of the energy efficiency of private office buildings in Hong Kong was conducted in 2002 because energy efficiency was declining. In the study, private office buildings were divided into five user groups. For each group, a multiple regression model was developed to find the relationship between Energy Use Intensities (EUIs) and other factors, such as operating hours, for normalization and benchmarking purposes. In this paper we make use of the regression results to study the energy efficiency of private office buildings by different grades. In Hong Kong, office buildings are divided into three grades (A, B, and C) based on the quality of the facility, which is reflected in rental values; a Grade A office building denotes expensive luxury. We found that the EUI of Grade A office buildings is the highest, consuming over 50% of the total energy used in office buildings. Recently, the annual EUI of office buildings has improved even though Grade A floor space is increasing. This may be due to the promotion of the energy efficiency program launched in the last decade. [Copyright &y& Elsevier]

Abstract: Mandatory energy codes to curb energy use of residential buildings have been formally launched in China for more than two decades but little has been publicized in literature. Similar codes are not available for residential buildings in Hong Kong, but most residential buildings in Hong Kong, especially public housing estates, are HK-BEAM certified to demonstrate their compliance with regulatory and basic design requirements. Given HK-BEAM is internationally recognized and there are doubts about the effectiveness of the China codes, how the energy efficiency of the HK-BEAM certified buildings compare with buildings in compliance with the China codes is of interest to most building designers and policy makers. This paper describes how the energy efficiency of a case study building in compliance with the China codes compare with the one in compliance with HK-BEAM. The energy simulation by HTB2 and BECRES reveal that the case study building in compliance with the China codes is 51.1% better in energy use. In the study, the relative impact of each compliance criterion on energy use and cooling load has been quantified by sensitivity analysis. The sensitivity values indicate that energy use is most sensitive to air-conditioning operation hours, indoor design temperature, coefficient of performance (COP) of the room air-conditioners (RAC) units, and the envelop characteristics. The results of this study indicate that a HK-BEAM certified building cannot satisfy the China codes requirements. This provides good reference to the policy makers, the building owners, and to the China and Hong Kong Governments when considering reciprocal recognition of building energy codes. [Copyright &y& Elsevier]

[Display omitted] • The communal areas can have different levels of energy performance in the 15 types of public residential buildings under study. • Spatial design features can evidently affect the energy consumption in the communal areas. • The ability to harvest daylight serves as a key determinant of energy efficiency. • Both econometric and machine learning techniques are proved to be effective to generate reliable findings. In this paper, we construct a unique database for 1228 residential buildings in Hong Kong to investigate how the spatial features of these residential buildings affect the electricity consumption in the communal area. We choose Hong Kong for this analysis as the city owns a large number of standard-type residential buildings managed by the public institution, which could be affected strongly by environmental policies. Both the machine learning method, based on the Least Absolute Shrinkage and Selection Operator (LASSO), and econometric regressions are adopted to analyse the data. We first utilize the machine learning LASSO technique to identify the most relevant factors for the subsequent econometric analysis. Our results show that the electricity demand for relatively low consumption building types, such as Twin Tower, is 6% lower than that of the high consumption building types. Newly constructed buildings usually belong to the medium consumption types, with the estimated monthly electricity consumption per apartment in communal areas to be around 50.2 kWh on average in 2020. These findings shed light on the nexus between spatial features and energy use for complex buildings, potentially contributing to the better crafting of energy-saving policy and the improvement of residential building programmes. [ABSTRACT FROM AUTHOR]

• In-situ monitoring allows for a more reliable estimation of envelope performance of residential buildings. • Policy differences are one of the main causes for the variation in building envelope performance across regions. • Potential global warming impacts ought to be considered when pondering on the future direction of envelope development of residential buildings. • Interactive policy framework underscores the necessity of devising more comprehensive public policies pertaining to energy saving. Climatic conditions can exert significant impacts on energy demand of residential buildings. Therefore, case-based evidence is necessary for aiding local policy making on building energy performance. By designing and carrying out in-situ monitoring campaigns respectively in Cambridge, Hong Kong and Shanghai, we present in this paper a cross-regional analysis of actual building envelope performance in these three climatic regions that operate under different energy efficiency policies. Compared with conventional tabulated data, information gleaned from the method of in-situ monitoring shows lower uncertainty and higher precision, especially when the wall has good thermal properties. By comparing practices in different regions and with accurate post-occupancy thermal data, the analytical results further show that the effectiveness of building-related policies on energy performance varies across regions. This is one of the pioneering studies that make interactive policy recommendations based on the evidence obtained from cross-regional, in-situ monitoring campaigns. [ABSTRACT FROM AUTHOR]

• Building Bio-Climatic Charts are proposed for different climate change scenarios. • Time-varying significance of nine design parameters in this century are provided. • Effectiveness of airtightness will increase up to 329% by the end of this century. • Cooling potentials of natural ventilation will significantly decrease up to 69%. • A holistic passive design can reduce the building annual cooling load by 56.7%. The application of passive design strategies is crucial at the early architectural design stage for building energy use minimization. However, the time-varying effectiveness of passive design strategies in responding to future climate change in hot and humid climates are rather limited in the literature. This paper aims to examine the dynamic effectiveness of passive design strategies for residential buildings in Hong Kong under the context of future climate change. Using the newly developed hourly weather data and adaptive comfort standard model, the dynamic effectiveness of viable passive design strategies for residential buildings are evaluated over time in the 21st century by plotting Givoni building bio-climatic charts (BBCC) and simulation-based sensitivity analyses in a validated EnergyPlus model. Results show that solar protection strategies are still the highly sensitive strategies for building energy performance and the effectiveness of external windows' airtightness is expected to increase up to 329% by the end of this century, whereas the cooling potential of ventilation utilization will significantly decrease over time. When the different combination of sensitive passive design parameters is implemented onto the baseline residential building model for different climate scenarios, the annual and peak cooling load can be reduced up to 56.7% and 64.5%, respectively. [ABSTRACT FROM AUTHOR]