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Highlights • A pre and post renovation energy use analysis of almost 90,000 renovated dwellings. • The (p)rebound effects explain only partly disappointing energy renovation results. • Effectiveness of renovations are dependent on state of building prior to renovation. • Effectiveness of renovations are dependent on type of occupant. • Deep renovations often save less energy than expected but are the most effective. Abstract Energy renovations often result in lower energy savings than expected. Therefore, in this study we investigate nearly 90,000 renovated dwellings in the Netherlands with pre and post renovation data of actual and calculated energy consumption. One of the main additions of this paper, compared to previous studies on thermal renovation, is that it only takes dwellings into account with the same occupants before and after renovation, using a large longitudinal dataset. Overall this paper shows new insights towards the influence of the energy efficiency state of a building prior to energy renovation, the type of building, the number of occupants, the income level of the occupants and the occupancy time on the actual energy savings, the energy saving gap and on the probability of lower energy savings than expected. We also investigate if the influence is different per type of thermal renovation measure. Some of the findings are: it is impossible to conclude which single thermal renovation measure is the most effective because this is dependent on the energy efficiency of the building prior to the energy renovation, type of building, income level and occupancy; occupants with a high income save more energy than occupants with low income; dwellings with employed occupants benefit more from improved building installations than dwellings occupied by unemployed occupants; The prebound and rebound effects are only part of the explanations for lower than expected energy savings; Deep renovations result more often in lower than expected energy savings than single renovation measures but nevertheless they result in the highest average energy saving compared to other thermal renovation measures. The results could be used for more realistic expectations of the energy reduction achieved by thermal renovations, which is important for (amongst others) policy makers, clients and contractors who make use of energy performance contracting, home owners, landlords and (social) housing associations and as a starting point to improve the energy calculation method. [ABSTRACT FROM AUTHOR]

[Display omitted] • Present a comprehensive review of building electricity profile models. • Distinguish the differences of building electricity profile and prediction models. • Categorize the statistical and bottom-up models for electricity use profiles. • Investigate the validation metrics in accordance with the modeling methods. • Discuss the key future perspectives of building electricity profile analysis. The building sector contributes significantly to overall energy consumption and carbon emissions. Improving renewable energy utilization in buildings is of considerable importance for their carbon neutrality. Electricity is expected to become the major form of final energy consumption in buildings; as such, understanding the features of building electricity use profiles is pivotal for building energy system design and city-scale electricity distribution network planning. This study reviews the current status and future challenges of building electricity use profile models. The paper distinguishes between electricity use profile models and electricity use prediction models. Then it comprehensively reviews current research papers, focusing on four aspects, including the temporal and spatial distribution of datasets, the distinction between statistical and bottom-up modeling methods, mathematical and engineering domain validation metrics, and applications in building energy system design and energy policy making. Key perspectives for future research are discussed in the paper, including the temporal scales of models, the aggregation of electricity use profiles, occupant-driven environment-interactive model structures, as well as the fit-for-purpose model evaluation. This is intended to inform and inspire future research on building electricity use profiles, improve the in-depth understanding and quantitative descriptions of building electricity use, and support the design of future building systems and energy distribution networks. [ABSTRACT FROM AUTHOR]

Facing the challage of energy conservation and emission reduction in the building sector, most energy saving strategies of central heating only focus on the performance improvement of building envelope, ignoring the impact of energy use behavior. This paper proposed a building energy conservation strategy based on energy use behavior analysis, which provides a perspective for in-depth exploration of building energy conservation. After investigating a typical university in the northern China, the energy use behaviors were characterized and two different DeST energy consumption models before or after considering energy use behavior were established. By comparing the results calculated by these two models, the impact of energy use behavior analysis on building energy consumption was quantitatively analyzed. The results show that the heating energy consumption and carbon emission can be reduced by 23.28% and 23% respectively through the proposed strategy based on energy use behavior. Therefore, the analysis of energy use behavior can provide a theoretical basis for heating operators to make decisions on energy supply regulation. With central cooling and heating further popularizing in the future, the research methodology of this paper has more extensive reference value for energy conservation and emission reduction strategies in the building sector. [ABSTRACT FROM AUTHOR]

• Operating time of SMEs is estimated using a SOM and hourly demand data. • The estimated operating time is used for hourly AC demand disaggregation. • The average errors of yearly AC demand estimation are better than 10%. • Hourly disaggregation highlights season and time period of AC demand peaks. Despite the growing penetration of smart meters and energy management systems in recent years, few tools have been proposed for energy demand data analysis and visualization to promote energy conservation in small- and medium-sized enterprises (SMEs). In this paper, we propose a new method consisting of operating time estimation and simplified disaggregation based only on the SME's hourly electricity demand data and actual outdoor temperature data. The method first estimates the operating time using a self-organizing map, which categorizes the hourly data as operating, half-operating, or non-operating time and eliminates manual parameter adjustment that requires user trial and error. Then, using the estimated operating time, our simplified disaggregation method estimates hourly air conditioning (AC) demand considering the variation in each office's temperature at which air conditioners are switched on. The method was evaluated using a public business energy management system dataset from Japan, and the average errors of yearly AC demand estimation were better than 10%. The outputs of the proposed method may provide information that is more relevant, reliable, and specific to each customer and efficiently promote energy conservation measures in SMEs. [ABSTRACT FROM AUTHOR]

Abstract Energy Management and Information Systems are a family of analytics technologies that include energy information systems, fault detection and diagnostics (FDD), and automated system optimization tools. Such systems have the potential to enable buildings to meet energy management goals of reducing total energy consumption and cost. Most current market offerings use data-driven and rule-based analytics. However, the use of physics-based models in the analytics offers potential improvements by providing an accurate estimation of outputs based on representation of the physical principles governing the building system behaviors. This also permits the use of design stage models to inform commissioning and operation. This paper describes the development and testing of a hybrid data-driven and physics model-based operational tool for energy efficiency in central cooling plants. The tool offers FDD functionality, setpoint optimization, and visualization of key performance parameters. It was demonstrated at a university campus in the mixed-humid ASHRAE Climate Zone 4A. Key performance metrics that were analyzed include plant electricity use reduction, plant model calibration, and system economics. Annual simulations indicate the tool can provide electricity savings of greater than 10% for approximately six months of the year, mainly during the winter season when wet bulb temperatures are low, though only 1.38% savings for the entire year. Additionally, over a 4-day period in April, recommended optimal setpoints were implemented, resulting in 17% savings versus metered baseline consumption. With respect to model calibration, the difference between model-predicted and measured parameters was less than 10% for 90% of data points acquired for three of six chillers, and for each ten cooling towers. Finally, the tool users reported that satisfaction with the capabilities was equal to or better than that with the preexisting BAS system. [ABSTRACT FROM AUTHOR]

Highlights • Providing a critical review of office building energy management based on occupancy monitoring and modeling, and HVAC and lighting control strategies. • Proposing a roadmap towards cognitive building management. Abstract Buildings are responsible for a large portion of global energy consumption. Therefore, a detailed investigation towards a more effective energy performance of buildings is needed. Building energy performance is mature in terms of parameters related to the buildings' physical characteristics, and their attributes are easily collectable. However, the poor ability of emulating reality pertinent to time-dependent parameters, such as occupancy parameters, may result in large discrepancies between estimated and actual energy consumption. Although efforts are being made to minimize energy waste in buildings by applying different control strategies based on occupancy information, new practices should be examined to achieve fully smart buildings by providing more realistic occupancy models to reflect their energy usage. This paper provides a comprehensive review of the methods for collection and application of occupancy-related parameters affecting total building energy consumption. Different occupancy-based control strategies are investigated with emphasis on heating, ventilation, and air conditioning (HVAC) and lighting systems. The advantages and limitations of existing methods are outlined to identify the gaps for future research. [ABSTRACT FROM AUTHOR]

Highlights • Non-intrusive techniques are proposed to infer occupancy from existing HVAC sensors. • Reheat energy use is reduced by more than 38% with better nighttime setback schedules. • Derived a comprehensive set of candidate anomalous zones using unsupervised learning. • Proposed approach can be readily applied to any commercial building with a BMS. Abstract The Heating Ventilation and Air Conditioning (HVAC) system of commercial buildings traditionally runs on a fixed schedule that does not take occupancy into account despite its huge variation over space and time, thereby wasting a lot of energy in conditioning empty or partially-occupied spaces. Occupancy information is essential to eliminate wasteful energy use with imperceptible impact on building operations and human comfort. This paper investigates the application of non-intrusive techniques to obtain a rough estimate of occupancy from coarse-grained measurements of sensors that are commonly available through the building management system. Various static and adaptive energy-efficient schedules are developed based on this approximate knowledge of occupancy at the level of individual zones. Our experiments in three large commercial buildings confirm that the proposed techniques can uncover the recurring occupancy pattern of the zones, and schedules that incorporate these occupancy patterns can achieve more than 38% reduction in reheat energy consumption while maintaining indoor thermal comfort. [ABSTRACT FROM AUTHOR]

Housing Stock Energy Models (HSEMs) play a determinant role in the study of strategies to decarbonise the UK housing stock. Over the past three decades, a range of national HSEMs have been developed and deployed to estimate the energy demand of the 27 million dwellings that comprise the UK housing stock. However, despite ongoing improvements in the fidelity of both modelling strategies and calibration data, their longevity, usability and reliability have been compromised by a lack of modularity and openness in the underlying algorithms and calibration data sets. To address these shortfalls, a new open and modular platform for the dynamic simulation of national (in the first instance, the UK) housing stocks has been developed—the Energy Hub (EnHub) . This paper describes EnHub’s architecture, its underlying rationale, the datasets it employs, its current scope, examples of its application, and plans for its further development. In this we pay particular attention to the systematic identification of housing archetypes and their corresponding attributes to represent the stock. The scenarios we analyse in our initial applications of EnHub, based on these archetypes, focus on improvements to housing fabric, the efficiency of lights and appliances and of the related behavioural practices of their users. In this we consider a perfect uptake scenario and a conditional (partial) uptake scenario. Results from the disaggregation of energy use throughout the stock for the baseline case and for our scenarios indicate that improvements to solid wall and loft thermal performance are particularly effective, as are reductions in infiltration. Improvements in lights and appliances and reductions in the intensity of their use are largely counteracted by increases in heating demand. Housing archetypes that offer the greatest potential savings are apartments and detached dwellings, owing to their relatively high surface area to volume ratio; in particular for pre-1919 and inter-war epochs. [ABSTRACT FROM AUTHOR]

Global trends in reapplication of wood re-application and wood-based products, used as construction and architectural coating materials, are present not only because of esthetic, artistic and design requirements or tradition and nature-based inspiration, but also because wood adapts to modern trends in sustainable development. This paper presents traditional influence on application of wood as a façade cladding element in modern architecture of Serbia and provides the analyses of functional and design potentials of wood as an element of ventilated façade systems and its influence on energy efficiency. The objective of this research was to provide a more detailed insight into potentials and limitations of the application of wood and wood-based products, as façade cladding elements used for construction and reconstruction of architectural objects, in the climate conditions of Belgrade (Serbia) as well as to point out certain suggestions about improving their energy efficiency characteristics. The paper presents the examples of various methods of applying wood and wood-based products as elements of façade cladding in modern architecture of Belgrade. The main focus is put on an object that underwent different refurbishment methods and façade system alterations in order to meet the requirements of energy saving. [ABSTRACT FROM AUTHOR]

This paper studies how human activity affects energy consumption and how such activity can be leveraged from electricity meter data. Using 15-minute interval data and applying the methods introduced in this paper, it is possible to identify in which days there was human activity and extract daily routines from such data. This type of insight into the way people consume energy helps understanding energy use at a deeper level, and realise where significant energy savings can be made. [ABSTRACT FROM AUTHOR]

This paper summarises the results of a study to identify and quantify the potential impact of measures and policies to reduce the energy consumption of air conditioning in European countries over a 10-year period. The market penetration of air conditioning in Europe has increased steadily over several decades. On a “business as usual” basis, its energy consumption would increase by over 50% by 2020. Measures to restrict this increase are therefore important, but the savings potential straddles several overlapping areas which are subject to different constraints including those imposed by the replacement rates of systems and products, and the refurbishment rates of existing buildings. This work reported in this paper is based on the use of information from a variety of sources in a highly disaggregated model to assess the “realisable” savings over a 10-year period, taking into account relevant constraints. The paper summarises results at a European level, focussing on those cases that generate the greatest realisable savings. Savings are possible in three areas: improved equipment and system efficiency, reduced cooling loads, and more effective operation. The cases that offer the largest savings provide the basis for recommendations for policy measures, often using existing policy instruments. In addition, areas where further work is needed are identified. More detailed results and information about the study and additional recommendations can be found at http://www.bre.co.uk/searchresults.jsp?category=5&q=energy+management [1] . [ABSTRACT FROM AUTHOR]

In this paper, a mathematical model is formulated to quantify the social impact an individual has on his/her community when he/she performs any energy efficiency project and transmits that information to his/her neighbours. This model is called the expected power savings model; it combines direct and indirect expected power savings of the energy efficiency project for each individual within the network. The indirect savings are quantified through the social interactions people in the network. The example used in this paper illustrates the effectiveness of the model by identifying the households who should have free solar water heaters installed in their residential houses based on their influence through interactions in their community. Two case studies are considered in this paper, single and multiple sources case studies. In the multiple source case study, the results show that it is not necessarily the people with the highest connections who provide the maximum expected power savings. [ABSTRACT FROM AUTHOR]

This paper considers energy conservation practices in Qatar with special emphasis on commercial buildings. Energy conservation approaches are classified into five main areas and an Energy Conservation Matrix (ECM) database for buildings is developed. The ECM maps the energy conservation techniques/technologies to models versus their application domain. Three scenarios (building envelope design, change in customer behavior, and consideration of renewable energy supply) are analyzed to study different alternatives for efficiency improvement. The analysis is done in a case hotel. The analysis shows that, the energy conservation potential of using envelope redesign for the case study is about 7.5% while conservation through behavior change ranges between 2.74% and 15.80%. The conserved energy potential ranges between 10% and 24.12% of the site energy in the combinatorial scenario that integrated envelope design alternatives with customer behavior change. The renewable energy (RE) scenario conserves energy, indirectly, by using green energies generated from renewable sources. The output shows that due to changes as per the three scenarios, total CO 2 emissions of the building are also reduced. The analysis shows that adoption of 30% RE alternative can reduce emissions by about 27% with respect to the reference scenario. It is believed that the scenarios developed in this paper and the results obtained will motivate the designers to consider alternative designs or redesigns in the large scale commercial buildings. [ABSTRACT FROM AUTHOR]

The energy consumption in a multi-chiller system is very significant and its consumption will be increased by inappropriate operating of the chillers. Accordingly, the economic dispatch in multi-chiller systems becomes an important issue for saving energy. Such issue is known as optimal chiller loading, which is solved by applying different optimization methods. This study employs exchange market algorithm to obtain optimal set points of the economic dispatch problem on chiller plants, which is inspired by trading the shares on a stock market. Exchange market algorithm is proposed for solving continuous non-linear optimization problems and it is comprised of two searching and two absorbing operators. The decision variable of the optimal chiller loading is partial load ratio of each chiller and the objective function of the optimal chiller loading problem is minimizing the power consumption while satisfying the cooling demand. This paper adopts three case studies to evaluate the performance of exchange market algorithm and compares it with other optimization methods applied on the optimal chiller loading problem. Results show that exchange market algorithm is an efficient method for solving optimal chiller loading problem in chiller plants, and is adaptable for usage in air-conditioning systems. In addition, the comparison results show that the exchange market algorithm provides better solutions than previous optimization methods applied on the optimal chiller loading method in terms of convergence speed and total consumption of electrical energy. [ABSTRACT FROM AUTHOR]

Heat recovery devices can help ventilation systems conserve energy; However, they cause a pressure drop in the system, and hence the system incurs an electricity consumption. In the present paper, the maximum allowable pressure drop of the recovery units is achieved from thermodynamic and economic points of view. The novelty of the research is that, unlike the existing criterion which does not differ for different cities, the introduced criteria can be calculated for each city with individual weather, economic, power plants, and energy conditions. Although the methods presented to calculate the criteria consider a broad range of effective parameters, there is no need to use complex energy simulation methods. Moreover, for each city, four types of criteria are introduced, which allows the city authorities to choose the best ones according to their city conditions, and then calculate the chosen criteria by the data of the city. In order to gain the criteria, modified enthalpy-hours and bin method variables are introduced to calculate sensible and latent energy consumption due to ventilation. The criteria are numerically calculated for Kerman city in Iran, and the results show that the recovery type and the chosen viewpoint has a considerable effect on the allowable pressure drop. The sensitivity of the results to different variables is analyzed in the end. [ABSTRACT FROM AUTHOR]

Thermally activated building system (TABS) is a hydronic cooling system, in which cold water is circulated through pipes embedded in the building structure to remove the heat from the indoor space. This paper proposes a hybrid passive cooling system, in which TABS is integrated with a cooling tower. The performance of this integrated system greatly depends on the climatic conditions of the geographical area. Hence, the feasibility of the proposed system to provide thermal comfort in twelve Indian cities spread over five different climatic regions is investigated using COMSOL Multiphysics. Different cooling scenarios like Roof and Floor cooled TABS (RF) and All Surfaces cooled TABS (AS) are compared. The proposed system performs well in arid and semi-arid regions, and the RF scenario is sufficient to achieve thermal comfort. The system is able to reduce the indoor operative temperature by 14 °C for the arid climatic conditions of Jaipur. In the other three regions, i.e., humid subtropical, tropical wet and dry and tropical wet regions, the performance of the proposed system is relatively low and the AS scenario is required to achieve thermal comfort. [ABSTRACT FROM AUTHOR]

This paper aims to analyse the changes that the new Hellenic Regulation on the Energy Performance of Buildings (REPB) has brought to the Hellenic residential buildings, which is in line with the European Directive 2010/31/EC. These changes refer to construction techniques, construction costs and energy performance. Our assessment is based on the numerical analysis of two typical residential buildings, a single and a multi-one. Both buildings were studied according to the requirements set before and after the application of the REPB for all (four in total) climate zones of Greece. The cost for implementing the two regulations was evaluated, as was also the energy consumption cost. Based on these costs we estimated the operating costs for heating, cooling and domestic hot water of the two buildings of this study. The implementation of the REPB significantly reduced the required heating loads for space heating in all climate zones by 37%–48% for both building types; this is mainly attributed to the improvement of the thermal properties of the building envelope and the improved energy performance of the electromechanical systems. The required cooling load was low and the implementation of the REPB did not change it significantly. Significant energy savings, in the range of 51%–58% were also achieved by installing flat plate solar collectors for Domestic Hot Water heating. [ABSTRACT FROM AUTHOR]

• The data requirements of quota methods are summarized, and a city-scale database containing 670 credible government office buildings is established. • By comparing the processes, the results and applicability, the selection basis of quota methods under different conditions is refined. • A flow chart of the formulation process and method selection of city-level building energy consumption quotas is constructed. • It is proposed that special attention should be paid to the outliers, and the characteristics of outliers in Chongqing are summarized. Energy consumption quota policies are effective management measures to promote energy conservation and emission reduction in China. Cities need to choose an appropriate method to formulate local energy consumption quota standards. This paper is based on the data of 670 government office buildings in Chongqing and the selected quantile method (QM), quota-level method (QLM) and multiple linear regression (MLR) method, which are widely used in the formulation of city-level energy quotas. By comparing their interpretability, evaluation, consistency and stability, the application conditions and applicability of each method are summarized. MLR has the strongest explanatory power but the highest requirements for the technology and information dimensions. The QLM is more explanatory and stable than the QM and is more suitable for the initial stage of energy quota management. When using the QLM, we should consider scientific classifications and reasonable quota levels. Special attention should be given to "outliers" with abnormal evaluations of the quota results. The outliers in Chongqing are characterized as buildings that have been used for more than 10 years and have an area of less than 5000 m2. Finally, this paper constructed a flow chart of the formulation process and method selection to help policymakers better understand how to choose the most appropriate method and identify inefficient buildings. [ABSTRACT FROM AUTHOR]

• A new urban building energy modeling tool-AutoBPS was developed. • AutoBPS calculated urban building energy demands, analyzed energy retrofit and rooftop PV potential via EnergyPlus. • AutoBPS automatically generated multi-zone models, considering shading from surrounding buildings. • A downtown district of 3633 buildings in Changsha, China, was simulated to demonstrate the tool's features. • All three energy conservation measures and PV installation could save 38.6% of total energy demand. China has promised to peak carbon emissions by 2030 and become carbon neutral before 2060. Achieving this target requires actions from all sectors, especially the building sector, which accounts for 33 % of the total energy consumption in China. Within this scenario, this paper introduces a new urban building energy modeling tool, Automated Building Performance Simulation (AutoBPS), to calculate urban building energy demands and to analyze energy retrofit and rooftop photovoltaic (PV) potential. AutoBPS uses a building-by-building approach to automatically generate multi-zone (one zone per floor) models based on the city building dataset, considering the shading effect by surrounding buildings. The tool simulates building energy use and PV generation via EnergyPlus. A downtown district of 3633 buildings in Changsha, China, was selected as a case study to demonstrate the features of the tool. Firstly, annual baseline energy uses of 1793 GWh were simulated by inputting Geographic Information System (GIS) data. Then, different energy conservation measures (covering envelope, lighting, cooling system upgrade, etc.) and roof PV generation systems were adopted to explore energy saving potential. The results showed that the window upgrade was the most energy-efficient individual measure for residential buildings, while the lighting upgrade was that one for commercial buildings. Altogether three measures could save 2.7 ∼ 30.7 % of annual site energy use intensity per building. The total energy demand could be reduced by 18.5 % by combining all measures and saved by 38.6 % when PV installation was added. AutoBPS can be easily applied to other cities, supporting urban energy efficiency plans for carbon reduction goal implementation. [ABSTRACT FROM AUTHOR]

Lighting energy savings, as well as visual and non-visual user benefits have been widely attributed to daylighting. This paper explores daylight design strategy, visual appraisal, Daylight Factor (DF), lighting energy usage and discomfort glare using two green building offices in Malaysia, which have incorporated daylighting into both façade and interior design. Visual appraisal surveys were collected from 39 and 145 subjects in the open plan working space of the Energy Commission Building (ECB) and Public Works Department Block G (PWD), respectively. The survey focused on task brightness, colour appearance, uniformity and lighting preference. Discomfort glare assessed via occupant point-of-view luminance maps was juxtaposed here from a glare study involving the same buildings. Illuminance loggers were used to monitor artificial lighting usage as well as the DF on a selected floor of each building. There were no significant differences in occupant responses to the visual appraisal survey for both office spaces. Using MS1525:2014 and Green Building Index (GBI NRNC) tool as baselines, the DF performance of both offices differs significantly: PWD had a 45.5% daylit area, with ECB a 14.8% daylit area for DF >1%. However, lighting energy usage results show substantial savings of 53% and 41% occurred from daylighting. These findings of visual appraisal, DF, lighting energy savings and discomfort glare show a discrepancy in using only the DF to justify the daylight performance of an office space in a tropical climate such as Malaysia. The findings suggest that equivalent consideration should be given to interior design to facilitate daylighting, which is often beyond the control of designer, but in the hands of office end users. [ABSTRACT FROM AUTHOR]

Currently, intermittent-operating escalators are gaining popularity on the market. The energy consumption of such devices highly relates to the passenger traffic profile during a day. This paper models the energy consumption of intermittent-operating escalators with four different passenger profiles and analyzes the resulting differences in the daily electricity consumption. The passenger profiles and their impact on escalator energy consumption are based on multiple long-term measurements and previous research studies. The results indicate that passenger volumes and density during a day affect the overall energy consumption drastically. The main reason for the differences is the principle of intermittent-operating escalators, the “power demand cycle”, along with the Variable Speed Drive. [ABSTRACT FROM AUTHOR]

In order to achieve greater energy sustainability, the European Union has begun the reform process of the energy policy. Two main lines have been raised: electricity generation with renewable energy and energy saving. The raising cost of energy makes indoor lighting techniques as one of the most important contributors for energy saving in most of the industrialized countries. Therefore, the history of indoor lighting is not exclusively linked to the development of new light sources, having impact on energy saving and sustainability. The aim of this paper was to study and analyse the evolution and milestones of indoor lighting from incandescent bulbs to the modern light-emitting diodes (LEDs) and organic lighting emitting diodes (OLED) going through intermediate milestones like fluorescent lamps (FL) and/or techniques in lighting induction lamps. As main conclusion of this review, it has been found that indoor lighting techniques with their energy efficiency have opened new perspectives for optimizing the energy conversion and this in turn will play a major role in people's quality of life and well-being. [ABSTRACT FROM AUTHOR]

The paper presents cost-optimal energy performance improving measures conducted in deep renovations of typical Finnish (cold climate) brick apartment buildings, built in the 1960’s. The study discusses the effects of different renovation measures on the energy performance and economic viability in a selected building. Energy performance is studied from the primary energy consumption’s perspective and cost-effective renovation measures to meet higher energy performance criteria are also studied. The cost-optimal renovation concepts to meet different energy performance criteria were determined from over 2 billion potential renovation measure combinations by using sophisticated simulation-based multi-objective optimisation (SBMOO) analysis, utilising the advanced Pareto-Archive NSGA-II genetic algorithm, as the main research method. The SBMOO analysis was used to minimise the primary energy consumption and the net present value of life-cycle cost over a 25-year discount period simultaneously. The results indicate that the cost optimum renovation solutions of the brick apartment building stock provide the same energy performance criteria as the current national minimum energy performance requirements of new apartment buildings. According to the study, the investments should be focused on high performance renewable energy production systems, which deliver the best return on investment. External financial support mechanisms are also required to encourage apartment building owners to conduct deep renovations towards nearly zero-energy apartment buildings. [ABSTRACT FROM AUTHOR]

This paper develops a rapid evaluation method for chillers’ operation strategies based on history data analysis, identifying their potential to improve the chillers’ performance. The data proliferation method and the moving-maximum method are developed to obtain the approximate best performance line of the overall chillers, and the line is taken as the evaluation benchmark. Three indexes, I select , I load , and I , are defined to evaluate the selection of the active chillers, the load allocation among the active chillers, and the operation performance of the overall chillers respectively. With the index I , the percentage of potential energy saving and the least energy consumption during a period can also be calculated. The method is validated by evaluating two operation strategies of chillers. And the results of the evaluation identify the potential improvement of the strategies. Also the evaluation method has low computation cost and can be executed rapidly. [ABSTRACT FROM AUTHOR]

[Display omitted] • Various elements influence micro-climate around building and impact its energy use. • Micro-climatic impact on buildings in sub-tropical/tropical zones is rarely studied. • Passivhaus building performance in sub-tropical/tropical zones is under examined. • Passivhaus buildings are sensitive to surrounding micro-climates in temperate zones. • Digitised Eco-feedback is effective in increasing energy consumption awareness. The earth's climate differs enormously across its breadth with numerous small-scale variations to surrounding atmospheric conditions (micro-climates) existing side by side. These differences impact indoor environments of residential buildings and, depending on occupants' preferences, building energy use, and can mean that home designs are unfit for the local context. Although considered leaders in producing energy efficient designs which are equally comfortable for occupants and the environment, even Passivhaus (PH) homes have been demonstrated to be sensitive to localised outdoor conditions. Meanwhile, occupants have little understanding of their own domestic energy use, how the situation of their property might impact their comfort, and of more sustainable alternatives open to them. To boost understanding of household energy use and to encourage energy conservation, instantaneous computerised feedback on household's energy consumption (Eco-feedback) has been widely used. Along with improving household energy use understanding, Eco-feedback technologies may assist in comprehending local micro-climatic conditions around a building, and in learning how to manipulate these can help to establish and sustain preferred indoor conditions with minimal energy use. This can be achieved through producing personalised and contextualised feedback and responses to update and renovate users' homes by suggesting short-term actions and long-term design recommendations. This systematic literature review paper explores the breadth of Eco-feedback techniques, their relative benefits and shows how these could be deployed in the context of understanding building performance in the home. [ABSTRACT FROM AUTHOR]

• POE was carried out to compare the design target and operational effect after use. • A Large Irregular Green Commercial Building was chosen for in-depth analysis. • We recommend the building energy saving and carbon emission reduction strategy. Commercial buildings, especially large irregular commercial buildings with complex space and dense occupation, have high energy consumption and carbon emissions. Moreover, the actual operating performance differs significantly from its design, in terms of energy conservation and carbon emissions. This study selected an irregular large-scale green commercial building in Dalian, a coastal city in the cold zone of China. The running energy consumption and indoor physical environment were investigated and analyzed, and a satisfaction survey was conducted using the Post-occupancy evaluation (POE) methods. The promotion strategies of holistic design were proposed by comparing the operational building performance with the design target. The research shows that the energy consumption of the building was 68.02 kWh/m2, which failed to meet the standard requirements. The carbon emission was 74.76 kgCO 2 /m2. Less than 10 % of humidity in summer fell in the expected range, and the lowest value of PM 2.5 concentration in winter was 28.3 %. The score of indoor environmental quality and service satisfaction was low. This paper identifies the problems and analyzes the differences between the operation stage and design phase. It provides recommendations and guidelines for optimizing the carbon emission and indoor environment based on the performance improvement of building operational conditions. [ABSTRACT FROM AUTHOR]

• Two model buildings are specially built for comparative study. • Dynamic monitoring of external insulation for improving thermal environment and energy saving during heating. • The time for EPS building to approach the air temperature set value has no obvious advantage. • The energy saving effect of short-time heating operation of EPS building is very weak. • A dynamic index is proposed to evaluate the improvement effect of external insulation on indoor thermal environment. In this paper, two identical model buildings were built, one of which adopted 38 mm Expanded Polystyrene (EPS) board as the external insulation. Under the same heating set-point temperature, the dynamic change process of indoor thermal environment and heating energy consumption of EPS insulation building and non-insulation Reference building was compared and monitored. Results show that under the same heating set-point temperature, the indoor temperature of the two buildings can quickly approach the set value in about 20 min. However, the temperature rise of the internal surface of the wall lags behind. After several hours, the advantage of the temperature rise of the internal surface of the EPS building gradually appeared. The energy consumption of the two buildings is similar in the initial heating period of 20 min, and the energy saving rate of EPS building increases slowly with the increase of the heating duration. The energy saving rate is about 1%–26% in the range of 0.5–8 h intermittent heating in hot summer and cold winter zone. The change curve of cumulative temperature rise ratio with heating time is proposed to evaluate the dynamic improvement effect of external insulation on indoor thermal environment. This research provides a reference basis for the development of energy conservation. [ABSTRACT FROM AUTHOR]

Abstract: The investigation presented in this paper has three main objectives. The first one is to study, through a case study, if it is possible to acceptably predict the energy consumption of a massive residential free-running building, when the exact behavior of the occupants is unknown or actual indoor conditions are not monitored, assuming standard use and occupation schedules, for the dry climate of the Argentinean Northwest. The second objective of the paper is to detect the possible causes of differences between actual and predicted energy consumption through an exhaustive thermal monitoring and occupant''s behavior, in order to obtain an improved model of the building giving more accurate predictions of the energy consumption. The third objective is to analyze the effect on the annual energy consumption of changing the massive envelope by a lightweight one. The comparison of real and simulated consumptions under comfort conditions defined by ASHRAE Standard 55 shows that simulations overestimated the energy consumption for heating and cooling. The main causes were detected from the experimental monitoring, indicating a lower use of the air conditioning equipment than the supposed initially. Simulations were improved to consider actual use and occupation conditions. Finally, an annual simulation of the improved model performed by changing the envelope material to a lightweight one showed that energy consumption for heating was increased, while energy consumption for cooling was decreased. In an annual balance, the massive walls are preferable over lightweight ones in arid sunny climates as in the Argentinean Northwest, giving energy savings of around 25%. [Copyright &y& Elsevier]

Abstract: This paper demonstrates a systematic, evidence-based methodology for calibrating whole building energy models. The methodology uses version control software to store a complete history of the calibration process, including the evidence on which decisions were made. This paper details the calibration of a whole building energy model to hourly energy consumption data using the methodology. The case study building was a 30,000m2, four-floor office building located on Intel''s campus in Ireland. The final calibrated model represents the building to a high level of detail using a large number of zones and uses measured lighting and plug load data in the simulation at hourly intervals. The results show excellent correlation with the measured HVAC consumption data for the analysed year (2007), demonstrating the effectiveness of the methodology. Mean Bias Error (MBE) and Cumulative Variation of Root Mean Squared Error (CVRMSE(hourly)) for HVAC electrical consumption were −4.16% and 7.8%, respectively for the final model. This model was then used to investigate Energy Conservation Measures (ECMs) for feasibility. The paper concludes with a discussion of discrepancies remaining in the model, the issues encountered related to the criteria used for determining when a model is calibrated, and recommendations for future calibration case studies. [Copyright &y& Elsevier]

Abstract: In early 2006 the European Commission launched the GreenBuilding Programme (GBP), aimed at improving the energy efficiency of existing as well as newly constructed non-residential buildings in Europe on a voluntary basis. Building owners from different sectors are participating in the programme, e.g., public authorities with schools, hospitals or swimming pools, companies from the services and industry sectors with office buildings, sports centres and hotels. The aim of the paper is to provide a summary analysis of the results of the GBP over its almost four-year operation – from the launch of the programme in 2006 until the end of 2009. By the end of 2009, 167 Partners had joined the programme with almost 300 buildings from all sorts of fields and sectors of operation. The total savings achieved by the Partners are 304GWh/year. The buildings themselves may vary in age, size and use, but they all have in common the energy performance, which goes far beyond the average performance of buildings in the participating countries. The paper focuses on efficiency measures implemented in the participating buildings and the achieved energy savings. [Copyright &y& Elsevier]

Abstract: Causes and effects of a few real faults in a hydronic heating system are explained in this paper. Since building energy management system (BEMS) has to be utilized in fault detection and diagnosis (FDD), practical explanations of faults and their related effects are important to building caretakers. A simple heat balance model is used in this study. The model is calibrated using the optimization tool. Site data from the BEMS of a real building are calibrated against the model. Desired and real data are compared, so that the effects of the following faults are analyzed: faults in an outdoor air temperature sensor, fault in the time schedule, and a water flow imbalance problem. This paper presents an overview of the real causes of the faults and their effects both on the energy consumption and on the indoor air temperature. In addition, simple instructions for the building caretakers for fault detection in the hydronic heating systems are given. [Copyright &y& Elsevier]

Abstract: Constructing an indicator to measure the effectiveness of energy management is important for energy agencies and authorities. This paper uses multiple linear regression method and data envelopment analysis to examine the effectiveness of energy management. First, the regression method using environmental factors is used to calculate the predicted energy usage intensity of each evaluated building. Data envelopment analysis is then employed to calculate overall energy efficiency, using the predicted energy usage intensity as output and the observed energy usage intensity as input. Data envelopment analysis can be further applied to measure the overall energy efficiency in details by examining environmental factors and management factors. Finally, the energy consumption of buildings can be measured to evaluate the effectiveness of energy management. Buildings examined as a case study in this paper are government office buildings in Taiwan. The results show that most of the buildings evaluated to report a higher predicted energy usage intensity have successfully used efficient energy management methods in energy saving. [Copyright &y& Elsevier]

Abstract: The present paper deals with the energy performance, energy classification and rating and the global environmental quality of school buildings. A new energy classification technique based on intelligent clustering methodologies is proposed. Energy rating of school buildings provides specific information on their energy consumption and efficiency relative to the other buildings of similar nature and permits a better planning of interventions to improve its energy performance. The overall work reported in the present paper, is carried out in three phases. During the first phase energy consumption data have been collected through energy surveys performed in 320 schools in Greece. In the second phase an innovative energy rating scheme based on fuzzy clustering techniques has been developed, while in the third phase, 10 schools have been selected and detailed measurements of their energy efficiency and performance as well as of the global environmental quality have been performed using a specific experimental protocol. The proposed energy rating method has been applied while the main environmental and energy problems have been identified. The potential for energy and environmental improvements has been assessed. [Copyright &y& Elsevier]

Abstract: The paper deals with the optimization of building energy efficiency in tropical climates by reducing the period of air-conditioning thanks to natural ventilation and a better bioclimatic design. A bioclimatic approach to designing comfortable buildings in hot and humid tropical regions requires, firstly, some preliminary, important work on the building envelope to limit the energy contributions, and secondly, an airflow optimization based on the analysis of natural ventilation airflow networks. For the first step, tools such as nodal or zonal models have been largely implemented in building energy codes to evaluate energy transport between indoor and outdoor. For the second step, the assessment of air velocities, in three dimensions and in a large space, can only be performed through the use of detailed models such as with CFD. A new modelling approach based on the derivation of a new quantity—i.e. the well-ventilated percentage of a living space is proposed. The well-ventilated percentage of a space allows a time analysis of the air motion behaviour of the building in its environment. These percentages can be over a period such as 1 day, a season or a year. Twelve living spaces with different configuration of openings have been studied to compare the performance of ventilation function of the opening distribution. Results and discussion are presented in the paper. This method is helpful for an architect to design the rooms according to their use, and their environment. Finally, the developed models can be used in building projects to estimate the period of the natural ventilation and to reduce the energy consumption due to air-conditioning. [Copyright &y& Elsevier]

This paper presents a practical method to optimize in-building section of centralized Heating, Ventilation and Air-conditioning (HVAC) systems which consist of indoor air loops and chilled water loops. First, through component characteristic analysis, mathematical models associated with cooling loads and energy consumption for heat exchangers and energy consuming devices are established. By considering variation of cooling load of each end user, adaptive neuro-fuzzy inference system (ANFIS) is employed to model duct and pipe networks and obtain optimal differential pressure (DP) set points based on limited sensor information. A mix-integer nonlinear constraint optimization of system energy is formulated and solved by a modified genetic algorithm. The main feature of our paper is a systematic approach in optimizing the overall system energy consumption rather than that of individual component. A simulation study for a typical centralized HVAC system is provided to compare the proposed optimization method with traditional ones. The results show that the proposed method indeed improves the system performance significantly. [Copyright &y& Elsevier]

This paper presents a practical case study using the computational fluid dynamics (CFD) technique in retrofitting the large cabinet fans and airflow channels in malt processing air-conditioning systems in order to get uniform airflow field, to increase fan capacity and reduce energy consumption.Site measurements were used to validate the models before they were used. CFD simulation results were used to evaluate and optimise the design and construction of splitter vanes in the airflow channels and scrolls of the fans. Simulation tests showed that the fan capacity (maximum total air flow rate delivered at full fan speed) could be increased by 8.3–20% using different shapes of scroll, and 30–34% by adding splitter vanes further in the airflow channels. After retrofitting the fans and airflow channels, site measurements showed that the fan capacity increased 21–24 and 28–29%, respectively in the two buildings validated. The approach of using the CFD technique in the retrofitting, the simulation results, and the site measurements before and after fan retrofitting are presented and compared in this paper. [Copyright &y& Elsevier]

Museums are buildings of particular significance due to their function and their status. At the same time they are buildings in which the principles of energy conservation are rarely applied, sometimes without reason. It has been decided by the Hellenic Ministry of Culture to convert a medieval tower, built in the year 1344 as a fortress with 0.8–1.5 m thick walls and almost no windows, into a museum. The present paper discusses the difficulties that arise in the attempt to balance between the indoor climate conditions necessary to protect the exhibits and to provide comfortable conditions to the visitors, whilst respecting the aesthetics and the historical significance of the building. Furthermore, one needs to consider the difficult but necessary task of assessing factors such as the building’s shell’s thermal conductivity and capacity, the ventilation necessary as well as the indoor air movement, in order to determine the cooling loads. Finally, the challenge lies in designing and dimensioning an effective and efficient HVAC system, which should be as discrete as possible. The present paper aims to present the results of the study, to discuss the expected energy behaviour of the building and to comment on the options for introducing energy conservation techniques. [Copyright &y& Elsevier]

The literature concerning the application of information-feedback methods for saving energy in the home is reviewed. Particular attention is given to electronic feedback via smart meters and displays, or “energy-consumption indicators” (ECI). Previous studies have not focused on individual appliances, but this paper presents the findings of a UK field study involving 44 households which considered domestic cooking: it compares the effectiveness of providing paper-based energy-use/saving information with electronic feedback of energy-consumption via ECIs designed specifically for this investigation. Twelve Control Group households were monitored for a period of at least 12 months and this revealed an average daily consumption for electric cooking of 1.30 kWh. Subsequently across a minimum monitoring period of 2 months, 14 out of 31 households achieved energy savings of greater than 10% and six of these achieved savings of greater than 20%. The average reduction for households employing an ECI was 15%, whereas those given antecedent information alone reduced their electricity consumption, on average, by only 3%. The associated behavioural changes and the importance of providing regular feedback during use are identified. It is recommended that further attention be given to optimising the design and assessing the use of energy-consumption indicators in the home, in order to maximise the associated energy-saving potential. [Copyright &y& Elsevier]

• Residential sector accounts for a quarter of consumption and a fifth of CO 2 emissions. • HVAC accounts for a third of residential consumption, equivalent to 8% of final energy. • Collecting and reporting information is crucial to target residential energy policies. • Retrofitting of residential stock and adopting conservation behaviours are mandatory. • Residential electrification is far away and needs to be accompanied by the decarbonisation of the electricity sector. The residential sector is a major contributor to climate change, accounting for almost a quarter of global energy consumption and a fifth of CO 2 emissions in 2019. Since 2000, residential consumption has grown at a sustained rate of 1%/year, driven by the development of emerging economies, despite stagnation in developed countries. The increasing demand for living space, energy services and comfort levels seems difficult to curb, especially in the developing world on its fair attempt to reduce inequality. To understand these trends, this paper analyses the trajectories of key indicators of activity and efficiency in this sector, for emerging and developed regions, as well as for major consuming nations, mainly China, United States, European Union, Russia, India, Japan and Brazil. Despite data limitations, meaningful cross-country comparisons are presented for fuel mixes, energy services and dwelling types. Heating, ventilation and air conditioning (HVAC) systems account for a third of residential consumption and will grow rapidly as increasing wealth in emerging economies allows for satisfying the thermal comfort demand. Economic development will naturally increase housing size and equipment level and reduce household size, and could close the per capita consumption gap between developing and developed regions. Efficiency improvements could reduce the energy use intensity to around 10 koe/m2 but will not be enough to curb residential consumption. International cooperation, policy support and funding are essential to accelerate development and efficiency gains in developing countries without compromising environmental targets. In the meantime, politicians should focus on decarbonising the energy mix and promoting energy efficiency, while citizens focus on energy conservation to avoid irreversible environmental damage. [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]

Temperature and humidity independent control (THIC) systems demonstrate promising energy-saving potential compared with the conventional air conditioning systems. One type of THIC systems is proposed to use dual cooling sources with different temperatures since they could be produced easily by traditional vapor compression refrigeration chillers. This paper investigates the applicable condition of the THIC system based on dual cooling sources (DCSTHIC system). It is found that the DCSTHIC system has limited conditions (such as scopes of the heat moisture ratio and the fresh air rate) when applied, otherwise the indoor air temperature and humidity can’t be fulfilled, and further available scope of the heat moisture ratio realized by the DCSTHIC system is disclosed for air conditioned spaces. The minimum realized heat moisture ratio depends on the temperature of low-temperature cooling sources ( t LCS ). A parametric study is also conducted to analyze effects on the energy efficiency of DCSTHIC systems. These parameters include the heat moisture ratio ( ε ) and temperatures of dual cooling sources. Results show that DCSTHIC systems show more significant energy-saving potential in the air conditioned spaces with higher ε . The system COP improvement ranges from 3.1% to 17.5% compared with conventional air conditioning systems when the heat moisture ratio changes from 8000 kJ/kg to 15,000 kJ/kg. This study helps to guide the design and optimization of DCSTHIC systems. [ABSTRACT FROM AUTHOR]

Few examples studied applicability of exergy analysis on human thermal comfort. These examples relate the human-body exergy consumption rate with subjectively obtained thermal sensation votes and had been based on steady-state calculation methods. However, humans are rarely exposed to steady-state thermal environments. Therefore, the first objective of the current paper was to compare a recently introduced unsteady-state model with previously used steady-state model using data obtained under both constant and transient temperature conditions. The second objective was to explore a relationship between the human-body exergy consumption rate and subjective assessment of thermal environment represented by thermal sensation as well as to extend the investigation towards thermal acceptability votes. Comparison of steady-state and unsteady-state model showed that results from both models were comparable when applied to data from environments with constant operative temperature. In contrast, when applied to data with temperature transients the prediction of particular models differed significantly and the unsteady-state model resulted in better prediction of mean skin temperature. The results of the present study confirmed previously indicated trends that lowest human body exergy consumption rate is associated with thermal sensation close to neutrality. Moreover, higher acceptability was in general associated with lower human body exergy consumption rate. [ABSTRACT FROM AUTHOR]

This paper shows development of a simple, cheap “Building Energy Management System” (BEMS) to monitor energy consumption, and an application to measure energy consumption, including electricity and gas consumption in buildings. The system uses current transformers to measure electric consumption at each distribution box. Web cameras monitor lighting in each room, as well as air conditioning status by recognizing the movement of a ribbon at the outlet. Web cameras can also monitor gas consumption at the meter through character recognition. The data is sent via network to a computer for monitoring and analysis. As an example, key components of this BEMS were tested to measure building energy consumption of Osaka City University Sugimoto Campus in Japan for a period of 2 years (2013, 2014). The electric consumption of campus as well as the electric and gas consumption for air conditioning use was measured. Web cameras were installed in several rooms in one section of the campus to record lighting and air conditioning use data. The data was analyzed to reveal a correlation between hourly outdoor temperature and hourly electric consumption, with a stronger correlation between hourly outdoor temperature and hourly electric consumption for air conditioning. [ABSTRACT FROM AUTHOR]

The residential sector represents about 30% of the total energy demand in Europe. Included in this percentage, lighting consumption is one of the basic end uses in all households and it may come to represents 15–20% of the total electricity bill. This figure can be reduced using advanced control techniques or more efficient lighting technologies, requiring previous detailed information about current consumption patterns. In this context, bottom-up stochastic models are established as the main tools to study new energy savings. In this paper, a high-resolution stochastic model for simulating lighting consumption profiles was developed, obtaining both daily active and reactive instantaneous power demand profiles, with a 1-min resolution. The model takes into account the number of household residents and differentiates between weekdays and weekends. Moreover, the monthly and annual amounts of electricity demanded by lighting in Spanish households were simulated. The proposed model was also used to quantify the impact of LED technology's penetration into domestic lighting systems on consumption patterns. Research has revealed the existence of two consumption peaks matching with morning and evening. Although these peaks are hard to shift since they are due to human behavior, they are easy to reduce through the improvement of lighting systems. [ABSTRACT FROM AUTHOR]

In order to optimize the global energy performance of a ground source heat pump system, special attention needs to be paid to the auxiliaries as they stand for a considerable part of the total energy consumption. A new in situ experimental methodology based on the frequency variation of the water circulation pumps in order to optimize the energy performance of the system was previously published by the authors for a ground source heat pump system using a single stage heat pump with ON/OFF regulation. The original single stage heat pump was recently replaced with a multistage unit consisting of two compressors of the same capacity working in tandem. A new experimental campaign was carried out and a new study was performed in order to adapt the in situ optimization methodology to the performance of the tandem compressors unit, and, by extension, to the multistage case. This paper presents the in situ optimization methodology for the water circulation pumps frequency adapted for multistage ground source heat pump systems. Results show that energy savings up to 32% can be obtained by applying this optimization methodology. [ABSTRACT FROM AUTHOR]

China is currently experiencing rapid urbanization. The building sector plays an important role in China's energy conservation and emission reduction. An increasing amount of energy will be steadily consumed in the building sector as the urbanization process accelerates. China's government attaches great importance to building energy efficiency (BEE). How does the urbanization process affect building energy consumption (BEC)? How much energy can be saved in the building sector through implementation of energy polices? These questions are critical for government development strategies and planning. Thus, in this paper, an econometric model (co-integration technique) is developed to analyze how China's BEC is affected by macroeconomic variables in the context of urbanization, and also forecast the BEC and BEE potential until 2020 under different scenarios. The research result shows that occupants’ lifestyles, residents’ living standards, and energy price have significant influences on BEC. The building sector is likely to contribute approximately 20% to China's energy conservation through electricity pricing reform. [ABSTRACT FROM AUTHOR]

• A dynamic setting temperature that adapts to climate change was proposed. • The method was based on clothing adjustment behavior which adapts to thermal comfort. • The dynamic setting temperature had significant energy saving potential. • The dynamic setting temperature is useful for intelligent control of air-conditioner. Saving energy consumption of air-conditioning is essential to building energy conservation while satisfying the thermal comfort requirements of indoor environment. On the basis of human clothing adjustment behavior, a dynamic setting temperature (DST) that adapts to climate change was proposed in this paper, i.e. indoor air-conditioning setting temperature changes dynamically with outdoor air temperature; furthermore. A method was established to obtain the DST. The daily mean clothing insulation was predicted according to the historical temperature at first, then indoor thermal comfort temperature was calculated based on the variable clothing insulation, and finally the DST was determined. According to the value or range of predicted mean vote (0, -0.5~0.5, -1~+1) corresponding to the thermal comfort, three levels of DST were defined. The corresponding thermal acceptability rates were 95%, 90% and 73%, respectively. A simulation of DST was conducted in a public building in Changsha, China based on meteorological data of 2017. Three levels of DST ranges were obtained, varied from 20.1 to 27.8 °C in level I, 17.8 to 28.7 °C in level II and 15.4 to 29.7 °C in level III, respectively. The simulation results of operational air-conditioning energy consumption shows that the application of DST could save up to 65.5% of energy consumption compared with the traditional fixed setting temperature (FST), and the operational energy consumption decreased by 59.1% due to the application of level-III DST compared with level-I DST. Therefore, the DST proposed in this paper has significant energy saving potential while meeting the thermal comfort requirements. [ABSTRACT FROM AUTHOR]

Abstract: Liquid desiccant air-conditioning system is a novel air-conditioner with good energy saving potential. For the liquid desiccant air-conditioning system, the energy consumption mainly relies on the regeneration process of desiccant solution. As the regeneration process of the liquid desiccant air-conditioning system only needs low-grade energy, solar energy (a kind of renewable energy) can be used to regenerate the desiccant solution and the solar desiccant regeneration system has attracted many attentions. In this paper, recent theoretical and experimental works on solar thermal regeneration method and solar electrodialysis regeneration method of the liquid desiccant air-conditioning system are extensively reviewed. Moreover, the comparison of solar TH regeneration method and solar electrodialysis regeneration method is discussed. The results showed that compared to the solar thermal regeneration system, the solar electrodialysis regeneration system is more energy-efficient but expensive. [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]

Interest in urban building energy modeling as a tool to evaluate effective management of urban building energy and carbon reduction policies is increasing. Since it takes a lot of time to model all buildings in the city with the lack of information about buildings, archetypes have been used. However, the deterministic method using archetypes does not reflect uncertainty with the disadvantage of not presenting design alternatives. To overcome such problems, we proposed an urban building energy modeling method using a stochastic-deterministic-coupled approach. In this paper, the identifiability of unknown parameters in a building stock was verified by analyzing the effect of the meta-model accuracy on the estimation of unknown parameters in the proposed urban building energy model. In addition, the possibility of using energy conservation measure analysis of the proposed model was evaluated. As a result, the posterior distribution of unknown input parameters was distorted when using the meta-model instead of the original building energy model in Bayesian calibration for building stock. However, the distorted posterior distribution could evaluate the effect of energy conservation measures within 0.71% errors. [ABSTRACT FROM AUTHOR]