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The Heating, Ventilation and Air Conditioning (HVAC) system is a significant energy consumer in built environments, and the building energy consumption could be minimised by optimising HVAC controls. Hence, this paper aims to investigate the applicability of Variable Refrigerant Flow (VRF) air conditioning systems for optimising the indoor comfort of buildings in Sri Lanka.

To address the research aim, the quantitative approach following the survey research strategy was deployed. Data collected through questionnaires were analysed using descriptive statistical tools, including Mean Rating (MR), Relative Important Index (RII) and Standard Deviation (SD).

The findings revealed that VRF systems are popularly used in Sri Lankan apartment buildings. Furthermore, energy efficiency and comfort were recognised as the most significant top-ranked benefits, while ventilation issues and initial cost were recognised as significant challenges. Moreover, the allocation of trained technicians and provision of proper ventilation through a Dedicated Outdoor Air System (DOAS) were highlighted as applicable mitigation strategies for the identified challenges in VRFs.

The study recommends VRF systems as a suitable technology to ensure energy efficiency, reduce GHG emissions and achieve climate performance within the built environment. The opportunities for adopting VRF systems for developing countries could be explored based on the research findings. The identified challenges would assist the design engineers and facilities professionals to devise suitable strategies to mitigate issues of VRF systems in developing countries.

This research provides empirical proof of the energy efficiency and comfort aspects of VRFs. The study has explored and recommended VRF technology as a beneficial application to overcome the persistent energy crisis in developing countries.

This paper, using energy softwares, designed of Iran and optimized a residential villa in Saman city located in Chaharmahal and Bakhtiari Province.

Having used the ideas of Climate Consultant software, the basic designing was conducted by Design Builder Software, and the cooling and heating loads and lighting tools and equipment were calculated. Then, the amount of consuming of heating, cooling and lighting load of the building was optimized through insulation of walls and ceiling, using green roof, double glazing UPVC windows, light intensity sensor and variable refrigerant flow (VRF) system.

Simulation results for the stated scenarios showed an annual reduction in energy consumption of 21.1, 7.9, 26.41, 27.3 and 72.3 per cent, respectively. Also, by combining all the five scenarios, an optimal state was achieved which, from the results, brought about an annual reduction of 86.9 per cent in the energy consumption.

The authors hope that the results of the current paper could be helpful for designers and engineers in reduction of energy consumption for designing a building in similar climatic conditions.

This chapter will introduce three novel technologies demonstrated in Sino-Italian Green Energy Lab of Shanghai Jiao Tong University for the hot summer and cold winter climate zone.

Experimental and modeling works have been conducted on the application of these systems. A comprehensive review on the features of these novel technologies, their adaptability to local climate condition have been carried out, and some initial study results have been reported.

Solar PV direct-driven air conditioner with grid connection, home used small temperature difference heat pump, smart house energy information and control system are appropriate energy technologies with reduced CO₂ emission, which can be applied efficiently in the hot summer and cold winter climate zone. More useful data will be obtained in the future demonstration tests in Sino-Italian Green Energy Lab.

This work shows combining renewable energy technologies and information technologies is crucial to improve the energy efficiency and the comfortableness for indoor environment.

The purpose of this paper is to standardised four-step flexibility assessment methodology for evaluating the available electrical load reduction or increase a building can provide in response to a signal from an aggregator or grid operator.

The four steps in the methodology consist of Step 1: systems, loads, storage and generation identification; Step 2: flexibility characterisation; Step 3: scenario modelling; and Step 4: key performance indicator (KPI) label.

A detailed case study for one building, validated through on-site experiments, verified the feasibility and accuracy of the approach.

The results were benchmarked against available demonstration studies but could benefit from the future development of standardised benchmarks.

The ease of implementation enables building operators to quickly and cost effectively evaluate the flexibility of their building. By clearly defining the flexibility range, the KPI label enables contract negotiation between stakeholders for demand side services. It may also be applicable as a smart readiness indicator.

The novel KPI label has the capability to operationalise the concept of building flexibility to a wider spectrum of society, enabling smart grid demand response roll-out to residential and small commercial customers.

This paper fulfils an identified need for an early stage flexibility assessment which explicitly includes source selection that can be implemented in an offline manner without the need for extensive real-time data acquisition, ICT platforms or additional metre and sensor installations.

In many countries, innovation in building design for improving energy performance, reducing CO2 emissions and minimizing life cycle cost has received much attention for sustainable development. This paper investigates the importance of optimization tools for enhancing the design performance in the early stages of Vietnam's cooling-dominated buildings in hot and humid climates using an integrated building design approach.

The methodology of this study exploits the non-dominated sorting genetic algorithm (NSGA-II) optimization algorithm coupled with building simulation to research a trade-off between the optimization of investment cost and energy consumption. Our approach focuses on the whole optimization problem of thermal envelope, glazing and energy systems from preliminary design phases. The methodology is then tested for a case study of a non-residential building located in Hanoi.

The results show a considerable improvement in design performance by our method compared to current building design. The optimal solutions present the trade-off between energy consumption and capital cost in the form of a Pareto front. This helps architects, engineers and investors make important decisions in the early design stages with a large view of impacts of all factors on energy performance and cost.

This is one of the original research to study integrated building design applying the simulation-based genetic optimization algorithm for cooling-dominated buildings in Vietnam. The case study in this article is for a non-residential building in the north of Vietnam but the methodology can also be applied to residential buildings and other regions.

Occupants are one of the most impacting factors in the overall energy performance of buildings, according to literature. Occupants’ behaviours and actions may impact the overall use of energy in more than 50%. In order to quantify the impact that occupant behaviour has in the use of energy, this study simulated interactions between occupants and the systems present in two actual buildings. The main aim was to compare the deviations due to occupant behaviour with the actual conditions and energy use of the two buildings.

The buildings used as a case study in this research were green buildings, rated according to the Australian Green Star certification system as a 6-star and a non-rated building. The two buildings are university buildings with similar characteristics, from Western Sydney University, in Sydney, Australia. A comparison was performed by means of building simulations among the use of energy in both buildings, aiming to understand if the green rating had any impact on the energy related to occupant behaviour. Therefore, to represent the actual buildings' conditions, the actual data related with climate, geometry, systems, internal loads, etc. were used as input variables in the simulation models of the green and the non-rated buildings. Both models were calibrated and validated, having as target the actual monitored use of electricity.

Occupants were categorized according to their levels of energy use as follows: saving, real and intensive energy users. Building simulations were performed to each building, with varying parameters related with lighting, plug loads, windows/doors opening, shading and air conditioning set points. Results show that occupant behaviour may impact the buildings' energy performance in a range of 72% between the two extremes. There is no significant relationship between the green rating and the way occupants behave in terms of the energy use.

This study intends to show the impact of different categories of occupant behaviour in the overall energy performance of two university buildings, a non-rated and a green-rated building, having as reference an actual representation of the buildings. Additionally, the study aims to understand the main differences between a green-rated and a non-rated building when accounting with the previous categories.

This study aims to explore the concept of green building by determining a suitable system for categorising green building features (GBFs) that are considered significant in enhancing the value of a building in a developing economy with particular reference to South Africa. The motivation for categorising the features is based on the perception that the upsurge in adopting green building and sustainability has ushered in a new and formidable set of challenges to practising professionals in terms of recognising the most significant value-adding GBFs.

A quantitative approach was adopted, involving randomly selected construction professionals within the Western Cape Province of South Africa. The data were analysed using descriptive and inferential statistical analysis tools.

Based on the mean ranking analysis, the top three most important features, amongst others, were kitchen and water-closet (WC) water efficient fittings, megawatt photovoltaic solar plant and water metering for monitoring and leak detection. Additionally, an exploratory factor analysis revealed that the underlying grouped features were “recycled materials and high-performance building energy design”, “water-saving and solar technologies”, “biometric system and acoustical feature”, “sensor control and natural daylight design”, “daylight harnessing feature”, “high-performance hydrologic strategy and noise control feature” and “special utility feature and water efficiency technologies”.

This study was conducted and limited only to the Western Cape Province of South Africa. However, the findings have practical significance to the generality of green building projects and may serve as a useful guide for other developing countries.

This study broadens the viewpoint of construction professionals to recognise and prioritise the most important GBFs in South Africa that increase the value of a building. To create a system for assessing the sustainability of a building, the seven components and the features associated with them may be useful.

Visual inspection and human judgement form the cornerstone of daily operations and maintenance (O&M) services activities carried out by facility managers nowadays. Recent advances in technologies such as building information modelling (BIM), distributed sensor networks, augmented reality (AR) technologies and digital twins present an immense opportunity to radically improve the way daily O&M is conducted. This paper aims to describe the development of an AR-supported automated environmental anomaly detection and fault isolation method to assist facility managers in addressing problems that affect building occupants’ thermal comfort.

The developed system focusses on the detection of environmental anomalies related to the thermal comfort of occupants within a building. The performance of three anomaly detection algorithms in terms of their ability to detect indoor temperature anomalies is compared. Based on the fault tree analysis (FTA), a decision-making tree is developed to assist facility management (FM) professionals in identifying corresponding failed assets according to the detected anomalous symptoms. The AR system facilitates easy maintenance by highlighting the failed assets hidden behind walls/ceilings on site to the maintenance personnel. The system can thus provide enhanced support to facility managers in their daily O&M activities such as inspection, recording, communication and verification.

Taking the indoor temperature inspection as an example, the case study demonstrates that the O&M management process can be improved using the proposed AR-enhanced inspection system. Comparative analysis of different anomaly detection algorithms reveals that the binary segmentation-based change point detection is effective and efficient in identifying temperature anomalies. The decision-making tree supported by FTA helps formalise the linkage between temperature issues and the corresponding failed assets. Finally, the AR-based model enhanced the maintenance process by visualising and highlighting the hidden failed assets to the maintenance personnel on site.

The originality lies in bringing together the advances in augmented reality, digital twins and data-driven decision-making to support the daily O&M management activities. In particular, the paper presents a novel binary segmentation-based change point detection for identifying temperature anomalous symptoms, a decision-making tree for matching the symptoms to the failed assets, and an AR system for visualising those assets with related information.

The amount of energy consumption of buildings has obtained international concern so the concept of zero energy building becomes a target for building designers. There are various definitions and evaluation methods for efficient buildings. However, detailed research about the critical parameters that have a major effect through the operational time to reduce the energy consumption is not emphasized as this paper represents. The main aim of this study is to identify the effect of applicable interventions on energy consumption parameters with their sensitivity to each other to reach zero energy building. Relatedly, the cost of energy reduction is also determined.

Energy consumption parameters were defined as area lightings, space heating, space cooling, ventilation fans, pumps, auxiliary equipment and related miscellaneous equipment. The effect of each applied intervention on energy consumption was classified as high, medium, low, very low, no effect and negative effect by utilizing a sensitivity analysis. The base case's energy model is created by utilizing energy performance software such as e-Quest. Accordingly, energy performance improvement scenarios are developed by applying interventions such as lamp replacements, sensors, heat pumps and photovoltaic panels’ integration. Furthermore, sensitivity analyses of each intervention were developed for consumed energy and its cost.

Results indicated the electric consumption is more effective than gas consumption on primary energy and energy cost. Solar systems decline primary energy by 78.53%, lighting systems by 13.47% and heat pump by 5.48% in this building; therefore, integrating mentioned strategies could rise the improvement rate to 100%, in other words, zero amount of energy is using from the grid that means saving $ 5,750.39 in one year.

The study can be applied to similar buildings. It is worthwhile to investigate suggested methods in diverse buildings with different functions and climates in future works.

This study aims to investigate of energy consumption of an educational building in the Mediterranean climate to convert an existing building into a zero energy building by saving energy and renewable sources. Subsequent purposes are analyzing the effect of each strategy on energy consumption and cost.

The novelty of this study is filling gaps in sensitivity analysis of energy consumption parameters by not only identifying their effect on overall energy consumption but also identifying their effect on each other. Some interventions may have a positive effect on overall consumption while having a negative effect on each other. Identifying this critical effect in detail not only further improves the energy performance, but also may affect the decision-making of the interventions.