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This paper analyzes electricity use in buildings and explores key research questions related to assessing, rating, labeling, and benchmarking building energy use. The analysis reviews annual Energy Use Intensity (EUI) data from 3060 fully electric-powered buildings across six categories: residential, educational, offices, hospitals, hotels and restaurants, and wholesale and retail trade services. One-fifth of the analyzed buildings is derived from an energy dataset that offers a higher time-scale resolution, providing more detailed insights into energy usage patterns. The analysis employs various factors, including the seasonal variation factor (SVF), daily variation factor (DVF), monthly factor (M f), and hourly factor (H f), to gain a detailed understanding of actual energy usage at different time scales. The findings indicate that electricity use is less sensitive to seasonal variations than other energy carriers that provide heating and cooling. The paper provides hourly and monthly peak load percentages (PPL), which can indirectly assist in assessing hourly schedules for building energy performance simulations. The monthly energy use pattern varies between building categories, with high-energy months alternating between winter and summer. For non-residential buildings, high-energy hours correspond directly to the daytime, while for residential buildings, there is a shift towards the evening, and the daily amplitude is lower. Furthermore, the analysis of daily and monthly variability of heating energy carriers, even if non-electric, sheds light on the implications of electrification for these loads. • The study evaluates annual electricity data from 3060 fully electric-powered buildings. • Median EUIs are meaningful energy performance benchmarks by building category. • Residential and educational buildings exhibit EUIs of 90-120 kW h/m2. • Offices and hospitals demonstrate EUIs of 160-170 kW h/m2. • Monthly and hourly factors establish energy benchmarks for finer time resolution. [ABSTRACT FROM AUTHOR]

• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

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]

The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [ABSTRACT FROM AUTHOR]

Building energy consumption forecasting is crucial for energy managers and policymakers. However, acutely predicting the energy consumption of any building is more important in energy efficiency benchmarking of buildings. Energy benchmarking is a precise technique for measuring, tracking, and reducing end-use energy usage of buildings by employing comparative scenarios. Bottom-Up energy consumption assessment has been used in several studies to evaluate a collection of buildings' energy performance to a standard. Traditionally, researchers have used a single approach to predict the energy use of buildings and to conduct benchmarking. However, it has been found that doing so frequently compromises the accuracy of the predicted energy use of buildings. It also has an adverse effect on the buildings' energy benchmarking framework results. This paper will provide an energy benchmarking framework for residential buildings based on the blending techniques of multiple approaches. Over 3000 datasets were gathered from the Indian city of Jaipur. In order to analyse the trends in energy consumption, the data were divided into categories based on economic levels. The data is then subjected to some fundamental statistical analysis, along with several approaches are blended to forecast the energy consumption of the buildings with the highest accuracy. These benchmark levels set guidelines for assessing and recognising strong performance while also identifying underperforming buildings and giving them more priority for energy efficiency improvement. The technique may be used for different metropolitan levels and climatic conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Unique preconditions, specific characteristics for use can be boundary conditions. • Energy use, users' behavior, lighting are correlated conditions within buildings. • Boundary conditions can help explain the occupants' behaviour and the use of spaces. • Knowledge of boundary conditions helps to understand how to design buildings. • Boundary conditions can be building/ user/ input-values and method-specific. This paper aims to review the boundary conditions (B/C) in specific categories (energy, building use, and lighting) within non-residential buildings to pave the way to a better understanding of users' requirements and needs of the built environment. For this paper, B/C are understood as unique preconditions, specific characteristics for use, determining specific features of buildings, enabling an accurate understanding of non-residential spaces concerning energy use, user behaviour, and lighting. This paper describes the results of an overall quantitative (1st method) review and a systematic review (2nd method) of boundary conditions and their factors within different types of non-residential buildings from the users' perception. Followed by a qualitative experts' literature review (3rd method) on B/C within offices, schools, and hospitals chosen by a team of international experts working together on Subtask A: User perspective and requirements, Task 61 IEA (International Energy Agency): Solutions for daylighting and electric lighting. The first review method led to the selection of 21 papers. The second method resulted in the selection of 7 papers out of 93,143 found in Scopus; during the 3rd review, experts collectively chose 74 additional papers focussing on the users' factors contributing to specific B/C. The scope of this paper is limited only to offices, schools, and hospitals. Based on the findings, the authors recognise a broad definition of boundary conditions from specific values, and conditions to interconnected factors, user profiles, functions of the building types, and operating hours. This paper is an overview of B/C factors found in the literature that can help explain the occupants' behaviour and the use of spaces. B/C are often type of building/user/location/situation/simulation input-values and method-specific. Therefore, they cannot be widely applicable but offer patterns and help to understand the correlations between various factors shaping the built environment. A better comprehension of the reasons for identifying B/C and their factors can help in developing a deeper knowledge of how we use buildings to find optimal ways to design them. [ABSTRACT FROM AUTHOR]

Highlights • Calculation of life cycle costs and payback periods of building intervention packages. • Calculation of financial gap between nZEB and cost optimality. • Study covers single and multi-family house buildings for 2 periods and climate zones. • Ranking of intervention packages based on cost effectiveness and energy efficiency. Abstract Nearly zero energy buildings (NZEBs) constitute one of the main pillars of the energy policy of European Union (EU). Greece has recently established a clear definition for NZEB, however the interdependence between cost-optimality and the energy performance of NZEB has not been adequately studied. The present work includes a cost effectiveness analysis among different energy efficiency interventions for the existing residential Greek building stock. To this end, the calculation of the investment as well as the operating and maintenance cost for a wide range of energy efficiency measures were carried out. All calculations were based on the methodology defined in the Directive 2010/31/EU on the energy performance of buildings, while the economic evaluation assumptions were based on the EN 15459-1 standard. The goal is the determination of the most cost effective (cost-optimal) measures that are applicable for two different building types; Single Family House (SFH) buildings and Multi-family House (MFH) apartment blocks, taking into account the period of their construction and the climate zone they belong to. Furthermore, the scope of the paper includes also the assessment of the gap between these measures and the NZEB thresholds. The analysis showed that in various cases and depending on the exact national NZEB definition, NZEBs are located beyond cost optimality. [ABSTRACT FROM AUTHOR]

• Provided a platform to test various residential building control systems. • Used probability of occupancy to determine setback temperature when unoccupied. • Integrated optimizer with adaptive and occupancy control. • Generated dynamic electricity tariff based on wholesale electricity pricing. • Evaluated the peak load shaving potential with dynamic pricing and optimization. Energy consumption in buildings continues to rise with increased deployment of energy-consuming equipment such as Heating, Ventilation, and Air Conditioning (HVAC) amid a growing world economy. Renewable energy is projected to comprise a majority of the future electricity supply, but the intermittent nature of renewables means that consumption must respond to dynamic supply for optimal utilization. This paper proposes a novel HVAC control strategy for residential buildings using the adaptive comfort model, considering occupancy through probability and real-time information, and optimizing the HVAC schedule to reduce cost, maintain thermal comfort, and respond to the dynamic availability of renewable energy while being generalizable to different situations. To validate this approach, the Universal CPS Environment for Federation (UCEF) co-simulation platform is used to connect advanced building controls with the building energy simulation software EnergyPlus. Simulations are performed for a residential building in Sacramento, CA during a typical summer week. Economic impacts, energy consumption, and thermal comfort are analyzed for traditional, adaptive, and occupancy-based control strategies under demand-based, tiered, and fixed electric tariff systems. Simulation results show that occupancy consideration, adaptive thermal comfort, and optimization can reduce cost by 50.1 %, electricity consumption by 52.9 %, and discomfort by 56.2 % compared to traditional fixed setpoints. The ability of the proposed HVAC control strategy to shift energy consumption away from peak times under a demand-based tariff system is qualitatively analyzed and findings suggest that maximum load-shifting on a grid-scale is attained using occupancy consideration with optimized control and demand-based pricing. For individual residential buildings, similar economic benefits can be gained using the less-complex adaptive HVAC control strategy with existing tiered or simple electric tariff systems. [ABSTRACT FROM AUTHOR]

Airtightness testing is widely undertaken to assess the as-built performance of dwellings, in support of achieving energy and ventilation strategies. Mandatory schemes operate in some countries, such as the UK, to ensure that dwellings are built in accordance with their design air permeability. However, testing is only useful if the results give a true picture of the airtightness of the building. Previous literature has investigated factors which could influence airtightness test results but has not questioned data quality, despite the pressure on builders to achieve design targets. This paper presents air permeability results from the largest UK dataset, comprising 144,024 dwellings tested under the Air Tightness Testing and Measurement Association (ATTMA) scheme. The data show an unexpected distribution of test results with narrow peaks just within test targets. Such results were not expected theoretically but do reflect findings in other fields where performance-based targets are in place. Such a close match between design and tested airtightness may be achieved by remedial works taking place during the test rather than afterwards. Recommendations are made with respect to quality assurance systems, design guidance and on-site sealing practices to increase the likelihood of long-term airtight buildings being constructed first time. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has significantly affected people's behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre– and post–COVID-19 pandemic times. The weekend usage patterns look similar pre– and post–COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems. [ABSTRACT FROM AUTHOR]

• Data about DHW in residential buildings were collected by survey in Southern Italy. • Contextual and personal factors influencing DHW usage were considered. • Descriptive statistics were performed to characterize DHW by climatic zone. • Inferential statistics were conducted to discover DHW usage patterns. • Four clusters of dwellings were identified considering DHW daily usage hours. In European efficient buildings, the share of energy use for DHW is a significant percentage of the heat requirement. The evaluation of DHW energy demand and consumption patterns has been neglected in the past and studies are located in Northern countries. This paper presents a survey conducted in Southern Italy. Descriptive statistics were performed to characterize DHW production by climatic zone. Inferential statistics were conducted to discover significant contextual and personal variables and identify usage groups. The most used energy source was biomass (49.3%), followed by methane gas (37.7%). Fireplaces were installed in the coldest zone, in detached houses, more in small municipalities (36%), and low-income families (32%). Solar systems were in 8% of dwellings having income higher than 28000€. Four clusters of dwellings were identified considering the daily usage hours. The eldest and less numerous households fell into the cluster with the lowest usage (3.5 h). Households with a percentage <25% of unemployed components had more probability to belong to clusters with more DHW usages. The paper contributes to fill the investigation in the Mediterranean area and provides a systematic approach to expand the limited knowledge about the influencing factors on the DHW production and usage. [ABSTRACT FROM AUTHOR]

Residential buildings are currently equipped with energy production facilities, e.g., solar rooftops and batteries, which in conjunction with smart meters, can function as smart energy hubs coordinating the loads and the resources in an optimal manner. This paper presents a mathematical model for the optimal energy management of a residential building and proposes a centralized energy management system (CEMS) framework for off-grid operation. The model of each component of the hub is integrated within the CEMS. The optimal decisions are determined in real-time by considering these models with realistic parameter settings and customer preferences. Model predictive control (MPC) is used to adapt the optimal decisions on a receding horizon to account for the deviations in the system inputs. Simulation results are presented to demonstrate the feasibility and effectiveness of the proposed CEMS framework. Results show that the proposed CEMS can reduce the energy cost and energy consumption of the customers by approximately 17% and 8%, respectively, over a day. Using the proposed CEMS, the total charging cycles of the ESS were reduced by more than 50% in a day. [ABSTRACT FROM AUTHOR]

[Display omitted] • Development of two benchmark models for post-world war II residential buildings. • Average energy use intensity per household (archetypes A and B) were 166 and 155 kWh/m2/year. • Models validated with four-year monitoring data on energy consumption. • Households are dominated by senior adults and their occupancy profiles are presented. • Findings on energy needs and use intensity are useful in temperate and continental climates. In the context of the European carbon neutrality targets, building benchmarks are a key issue for the renovation of existing buildings. Although there are various benchmark methods for energy efficiency characterization, their application to the residential sector is still limited. This paper developed two building simulation models for post-world war II houses in Belgium based on data from post-occupancy measurements and field survey campaigns. The study reports the energy characteristics and occupancy profiled of detached single-family houses. An analysis of energy consumption (electricity and natural gas) and a walkthrough survey were conducted between 2016 and 2019. The benchmark model's validity has been further checked against public statistics and verified through model calibration and monthly energy bill comparison. Two reference models representing 633.702 post-WWII single-family houses in Belgium were created and validated. The first archetype has an average energy use intensity of 166 kWh/m2/year and represents detached single-family houses built between 1945 and 1969. The second archetype has an average energy use intensity of 155 kWh/m2/year and represents detached single-family houses built between 1970 and 1990. The paper provides a timely opportunity to evaluate the real performance of post-world war II most common archetypes concerning design assumptions and how building professionals can turn the energy performance gap challenge to their advantage. The findings on energy needs and intensity are useful for creating future renovation scenarios for similar archetypes in Western European countries. [ABSTRACT FROM AUTHOR]

One of the main required actions for moving forward in zero-carbon cities' mission is to increase building energy efficiency. Building energy simulations are key tools for HVAC control, building energy management, testing different building energy efficiency scenarios, and providing feedback to the occupants. Unfortunately, these tools have a significant weakness in occupant behavior modeling and prediction. Several recent studies used different occupancy measurements and methods to predict occupant behavior. However, they suffer from threatening the occupant's privacy and the high cost of their infrastructure and deployment. This paper aims to leverage passive WiFi sensing methods for occupant behavior estimation using commercial off-the-shelf WiFi devices, for which the infrastructure is already available in many buildings. Passive and device-free WiFi sensing does not threaten the occupant's privacy, and its deployment cost is low. Therefore, this method of occupancy measurement has the potential to be used on an urban scale and to play an essential role in zero carbon and smart cities in the future. Different machine learning algorithms have been applied to the collected, denoised, and preprocessed Channel State Information (CSI) data to estimate the occupant behavior. Five schedules of occupancy, occupant activity, lighting, electrical equipment usage, and thermostat set point temperature could be extracted and estimated from CSI data. In the last step, all estimated schedules were fed into EnergyPlus, an energy simulation software, along with other required data for accurate energy demand calculation to estimate heating and cooling demand, which can be used for HVAC control and occupancy feedback. [ABSTRACT FROM AUTHOR]

[Display omitted] • A hierarchical approach for automatic layout of an underfloor heating system is proposed. • The routing problem is formulated as a shortest path problem in a proper routing graph. • An order relation is defined to separate the intersecting paths. • A depth-first layout algorithm based on recursion is developed to solve the coverage path planning problem. The layout of an underfloor heating system determines its heating performance. Conventionally, the design is completed by qualified experts using professional software, but this method is inefficient and heavily relies on the experts' previous experience. This paper proposes a hierarchical approach for the automatic design of underfloor heating systems aimed at residential buildings, and the underfloor heating layout problem is decomposed into a routing problem and coverage path planning problem. First, the routing problem is formulated as a shortest path problem in an appropriate routing graph and solved to provide the routing of pipes for further coverage. Subsequently, a depth-first layout algorithm is developed to recursively simplify the coverage path planning problem to obtain the basic rectangle layout, achieving uniform coverage of the given layout zone. Simulation results on two houses show that, unlike one popular commercial platform, the proposed approach generated feasible solutions in all 13 test instances. The new method improved the minimum temperature, average temperature, average percentage of nodes greater than 30 °C, and total energy efficiency by 3.18 °C, 0.79 °C, 3.23%, and 4.19%, respectively, with a lower variance on average. These improvements lead to a higher coverage rate, more even thermal distribution, and stronger robustness under flexible parameter selection. [ABSTRACT FROM AUTHOR]

• In 2017, renewable heat used in residential buildings in AT and CH was 48% and 30% • Renewable heat must be increased by 131% in AT by 2040 and 210% in CH by 2050. • Public subsidies contributed to 51% and 36% of total heat savings in AT and CH. • AT relies more on public subsidies and has a lower cost-effectiveness of policies. • CH obtains similar heat savings with eight times lesser public subsidies. Reducing heat demand and decarbonising heat supply are essential if countries have to meet net zero emission targets. This paper presents a comparative assessment of the impact of energy efficiency polices for heat demand reduction and heat decarbonisation in the buildings sector (2000–2017) in Austria (AT) and Switzerland (CH). It assesses the heat demand, heat supply, effect of different factors on changes in total heat consumption, impact of energy policies that provide public subsidies for heating and compares the effectiveness of different policies and measures. The assessment shows that renewable heat supply in residential buildings has to be increased by about 150 PJ (130% increase from 2017) in AT by 2040 and by 120 PJ (210%) in CH by 2050, which is challenging. Energy savings from improvements in energy efficiency from 2000 to 2017 are 83 PJ in AT and 97 PJ in CH, but these are largely offset by increase in activity and wealth effects thereby resulting in small changes in final heat consumption. The average (2014–2017) annual public subsidies for heating were about 2500 million Euros and 310 million CHF and contributed to 51% and 36% share of energy saving in AT and CH respectively. Both countries achieved similar energy savings, albeit following different policy approaches. Public subsidies for heating are an important policy instrument in AT but have lower cost effectiveness. On the other hand, CH minimised the use of public spending by deploying other policies and funding measures that leveraged private investment to achieve similar energy savings. [ABSTRACT FROM AUTHOR]

The main objective of the presented paper was to evaluate the integrated design strategies applied in refurbishment of the prefabricated residential housing, erected in ′70 in the New Belgrade, Serbia, in order to achieve energy savings accompanied with reduction of CO 2 emissions and improvement of households’ health and comfort. Conducted study led to the preliminary design of energy refurbishment of the existing building, and its conversion to energy efficient building with minimized loads. Building's dynamic behavior and energy efficiency have been optimized implementing BPS-Building Performance Simulation. Very significant reduction of thermal and cooling loads with the reference to the building's existing status is obtained. Refurbishment encompassed comprehensive optimization of building's envelope structure, natural and mixed ventilation. The implementation of a series of EEI (energy efficiency improvement) measures resulted in significant reduction of buildings energy loads. The investment in energy efficiency retrofitting can improve macroeconomic stability and contribute to the sustainable economic growth. Furthermore, economic analyses were performed for each model, considering present economic situation in Serbia and availability of funds for refurbishment. Presented methodology and results of the performed analyses offer an opportunity to extend their application to other neighborhoods, exploring refurbishment potential results if applied on a greater urban scale. [ABSTRACT FROM AUTHOR]

Residential building sector in Serbia has changed dramatically over the last two decades. Large scale projects have given way to individual, private initiative resulting in smaller interventions rarely exceeding one lot. For this reason architectural concepts, building types, scopes and construction technology have been marginalized and fallen under the influence of market mechanisms and stringent local planning procedures. New regulations on energy efficiency have risen the standards for thermal insulation therefore increasing the thickness of building enclosure. This actually means that construction costs are increased and net built area, therefore expected profit, reduced. In order to provide the viable ground for both implementation of new regulations and economic benefits for investors, authors of energy efficiency regulations in Serbia have noted a whole set of solar systems, among which sunspaces that would not count as a part of gross area, provided that they contribute to the increase of energy performance of the building. This paper describes the case of a typical residential new construction in Belgrade that has applied the prescribed solutions and became the first building that has obtained the building permit by applying a sunspace as an efficient strategy for energy saving. [ABSTRACT FROM AUTHOR]

Currently, there is no clear and unified understanding about the status quo of China's energy consumption in the building sector. In addition, a considerable underestimation of energy associated with buildings has impeded the effective implementation of measures to improve building energy efficiency of China. Thus, in this paper, we seek to identify the building sector's energy consumption of China by establishing an estimation model of building energy consumption from a life cycle perspective. On the basis of macro-level statistical data and relevant literature, we analyze the activities in each phase and calculate associated energy consumptions throughout buildings’ whole life cycle in China from 2001 to 2013. The results show that China's energy consumption associated with buildings has reached 1.66 billion tons coal equivalent in 2013, with a stable growth rate of 7% annually since 2001. Buildings’ life-cycle energy has approximately accounted for 43% of China's total energy consumption for recent three years (2011–2013). What's more, energy consumption in buildings’ operation phase has been salient, accounting for over 20% of China's total energy consumption. More focus should be drawn on energy efficiency in building material production phase and energy consumed in China's rural residential buildings as both have been significantly neglected. [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]

• End-use of electricity consumption in residential buildings in Gulf Cooperation Council countries was presented. • Discrepancies in certain indicators have been observed by the end-use of electricity consumption. • Improving the efficiency of air conditioners and thermal insulation of the walls are the best measures to conserve electricity in residential buildings. • The results can be used in areas with a similar climate, living standard, buildings types, and the inhabitants' behavior. Energy conservation and improvement in energy efficiency yield multiple technical, economic, environmental, and social benefits and realize comfort and sustainability of residential buildings (RBs). This review paper presents the end-use of electricity consumption in RBs and the results of economic analysis. In addition, a description and discussion of studies on energy conservation measures, Net Zero Energy Building, and renewable energy in RBs are discussed. The percentage of end-used energy consumption for different purposes obtained in many studies are often not consistent. Moreover, discrepancies in certain indicators have been observed, necessitating the need to clarify the factors in the consumption of electricity in RBs. Further, a few studies used the term energy consumption in buildings (total or electrical); however, specifying the type of buildings to identify and use the necessary indicators of energy consumption in each type of building are desirable. Furthermore, most studies emphasized improving the efficiency of air conditioners and thermal insulation of the walls as these are the best measures to conserve electricity. [ABSTRACT FROM AUTHOR]

Human influence is recognized as a major source of discrepancy between predicted and actual building energy use and has been a subject of extensive analysis for many years now. However, the impact that different users can bring to the actual performance of a building has not yet been studied in depth. This paper aims to contribute to this understudied dimension of the performance gap by providing a quantitative assessment of the impact of different users in residential heating consumption and indoor environmental conditions. For this purpose, heating energy consumption profiles for real users along with their corresponding thermostat settings were modeled in a building simulation model of a single dwelling thus allowing the study of the user factor in isolation. Remarkable differences were found in the resulting heating energy consumption and in the percentage of time that thermal comfort conditions defined by building regulations and standards were met for the different user scenarios. Results also demonstrate how the more complicated and varying the heating practices of a user are the more varying and unpredictable the impacts on heating consumption and comfort are. Overall, findings add to the growing body of literature that questions the standardized heating profiles and temperature settings used in energy simulation for residential buildings. [ABSTRACT FROM AUTHOR]

• Occupancy-based HVAC control using dynamic conditioning time estimation. • Deep learning algorithms are employed to provide online estimations of heat-up time. • Profitability of smart thermostats is studied via comprehensive financial analysis. • Occupancy information might negatively affect peak energy demand. • Conservative setback provides relatively poor financial gains. This paper presents a rule-based (RB) heating, ventilation, and air-conditioning (HVAC) control system using a multi-layer perceptron network, a deep learning algorithm, for estimating dynamic preconditioning time in residential buildings. The proposed system takes advantage of occupancy, indoor temperature, and weather data to make control decisions in buildings. The system performance is evaluated in terms of financial, demand-side management, energy-efficiency, and occupants' thermal comfort. The proposed approach considers the perfect occupancy prediction assumption to remove the impact of the uncertainty associated with occupancy prediction and to estimate an upper bound limit for the system performance. The system performance is compared with that of conventional rule-based control approaches to show its effectiveness. To select the optimal control system, the TOPSIS method, as a multi-criteria decision-making approach, is employed. The sensitivity of the proposed system to the temperature setback is also assessed by considering conservative, medium, and deep setback bounds. It is demonstrated that the proposed system outperforms other alternatives when the deep and medium bounds are utilized. This study reveals two limitations of occupancy-based control systems by investigating their performance from financial and peak-demand points of view. First, these systems can cause peak-demand issues and increase the on-peak energy consumption by up to 10%. Secondly, employing a conservative setback can significantly decrease the financial merits of the system, leading to a discounted payback period of 10.87 years for implementing smart thermostats. [ABSTRACT FROM AUTHOR]

• Linking top-down energy efficiency indicator analysis with bottom-up policy analysis. • Explaining the contribution of energy efficiency policies in Germany and Switzerland. • Analysing the counteracting effects to energy policy of rebound and non-compliance. This paper studies the factors underlying the evolution of the energy consumption for space heating in residential buildings by linking top-down analysis, based on meso -indicators, and bottom-up analysis, based on policy evaluations. The top-down analysis (i.e. the perspective from energy statistics) allows one to separate the change in total energy use into activity level, societal factors and energy efficiency gains. The explanatory power of the resulting meso-(statistical) indicators is often limited, if the underlying factors are not examined (e.g. changes in heating levels and patterns, weather effects, cost of energy and policies regarding insulation and heating system standards). We overcome most of these drawbacks by conducting a bottom-up analysis (i.e the perspective from single policy measures), which enables us to discern the contribution of energy efficiency policies to the changes observed with the meso -analysis. We focus on space heating consumption in the residential sectors for Germany and Switzerland. A major aim of this analysis is to show the contribution of energy efficiency policies (such as thermal building regulation, subsidy programmes, fiscal measures etc.) towards the changes in this indicator. The results show that the progress in energy efficiency (both autonomous and policy induced) in both countries had the greatest effect (-776 PJ for Germany, −42 PJ for Switzerland) regarding the change in energy consumption for space heating in the period from 2000 to 2016. However, the impacts of "technical and comfort" rebounds (+436 PJ for Germany, N/A for Switzerland) and other developments such as societal changes (+316 PJ for Germany, +35.5 PJ for Switzerland) were found to compensate for a significant part of the energy efficiency gains. In both countries, it was possible to link physical energy efficiency indicators to policy evaluation, but limitations were also identified which are primarily related to data gaps. [ABSTRACT FROM AUTHOR]

• The performance of Saudi houses is compromised by weaknesses in the building envelope. • Walls formed with insulated concrete blocks do not comply with the Saudi Code 2018. • The thermal bridging increases the thermal transmittance considerably. • 39% of energy consumption is attributed to heat loss from thermal bridging. • External insulation improves the U-value and reduces the impact of bridging. Electrical energy usage in Saudi Arabia is high (~300 TWh/yr) and is increasing (>5%/yr). The residential building sector is responsible for approximately half of the total electricity usage. Past studies have shown that up to 70% of the electric energy used in buildings in Saudi Arabia is consumed in the air conditioning of internal space. This study investigates this significant cooling requirement, particularly concerning the building envelope in typical detached villa housing. The paper concludes that walls formed using insulated concrete blocks only, as is common in Saudi Arabia, do not ensure compliance with the minimum requirements of the Saudi Code 2018. Thermal bridging of the building's envelope, which is currently not given due focus in the code, undermines the performance further. Bridging caused by the mortar joints between blocks, and by the cast concrete structural elements, increases the thermal transmittance through the envelope by a factor of two, relative to a non-bridged insulated concrete block wall. Simplified methods for thermal bridging calculation are referenced in the Saudi code, and these are evaluated here with reference to a detailed finite element study. Modelling studies show that the neglection of thermal bridging could underpredict building energy load by approximately 54 kWh/m2/yr – from 139 to 85 kWh/m2/yr. A 55 mm thick continuous external insulation layer is proposed to improve the performance considerably, reducing the wall-averaged thermal transmittance from 1.27 W/(m2·K) to 0.34 W/(m2·K) and hence achieving compliance with the latest building code. [ABSTRACT FROM AUTHOR]

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

• A new retrofitting strategy by using prefabricated elements window machine. • Minimization of the renovation costs and speeding up the retrofit action. • A potential in energy saving and improving the Indoor Environment Quality. • Further significance in retrofit and healthy home office working environments. The renovation of existing residential buildings across Europe has become a key factor for energy saving and the improvement of Indoor Environment Quality (IEQ). This paper presents an investigation of IEQ for a typical 1960s single-family house in Germany before and after a new retrofitting strategy (prefabricated element with integrated ventilation and new thermal envelope). In-situ measurements were applied to investigate the energy efficiency and IEQ improvement for the new retrofitting strategy in temperate winter regions of Europe. The simulation model replicates the measured data to be closer to reality and simulates a home office (COVID-19) scenario. The in-situ measurements showed that our retrofitting strategy increases the indoor air temperature during the heating period by up to 2.5 °C, decreases relative humidity by up to 3.8% and increases CO 2 by up to 24 ppm than before. As the simulation results shows, the retrofitted home office scenario allows a reduction in heating energy of up to 77%, an increase in CO 2 concentration of up to 41.8 ppm, 0.5% less relative humidity and 1.6 °C higher indoor air temperature than that without retrofitting. The new approach to retrofit residential buildings thus showed a potential in energy saving and improving the IEQ. [ABSTRACT FROM AUTHOR]

A novel dynamic overhang system is evaluated in this paper when applied to control solar heat gains through windows of US residential buildings. In particular, the energy performance of the dynamic overhangs is compared to static systems using various operation scenarios. The main objective for the control strategies evaluated in the analysis is to minimize annual heating and cooling energy consumption when dynamic instead of static overhangs are applied to US residential buildings. The operation of the dynamic overhangs is adjusted to account for the range of positions allowed as well as the setting frequencies. In particular, the dynamic overhangs can be set on hourly, daily, and monthly basis depending on the window orientation and the time of the year. The analysis has indicated that the performance of the dynamic overhangs depend on their design specifications as well as on the window glazing type. However, the energy saving potential for the dynamic overhangs compared to static devices depend largely on the window size and the climate with significant reduction in cooling energy use achieved in hot and mild US climatic zones. Indeed, the dynamic overhangs can save over 45% of the air conditioning needs for US homes with window-to-wall ratio of 30% located in Phoenix, AZ, and San Francisco, CA, when automatically operated on hourly basis. [ABSTRACT FROM AUTHOR]

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

• Several control strategies are developed for attic switchable insulation systems. • A systematic analysis is carried out to evaluate these controls for US homes. • Switchable insulation systems can save up to 88% of heating/cooling energy needs. This paper summarizes the main findings for evaluating the effectiveness of simplified and advanced control strategies to operate switchable insulation systems applied to the attic of US residential buildings. Specifically, the evaluation analysis is performed for five US representative climates to determine the performance of several control options for dynamic insulation systems to minimize the heating and cooling energy end-uses for US homes. The control strategies considered include scheduled settings, temperature-based rule sets, and optimal control schemes. The comparative analysis results clearly indicate that the switchable insulation systems even when only applied to attics have significant potentials in reducing the cooling energy use of US residential homes especially those located in mild climates. Even when operated with simplified controls such as time-scheduled controls and temperature-based rule-sets, dynamic insulations are capable of providing substantial energy savings. In particular, controls using rules based on mean air and sol-air temperatures result in cooling energy savings ranging from 8% to 43% for all US climates. When optimal controls are used to operate attic dynamic insulation systems, up to 40% additional savings in cooling energy can be achieved compared to the best simplified controls at least when the building is located in Golden, CO. [ABSTRACT FROM AUTHOR]

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

• A retrofit selection strategy employing economic and environmental decision criteria was proposed. • Building energy retrofits were evaluated through a life cycle thinking approach. • Retrofits with operational emissions savings may not be beneficial when considering life cycle impacts. • Energy mix and the heating system of the house greatly impact the effectiveness. • Retrofit selection changes with stakeholder priorities on environment and economics. Improving the energy performance of buildings has been a much-discussed topic over the past few decades. With the current focus on climate change mitigation, emissions reduction has also come to the forefront of this discussion. Retrofitting is an option to improve the energy and emissions performance of buildings. However, in the residential building stock, retrofit planning for existing buildings faces many complexities due to variations in climatic conditions and macro-environment as well as the presence of multiple stakeholder groups. Thus, in identifying solutions, it is necessary to take a holistic perspective that covers these different dimensions. In this paper, commonly used building energy retrofits were evaluated through a life cycle thinking approach. The performance of various retrofit options applicable for single family detached housing were evaluated using the HOT2000 energy simulation software package under the varying climatic conditions and energy supply scenarios across Canada. The retrofits were evaluated in terms of the additional investment, energy use and cost reduction achieved over the life cycle, and life cycle emissions reduction. The findings indicate that the provincial energy mix and the heating system of the house (i.e. electric or natural gas) play a major role in determining the effectiveness of a retrofit, and this "effectiveness" changes at different stakeholder levels. However, not all retrofits that reduce emissions make economic sense and vice versa when life cycle thinking comes into play. The findings will be useful for building owners and occupants as well as for policy developers and other decision makers interested in demand side management. [ABSTRACT FROM AUTHOR]

• A methodology was represented for calibrating the building energy performance model. • Accurate calibration was achieved on the model even with the short-term measurement. • The calibration process was utilized the MBE- CVRMSE and obtained an enhanced accuracy. • The HDD and CDD was applied in the absence of the real weather data. • The accurate model also provides the opportunity to trail the systems' performance. The calibration process has an excellent advantage, especially for large-scale projects that manage the potentially complex energy performances of various building systems. It also provides great advantages when the annual real-time measurements are not available since the created model can be calibrated with short-term measurements to obtain an accurate annual energy performance. This paper presents a methodology for creating an energy performance model based on a calibration process of a large-scale residential building incorporating heating and cooling energy consumptions. The main purpose is to calibrate the building energy model by utilizing mean bias error (MBE) and coefficient of variation of root-mean-squared error (CVRMSE) indices and obtain the annual building-energy performance with enhanced accuracy. Furthermore, two novel approaches were developed. The first is to provide accurate weather data in the absence of real weather data by taking advantage of available data for heating degree days (HDDs) and cooling degree days (CDDs). The second is to provide accuracy on the collected data of measurements by taking advantage of the predicted data of short term measurements. A methodology is evolved to calibrate the building model by using real-time short-term monitored data from the building. The methodology consists of four main steps and further sub-steps. Modeling, the first step, covers the collection of input data and the development of the model stages. Measurements, the second step, covers the process of data collection for calibration. Improvements for calibration represent the third step, where different versions of the model are developed by changing the input parameters of the model within the defined ranges of variation (ROV). Then, the results of the obtained versions are compared with the real-time measurements, and MBE and CVRMSE values for each version calculated to examine the model's accuracy. Finally, when the model is considered as calibrated, the simulation is run to obtain the annual energy performance of the building for better precision. The results in the model run here show the monthly MBE and CVRMSE values for the initial version to be 15.12% and 17.19%, respectively. After applied strategies, these values are improved according to the calibration criteria defined by ASHRAE to −2.76% and 8.40% respectively, which is considered as calibrated. Overall, it is usually hard and costly to track the real-time energy consumptions of buildings for a long period. Annual building energy consumptions can be obtained accurately by calibrating the building model with the short-term measurements. An accurate model gives the opportunity to trial the performance of each building system. [ABSTRACT FROM AUTHOR]

• The types and benefits of occupancy-based temperature controls for residential buildings are reviewed. • A systematic analysis approach is performed for a wide range of temperature controls specific to Saudi households. • Smart occupancy-controls can save on average 36% of annual energy consumption for a typical KSA household. The paper describes the potential energy efficiency and demand response benefits of occupancy-based temperature controls applicable to residential buildings for the Kingdom of Saudi Arabia (KSA). Specifically, various spatial and temporal temperature controls are evaluated to account for spatial and temporal occupancy patterns associated to typical living styles of Saudi households. The analysis results show that the benefits of occupancy-based temperature settings can be significant when at least two thermal zones controlled by different thermostats exist within the same housing unit. Specifically, occupancy-based thermostat settings can save up to 38.7% of total annual electricity consumption for a dwelling located in Riyadh. Moreover, when the indoor temperature settings are adjusted spatially, a reduction of up to 34.7% in peak demand can result for most KSA regions. Using a bottom-up analysis approach, it is found that when scaling up to the entire KSA housing stock, the adoption of smart thermostats has the potential to reduce annual electricity use by 48 TWh/year or over 30% of the national residential sector energy consumption. [ABSTRACT FROM AUTHOR]

A strong correlation exists between occupant behaviour and space heating energy use. In particular, the occupancy status (e.g., daytime absence) is known to have a significant influence on residential heating load profiles, as well as on cumulative heating energy consumption. In the literature, many occupancy models have been utilised to predict occupancy profiles of individual dwellings as part of the larger residential building stock. However, none of the existing models consider diversity associated with occupancy-integrated archetypes to generate high-temporal resolution heating load profiles. The current paper uses Time Use Survey (TUS) data to develop a high-temporal resolution residential building occupancy model. The key feature of the proposed model, implemented using MATLAB, is the ability to generate stochastic occupancy time-series data for national population subgroups characterised by specific occupancy profiles. It is shown that the results are capable of closely approximating data available from TUS. The developed model can be applied to improve the quality of modelled high-temporal resolution heating load profiles for generic building stock characterised by population subgroups represented by different occupancy-integrated archetypes. A case study is performed on a building stock sample located in London, UK. The developed occupancy model has been implemented in MATLAB and is available for download. [ABSTRACT FROM AUTHOR]

• A replicable methodology for identifying reference buildings is presented. • The k -means clustering method is applied to the energy performance certificate database. • To illustrate the methodology, an EPC database including 13,701 offices is used. • Sixteen clusters and corresponding representative offices are identified. • Representative offices can be used for cost-optimal retrofitting analysis of the entire stock. A large number of buildings must be evaluated to formulate energy retrofitting policies for existing building stock. In this context, it is crucial to identify reference buildings that can effectively represent the entire stock, since such buildings can then be used to assess the individualized cost-effectiveness of retrofitting measures. This paper presents a novel approach for identifying and defining a set of reference buildings by applying the k -means clustering method to energy performance certificate databases. To this end, a four-step methodology has been envisaged. First, an energy performance certificate database is prepared and variables that have an impact on energy consumption are pre-selected. Selected data are then pre-processed. Next, the k -means clustering method is applied. Finally, the resulting cluster centroids are used to identify the closest energy performance certificates in the database, in other words, the representative buildings that will then be used for cost-optimal retrofitting analysis. The methodology is illustrated using the energy performance certificate database managed by the Catalan Institute of Energy (ICAEN), which includes a sample of 13,701 offices. Due to the large number of missing values in the database, the k -means clustering algorithm was finally performed over 6,083 energy performance certificates. Seven representative office blocks and offices in industrial buildings and nine representative offices in residential buildings were identified. The results establish the basis for supporting strategic decision-making for energy saving retrofit interventions in existing Spanish offices. [ABSTRACT FROM AUTHOR]

Many studies have investigated different aspects in the decarbonisation of the European housing stock. However, a comprehensive quantitative analysis of the literature on the diffusion of energy efficiency technologies is still missing. We conducted a bibliometric analysis to better understand the knowledge base in the field energy efficiency technology diffusion in the European residential building stock. After the scanning and screening process, we identified 954 scientific articles pertinent to this topic. Through a co-citation network analysis, we generated a visual knowledge structure of the field and by the further investigation of the bibliography we were able to synthesize the state-of-the-art and answer to our initial research questions. Results of the co-citation network show a scattered and fragmented field in many domains. The descriptive analysis highlights this fragmentation, especially on a cross-country level among EU country members. Findings from this study contribute to map the scientific knowledge base in relation to technology diffusion in European residential building projects, identify relevant topic areas, visualize the links between the topics, as well as to recognize research gaps and opportunities. The methodology utilized in this paper proved to be viable approach to map and characterize the knowledge base within a field and can, therefore, be replicated in upcoming studies with analogous ambitions. [ABSTRACT FROM AUTHOR]

• The same building geometries and the same thermal properties of building envelope for different seven climatic cities were assumed. • Energy conservation effect including saving amount and saving ratio were discussed annually and monthly among seven cities. • The inner mechanism of the difference was revealed from the hourly and daily perspectives through two extremely contrast climatic cities. • Guidance and reference were provided for both standard determination and behavioral energy saving for air conditioning systems. Indoor setting temperature is a key controllable parameter by users, highly impacting the total cooling energy usage. In this paper, the hourly cooling load of residential buildings is simulated for seven cities respectively when the cooling setting temperature (CST) increases by 1°C, and the dissimilarity and internal mechanism of the energy saving effect are discussed and revealed from the hourly and daily perspectives through two extremely contrast climatic cities. The results show that although the higher yearly energy saving amount (ESA) can appear in a hotter city, energy saving effect is all significant in different cities. The ESA in hotter months of hotter cities may not be higher than that in the corresponding months of cooler cities, and the hotter cities have more obvious platform features while the cooler cities have single peak features, and the peak value is much higher than the plateau value. The yearly cooling saving ratio (CSR) is higher in cooler cities because CSR depends on both the hourly CSR and its weightiness, and the proportion of the higher ratio hours in cool cities is larger. This study can provide references for both standard determination and behavioral energy saving for air conditioning systems. [ABSTRACT FROM AUTHOR]