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• Renewable energy assessment methods used in 12 GBRSs are analysed and compared. • Methods used in green neighbourhood rating system are also introduced. • Evaluation way, renewable energy types, building characteristics, etc. are analyzed. • The effects by using different methods in one building are analysed. • Suggestions are provided to improve the renewable energy assessment. Green buildings and neighborhoods can help mitigate impacts of buildings on the environment, society and economy. Many rating systems or tools have been developed worldwide to assess and certificate green buildings or green neighborhoods. Renewable energy plays an important role in achieving green buildings/neighborhoods or zero energy buildings/neighborhoods by reducing fuel consumption and pollution emissions. However, substantial differences exist in assessing or quantifying the renewable energy in green building/neighborhood rating systems. This paper therefore provides a comprehensive review on renewable energy assessment methods adopted in green building/neighborhood rating systems, which would be very helpful to understand and then improve the rating systems. These methods are analyzed and discussed regarding to the calculation way, involved renewable energy types, building characteristics and energy conversion. Then a case study is conducted to quantitatively illustrate the difference of typical renewable energy assessment. Suggestions are summarized to improve the assessment methods. This paper will help investors, users and policy makers understand the rating systems more thoroughly and promote the development of green buildings and green neighborhoods. [ABSTRACT FROM AUTHOR]

Access to modern energy services in households is central to achieving decent living standards and well-being. Almost 3 billion people in Sub-Saharan Africa and developing Asia still lack access to modern energy services and endure energy consumption rates equivalent to a fraction of that in developed countries. While critical for the successful achievement of several internationally agreed Sustainable Development Goals (SDGs), closing this energy divide may pose an additional pressure on the already daunting challenge of securing climate stabilization. The ways in which this divide is closed will significantly affect the development of buildings-related emissions. This paper revisits previous work on the potential conflict between efforts towards closing the energy divide and enabling the achievement of higher levels of human well-being, and those associated with climate stabilization. It estimates the additional energy needed to achieve the former in terms of final energy consumption levels in key regions, and the associated emission pathways under different climate action scenarios. It then analyses the impact that such pathways could have on estimated carbon budgets associated with fulfilling the Paris Agreement, and provides some suggestions on how this impact could be minimized in the buildings sector. [ABSTRACT FROM AUTHOR]

Abstract: The construction industry requires significant materials and energy, and has some of the most pressing needs for energy-saving initiatives to support sustainable development. This paper studies energy efficiency during the construction of structural systems for multi-residential apartment buildings using composite structural systems. For this purpose, nine linear-shaped apartment buildings originally designed as bearing wall systems were designed as flat slabs and hybrid composite frames to study the energy consumptions of such buildings during the construction phase. The energy consumptions were then compared in terms of structural system, number of floors, and area. The energy-efficient hybrid frame used structural steel, cast-in-place concrete, and precast concrete. The structural system proposed in this paper is intended to reduce energy consumption through the proper combination of structural steel, cast-in-place concrete, and precast concrete. It was found that a multi-residential apartment building constructed with an energy-efficient hybrid composite frame could save approximately 20% of the construction phase energy used in the conventional bearing wall system. This energy savings was made possible by the reduced use of form-work resulting from the utilization of precast members, and the reduced consumptions of steel and concrete resulting from the enhanced structural performance of the hybrid composite system. The energy-efficient hybrid structural system is expected to be an alternative for future multi-residential apartment buildings. [Copyright &y& Elsevier]

Abstract: This paper presents a multicriteria decision-making model for lifespan energy efficiency assessment of intelligent buildings (IBs). The decision-making model called IBAssessor is developed using an analytic network process (ANP) method and a set of lifespan performance indicators for IBs selected by a new quantitative approach called energy–time consumption index (ETI). In order to improve the quality of decision-making, the authors of this paper make use of previous research achievements including a lifespan sustainable business model, the Asian IB Index, and a number of relevant publications. Practitioners can use the IBAssessor ANP model at different stages of an IB lifespan for either engineering or business oriented assessments. Finally, this paper presents an experimental case study to demonstrate how to use IBAssessor ANP model to solve real-world design tasks. [Copyright &y& Elsevier]

To reduce energy consumption in buildings, researchers have in the recent decade explored the potential of changing occupants’ energy consumption behaviors using eco-feedback technologies. Energy consumption behavior is a type of consumer behavior, which has been proven culture-specific in prior research. This paper aims to assess the impact of culture on the effectiveness of eco-feedback technologies in reshaping building occupants’ energy consumption behaviors, and to examine the mechanism of such impact. A total of 39 students from 10 different countries who shared four university dormitories were recruited in an experiment. A web-based eco-feedback system was developed in this study, and implemented in these dormitories. The eco-feedback system was responsible for sending weekly email reminders to students participating in the study and, upon their login, providing them with their detailed energy consumption data as well as those of their peers on a daily basis. Subsequent changes in the students’ energy consumption behaviors were analyzed, and correlated with their cultural background, which was assessed using a survey instrument designed based on Hofstede's cultural dimensions model. The experiment results showed that the mean and variance of changes in energy consumption, in response to the provision of eco-feedback information, differed significantly between participants from different countries. The results also showed that all cultural dimensions were statistically correlated to the effectiveness of the eco-feedback system, which explained how different aspects of culture could influence the energy consumption behaviors of building occupants. The results suggested that eco-feedback technologies should be tailored to specific cultural context to improve their effectiveness in building energy conservation. [ABSTRACT FROM AUTHOR]

• An innovative methodology to model a logistic centre with TRNSYS® is proposed and validated with real data over a whole year. • Building modelling using a 3D model reduces differences from real data to 7% from 26% for a non-D model. • Quantification of the thermal charges (isolation, infiltration, heat released from goods stored, workers, machinery, etc.) in this complex scenario is given. • Infiltrations during loading/unloading processes are one of the more influential charges for refrigeration in this logistic centre. • Loading/unloading procedures are key factors for saving refrigeration energy. In this paper, the authors aim to support users when modelling scenarios with complex processes entailing thermal loads and infiltrations. The large building analysed is a logistics centre for the replenishment and distribution of perishable foodstuffs where cold chains must be maintained. The logistics centre, with 96 loading/unloading docks, handles large turnovers of different goods. This produces heat inside the facility. Due to continuous loading/unloading, the infiltrations in the building, and the fixed and variable thermal loads, this facility consumes a large amount of energy. Aiming to optimise the centre and contribute to sustainable development goal SDG7, this building has been modelled with a classical non-D envelope using TRNBuild® and also with the more sophisticated 3D software, SketchUp®, to compare and validate their results over a year with real consumption, as well as to assess the main sources of energy consumption. To obtain reliable results, the authors provide some methodology models to identify the sources of the building's thermal losses and quantify the different sources of consumption. These models are useful tools to support decision-makers (to improve insulation and arrange loads, among other things) when trying to reduce energy use in large buildings with intense operating processes. The results indicate that by modelling the entire facility with 3D software, the model estimation differs from real consumption by around 7.22%, while using a non-D model increases the difference to 26%. Additionally, the results show that around 47% of the energy consumption in the building is due to air infiltrations during loading/unloading, 18% is due to perishable products, and around 30% is due to building insulation. The methodology and models presented here, including the possibility of modifying the thermal load profiles, have demonstrated their capacity to reduce and optimise the load demand of refrigeration for warehouses if reliable data records are available. [ABSTRACT FROM AUTHOR]

[Display omitted] • The influencing factors on energy efficiency of data center are reviewed. • Energy efficiency metrics are classified according to different priorities. • Appropriate metrics should be selected according to data center function for optimization. • Metrics are analyzed by hierarchy according to the degree of sustainable development. • Challenges and gaps are highlighted and suggestions are given for future works. The rapid development of the Internet requires data center infrastructures to be extended to a large scale with a higher power capacity and a reduction in energy consumption and carbon emissions. It is of great significance for this application to reduce energy consumption, capital cost and carbon emissions while ensuring a safe and reliable data center operation. Evaluation metrics have been considered an effective method to assess the energy efficiency of data centers and have been widely used in various data centers for many years. This work reviews the latest progress of data center evaluation metrics development in recent 20 years. Energy efficiency metrics are summarized based on energy conservation, eco-design and data center security, with the advantages and disadvantages and their correlations discussed. The applicability of each metric is analyzed. The influencing factors of energy efficiency of data centers discussed include site selection, IT equipment, power supply and distribution systems, cooling systems, building structure, and temperature control. The results show that the current evaluation metrics are valuable for the assessment of energy saving of data centers. However, more comprehensive and multi-scale evaluation metrics combining energy consumption, eco-design and data center security are needed to accelerate the progress towards carbon neutrality. In this paper, the hierarchy analysis of metrics is carried out according to sustainability, and metrics in line with sustainable development should be used preferentially. [ABSTRACT FROM AUTHOR]

Residential and commercial buildings account for more than 74% of total annual electricity consumption in the United States. Studies have shown that occupants’ awareness of their behaviors in consuming electricity encourages them to change their unsustainable behaviors and improves the sustainable ones. As behaviors impact the ways that daily activities are performed, in order to develop a personalized appliance level model of an occupant's behavior, precise activity recognition is required. In this paper, we introduce a novel framework to allocate personalized appliance-level disaggregated electricity consumption to daily activities. In our framework, using ontology-based approach, the input appliance usage data is first separated into categories of non-overlapping activity events. The separated data sets are then segmented to detect activity segments, which are next mapped into activity classes using a trained classification model. To evaluate the performance of our presented framework, an experimental validation was carried out in three test bed apartment units. Results of validation showed a total F -measure value of 0.97 for segmentation and an average accuracy of 93.41% for activity recognition. Following the activity recognition, the approximate electricity consumption associated with the recognized activities was estimated and the results of each test bed unit were compared with the others. [ABSTRACT FROM AUTHOR]

The principal aim of our study is to investigate the contribution and/or the influence of Foreign Trade (FT), Foreign Direct Investment (FDI), and Financial Development (FD) on the Energy Consumption (EC)-Environmental Pollution (EP)-Economic Growth (EG) link for the Gulf Cooperation Council (GCC) over the period 1971–2019. To realize the study aim, we develop an augmented growth model to examine the long-run relationship between the mentioned variables by applying the Autoregressive Distributed Lag (ARDL) procedure and the Vector Error Correction Model (VECM) to capture direction causality. The empirical results suggest that the variables concerned are cointegrated. Further, the coefficients estimated are mixed across countries. In the long-run, EC, FT (except Kuwait), and FDI (except Oman and KSA) are related to a rise in EG for all countries. Besides, the findings support that EC generates EG in the short-run for all GCC countries, implying economic expansion. Moreover, the major conclusion of this research paper has an impressive value for the policymakers to advance comprehensive trade, investment, financial, and energy policies that enable to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Abstract: Energy efficiency in new building construction has become a key target to lower nation-wide energy use. The goals of this paper are to estimate life-cycle energy savings, carbon emission reduction, and cost-effectiveness of energy efficiency measures in new commercial buildings using an integrated design approach, and estimate the implications from a cost on energy-based carbon emissions. A total of 576 energy simulations are run for 12 prototypical buildings in 16 cities, with 3 building designs for each building-location combination. Simulated energy consumption and building cost databases are used to determine the life-cycle cost-effectiveness and carbon emissions of each design. The results show conventional energy efficiency technologies can be used to decrease energy use in new commercial buildings by 20–30% on average and up to over 40% for some building types and locations. These reductions can often be done at negative life-cycle costs because the improved efficiencies allow the installation of smaller, cheaper HVAC equipment. These improvements not only save money and energy, but reduce a building’s carbon footprint by 16% on average. A cost on carbon emissions from energy use increases the return on energy efficiency investments because energy is more expensive, making some cost-ineffective projects economically feasible. [Copyright &y& Elsevier]

In the current economic situation in Ukraine, the operation of heat supply systems occurs at a reduced temperature of circuit water. The increased temperature graph of 95/70 °C due to the high cost of fuel is impractical. The experience of such countries as Denmark, Germany, Finland, Sweden and Holland with developed centralized heat supply indicates the need for the first-class equipment of an individual heating point (IHP) of a building with an automatic control system, and then the transition to technology with a reduced temperature graph is carried out. Therefore, the modernization of heat supply systems in Ukraine aimed at the use of a reduced temperature graph will require a transition to closed independent heating systems, to qualitative and quantitative regulation and to automation of consumer IHP systems. A lot of district heating systems in Poland also require modernization to meet the requirements of the European Directive EED 2018/2002. This paper presents the results of numerical study of the influence of design and operating parameters of the heat supply network on the choice of the optimal temperature and flow- rate of circuit water of a distric heating system (DHS). [ABSTRACT FROM AUTHOR]

[Display omitted] This paper evaluates the cost benefits of combining energy efficiency practices and hybrid photovoltaic-biomass distributed generation systems to design standalone rural housing in Morocco. This integrated analysis approach seeks an enhancement of the economic and environmental sustainability of rural housing units in the Fez region. It utilizes optimization selection procedures to identify both, the energy efficient and renewable energy technologies readily available in the region to reduce the cost and energy use of the housing units. The results of the integrated design indicate that an optimally designed house can reduce life cycle costs by 25% and carbon emissions by 47.13% compared to the current practices. Applying the optimized design to 30-residential houses can result in a decrease of the cost of energy (COE) for the proposed system from 0.155 US$/kW h to 0.125 US$/kW h. However, a sensitivity analysis confirmed that the availability of biomass resource influences greatly the economic viability of the proposed hybrid system. Increasing the daily collected biomass resources from 2.5 to 8.5 tons/day causes a drop in the COE by 46.6%. [ABSTRACT FROM AUTHOR]

While the economic is rapidly developing, human beings are facing a serious ecological problems, sustainable-development has got attention from more and more countries and has been treated as an economic and social development strategy. The development and utilization of renewable energy can realize the transformation of regional economic development mode and promote the long-term sustainable development of regional economy. One of the latest concepts that has attracted a lot of attention in the power systems is the energy hub (EH). In this paper, a combined energy system (CES) known as the EH consisting of electrical, cooling and heating equipment along with the demand response programs (DRPs) as well as renewable energy resources (RERs) optimization study have been proposed. Moreover, the uncertainty modeling and electrical scenario creation of cooling, heating, wind speed, solar irradiation and the energy carriers prices including electricity and natural gas is presented. The objective of the optimization problem is maximizing the profit of the EH with the existence of DRPs and RERs under four scenarios which is solved by enhanced grey wolf optimization (GWO) algorithm. In order to avoid such deficiencies and to realize a stabilized relationship between exploration and exploitation, a new modified grey wolf optimization (MGWO) algorithm is proposed. The implementation results show high accuracy and power levels of this method to solve the aforementioned problem under different uncertain parameters and various scenarios. The simulation results of proposed EH profit maximization model shows a reduction in purchased electricity from the main grid and a reduction of the overall operation costs. [ABSTRACT FROM AUTHOR]