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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]

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]

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]

• 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]

[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]