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The management of large enterprises influences their efficiency and profitability. One of the important aspects is the appropriate management of electricity consumption used for production and daily operation. The problem becomes more complicated when you need to manage not one but a large complex of buildings with heterogeneous purposes. In the paper, we examine real-time series data of electrical energy consumption in a complex of heterogeneous buildings, including offices and warehouses, using time series analysis methods such as the Holt–Winters model and ARIMA/SARIMA model, and neural networks (Deep Neural Network, Recurrent Neural Network, and Long Short-Term Memory). Experimental research was performed on a dataset obtained from an energy consumption meter placed in the building complex, built in different periods, and equipped with a variety of automation devices. The data were collected over a period of four years 2018–2021 in the form of time series. Results show that classic models are good at predicting energy consumption in the mentioned type of buildings. The ARIMA model gave the best results—for buildings characterized by seasonality and trends the forecasts were almost perfect with actual values. [ABSTRACT FROM AUTHOR]

Increasing building energy consumption has led to environmental and economic issues. Energy demand prediction (DP) aims to reduce energy use. Machine learning (ML) methods have been used to improve building energy consumption, but not all have performed well in terms of accuracy and efficiency. In this paper, these methods are examined and evaluated for modern building (MB) DP. [ABSTRACT FROM AUTHOR]

In this paper, the window-opening behavior in a three-star green building with an operation mark in Ningbo was investigated. Four single offices facing south were selected, and the measurement lasted 20–40 days in the cooling season. An analysis of the relationship between window use and environmental factors was assessed by monitoring the occupancy state, the window action and window state, the time, and the temperature and humidity. A statistical analysis method was conducted to reveal the similarities and differences in window use among different occupants. The main findings were as follows: The window adjustment behaviors of different people vary significantly. In terms of adjustment time, there are two modes of behaviors. In addition, the occupancy state had a great impact on window action. Moreover, some people prefer to open the windows in the morning and close the windows at departure time, However, some of them prefer to open the windows at departure time and close the windows at the arrival time. Some irrational window opening behaviors were found in this research. Through correlation analysis, it was shown that the longer time the occupants were in the office, the higher window-opening duration and window-opening frequency would be. If the window was closed at arrival time, the total opening duration of window was significantly reduced. Also, window opening duration and closing duration are proportional to each other. With the help of principal component analysis (PCA) of the 12 features that affected window adjustment, the correlation between the window opening behaviors and the features could be clearly illustrated. A stochastic model of window-opening behavior based on logistics regression and uncertainty analysis was used in this paper. The cooling energy consumption of the stochastic model is 99.9% higher than the energy consumption generated by a fixed number of air changes, and the average energy consumption exceeds the fixed value by more than 21%. The findings of this study have certain guiding significance for promoting energy conservation by occupants' behaviors in green buildings in this region. [ABSTRACT FROM AUTHOR]

This paper presents the challenges of increasing the energy efficiency investments in European Union (EU) residential buildings in the context of achieving climate neutrality by 2050. The paper presents the results of the PRIMES buildings model in key energy policy applications to support cost-effective and fair policy making in buildings across Europe. The model covers, in detail, the building sector for all the EU Member States (MS), segmenting the buildings into many categories. The approach proposed includes non-market barriers in conventional microeconomic modelling, which combined with idiosyncratic preferences can capture poor energy efficiency choices and still represent rational behaviours. The model includes a detailed portrayal of policies specific to the sector, comprising economic and regulatory policies as well as institutional measures. The results of the model show that the removal of non-market barriers is of great importance in reducing energy consumption and increasing both the pace and the depth of renovation investment. However, the institutional measures alone are not enough to induce energy efficiency improvement to the scale required to achieve the climate neutrality objectives. Economic (i.e., subsidies) or regulatory measures (i.e., energy performance standards) are also required to decrease emissions and energy consumption in buildings and the paper compares different configurations thereof. The optimum policy mix obviously derives from a compromise among various aims including the cost-effectiveness of the policy budget and the distributional impacts across building and consumer types. [ABSTRACT FROM AUTHOR]

The goal of this work is to give a full review of how machine learning (ML) is used in thermal comfort studies, highlight the most recent techniques and findings, and lay out a plan for future research. Most of the researchers focus on developing models related to thermal comfort prediction. However, only a few works look at the current state of adaptive thermal comfort studies and the ways in which it could save energy. This study showed that using ML control schemas to make buildings more comfortable in terms of temperature could cut energy by more than 27%. Finally, this paper identifies the remaining difficulties in using ML in thermal comfort investigations, including data collection, thermal comfort indices, sample size, feature selection, model selection, and real-world application. [ABSTRACT FROM AUTHOR]

Although the energy and cost benefits for retrofitting existing buildings are promising, several challenges remain for accurate measurement and verification (M&V) analysis to estimate these benefits. Due to the rapid development in advanced metering infrastructure (AMI), data-driven approaches are becoming more effective than deterministic methods in developing baseline energy models for existing buildings using historical energy consumption data. The literature review presented in this paper provides an extensive summary of data-driven approaches suitable for building energy consumption prediction needed for M&V applications. The presented literature review describes commonly used data-driven modeling approaches including linear regressions, decision trees, ensemble methods, support vector machine, deep learning, and kernel regressions. The advantages and limitations of each data-driven modeling approach and its variants are discussed, including their cited applications. Additionally, feature engineering methods used in building energy data-driven modeling are outlined and described based on reported case studies to outline commonly used building features as well as selection and processing techniques of the most relevant features. This review highlights the gap between the listed existing frameworks and recently reported case studies using data-driven models. As a conclusion, this review demonstrates the need for a flexible M&V analysis framework to identify the best data-driven methods and their associated features depending on the building type and retrofit measures. [ABSTRACT FROM AUTHOR]

For heritage buildings, energy-efficient retrofitting cannot be applied with the same range of possibilities as with existing buildings. Applying such improvements to heritage buildings can be challenging due to their historic and/or cultural significance and non-standard construction methods. This paper reviews the technical challenges and potential of applying energy efficient retrofit elements in heritage buildings. The retrofitting measures reviewed are draught-proofing, windows, insulation, ventilation, heating, solar photovoltaics and phase change materials. It is possible to significantly reduce energy use in heritage buildings with such retrofits. However, there is no universal way to apply energy-efficient retrofitting in heritage buildings, which is apparent in the literature, where case studies are prevalent. [ABSTRACT FROM AUTHOR]

Buildings are responsible for around 30 to 40% of the energy demand and greenhouse gas (GHG) emissions in European countries. Building stock energy models (BSEMs) are an established method to assess the energy demand and environmental impact of building stocks. Spatial analysis of building stock energy demand has so far been limited to cases where detailed, building specific data is available. This paper introduces two approaches of using synthetic building stock energy modelling (SBSEM) to model spatially distributed synthetic building stocks based on aggregate data. The two approaches build on different types of data that are implemented and validated for two separate case studies in Ireland and Austria. The results demonstrate the feasibility of both approaches to accurately reproduce the spatial distribution of the building stocks of the two cases. Furthermore, the results demonstrate that by using a SBSEM approach, a spatial analysis for building stock energy demand can be carried out for cases where no building level data is available and how these results may be used in energy planning. [ABSTRACT FROM AUTHOR]

Applications of the Internet of Things (IoT) are rapidly utilized in smart buildings and smart cities to reduce energy consumption. This advancement has caused a knowledge gap in applying IoT effectively by experts in the built environment to achieve energy efficiency. The study aims to provide an extensive review of IoT applications for energy savings in buildings and cities. This study contributes to the field of IoT by guiding and supporting built environment experts to utilize IoT technologies. This paper performed a thorough study using a systematic review that covered an overview of IoT concepts, models, applications, trends and challenges that can be encountered in the built environment. The findings indicated limitations in developing IoT strategies in buildings and cities by professionals in this field due to insufficient comprehension of technologies and their applied methods. Additionally, the study found an indefinite implementation and constraints on using IoT when integrated into the built environment. Finally, the study provides critical arguments and the next steps to effectively utilize IoT in terms of energy efficiency. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy sources creates a challenge for the stability of current power systems due to their intermittent and stochastic nature. This paper presents the field results of an efficient demand response solution for controlling and adjusting the electric demand of buildings in an energy district through the activation of their thermal mass while respecting the occupants' thermal comfort constraints. This multilevel control approach aims to support grid flexibility during peak times by constraining the energy exchange with the grid and increasing the self-consumption of the district. The results show a great potential for increasing the self-consumption up to 37% for offices, as well as improving the indoor environment, based on real data collected from a case study in Greece. [ABSTRACT FROM AUTHOR]

Oversimplifying occupant behaviour using static and standard schedules has been identified as a limitation of building energy simulation tools. This paper describes the use of hierarchical cluster analysis to establish the most typical indoor temperature profiles of Albanian dwellings based on monitored indoor temperatures in winter and summer, along with building and occupant surveys undertaken in 49 randomly selected dwellings in Tirana. Three statistically different profiles were developed for each summer and winter, indicating that homes are used in different ways, as well as revealing possible comfort requirements. Furthermore, statistical analysis was undertaken to determine the strength of the association between the clusters and contextual factors related to the building, household, and occupancy. A statistically significant association was found between the presence of children and the clusters in winter, suggesting that families with dependents use more energy. Building-related factors including building type, building age, and wall insulation were found to be statistically significantly associated with clusters in summer. These profiles could provide more accurate outcomes of energy consumption of Albanian homes and energy savings from retrofits. They could also facilitate the development of low-energy strategies and policies for specific households. [ABSTRACT FROM AUTHOR]

This paper presents an analysis to determine the economic, energetic, and environmental benefits that could be obtained from the implementation of a combined solar-power organic Rankine cycle (ORC) with electric energy storage (EES) to supply electricity to several commercial buildings including a large office, a small office, and a full service restaurant. The operational strategy for the ORC-EES system consists in the ORC charging the EES when the irradiation level is sufficient to generate power, and the EES providing electricity to the building when there is not irradiation (i.e., during night time). Electricity is purchased from the utility grid unless it is provided by the EES. The potential of the proposed system to reduce primary energy consumption (PEC), carbon dioxide emission (CDE), and cost was evaluated. Furthermore, the available capital cost for a variable payback period for the ORC-EES system was determined for each of the evaluated buildings. The effect of the number of solar collectors on the performance of the ORC-EES is also studied. Results indicate that the proposed ORC-EES system is able to satisfy 11%, 13%, and 18% of the electrical demand for the large office, the small office and the restaurant, respectively. [ABSTRACT FROM AUTHOR]

A Virtual energy assessment (VEA) refers to the assessment of the energy flow in a building without physical data collection. It has been occasionally conducted before the COVID-19 pandemic to residential and commercial buildings. However, there is no established framework method for conducting this type of energy assessment. The COVID-19 pandemic has catalysed the implementation of remote energy assessments and remote facility management. In this paper, a novel framework for VEA is developed and tested on case study buildings at the University of Melbourne. The proposed method is a hybrid of top-down and bottom-up approaches: gathering the general information of the building and the historical data, in addition to investigating and modelling the electrical consumption with artificial neural network (ANN) with a projection of the future consumption. Through sensitivity analysis, the outdoor temperature was found to be the most sensitive (influential) parameter to electrical consumption. The lockdown of the buildings provided invaluable opportunities to assess electrical baseload with zero occupancies and usage of the building. Furthermore, comparison of the baseload with the consumption projection through ANN modelling accurately quantifies the energy consumption attributed to occupation and operational use, referred to as 'operational energy' in this paper. Differentiation and quantification of the baseload and operational energy may aid in energy conservation measures that specifically target to minimise these two distinct energy consumptions. [ABSTRACT FROM AUTHOR]

Increased use of energy in buildings and HVAC systems requires advanced control schemes like model-based control to improve energy efficiency, which in turn requires accurate thermodynamic models of buildings. The Resistive-Capacitive (RC) method is a popular and versatile approach for thermal modeling of buildings. Despite this, it is not easy to find practical solutions of implementation of the RC method. It is the goal of this paper to clarify the RC method and demonstrate simple implementation of this method, especially for multi-zone buildings, which have more potential for energy savings from use of model-based control. This paper provides two contributions. First is a detailed explanation of the RC method, focusing on its use for developing a structure of a model and first-principles approach for estimation of parameters of a model. Second is a demonstration of an algorithm that enables automatic development of the structure of a model from basic information about a building (layout, construction elements) and its combination with data-based parameter estimation. Use of the algorithm is presented with a case-study on industrial multi-zone building, for which such a grey-box model is developed and analyzed. The resulting model is rapidly developed and used in a simulation with the measured data. The outputs of the model are compared with the measured temperatures and they show good fit. [ABSTRACT FROM AUTHOR]

In this paper, the energy performance of a university campus in a tropical climate is assessed, and four mixed classroom buildings are compared using benchmarking methods based on simple normalization: the classic Energy Use Intensity (EUI), end-used based EUI, and people-based EUI. To estimate the energy consumption of the case studies, building energy simulations were carried out in EnergyPlus using custom inputs. The analysis found that buildings with more classroom spaces presented higher energy consumption for cooling and lighting than others. In comparison, buildings with a greater percentage of laboratories and offices exhibited higher energy consumption for plug loads. Nevertheless, differences were identified when using the people-based EUI since buildings with larger floor areas showed the highest values, highlighting the impact of occupant behavior on energy consumption. Given the fact that little is known about a benchmark range for university campuses and academic buildings in hot and humid climates, this paper also provides a comparison against the EUIs reported in the literature for both cases. In this sense, the identified range for campuses was 49–367 kWh/m 2 /year, while for academic buildings, the range was 47–628 kWh/m 2 /year. Overall, the findings of this study could contribute to identifying better-targeted energy efficiency strategies for the studied buildings in the future by assessing their performance under different indicators and drawing a benchmark to compare similar buildings in hot and humid climates. [ABSTRACT FROM AUTHOR]

Small commercial buildings, or those comprising less than 50,000 square feet of floor area, represent 94% of U.S commercial buildings by count and consume approximately 8% of the nation's primary energy; as such, they represent a largely unexploited opportunity for energy savings. Small commercial buildings also represent a large economic market—the National Institute of Building Sciences (NIBS) estimated the small commercial retrofit market at USD 35.6 billion. Despite the prominence of small commercial buildings and the economic opportunity for energy retrofits, many energy efficiency programs focus on large commercial buildings, and create efficiency solutions that do not meet the needs of the small commercial market. This paper presents an analysis of 34 small commercial case study projects that implemented energy efficiency retrofits. This paper contributes to the existing building retrofit body of knowledge in the following ways: (1) it identifies the decision criteria used by small commercial building stakeholders that decided to complete an energy retrofit; (2) it identifies the most commonly implemented efficiency measures in small commercial buildings, and discusses why this is the case; and (3) it provides empirical evidence about the efficacy of installing single energy efficiency measures (EEMs) compared to packages of EEMs in small commercial buildings by reporting verified energy savings. To the authors' knowledge, this paper is the first to catalog decision criteria and energy savings for the existing small commercial buildings market, and this research illustrates that small commercial building decision-makers seem most motivated to retrofit their spaces by energy cost savings and operational concerns. Furthermore, small commercial building decision-makers opted to implement single-system retrofits in fifteen (15) of the thirty-four cases studied. Finally, this research documents the improved savings, in the small commercial buildings market, associated with a more integrated package of EEMs compared to a single-system approach, achieving approximately 10% energy savings for a single-system approach and more than 20% energy savings for integrated approaches. These savings translate to CO2 savings of 1,324,000 kgCO2/year to 2,647,000 kgCO2/year, respectively, assuming small commercial buildings are retrofit at a rate of 0.95% of the stock annually. [ABSTRACT FROM AUTHOR]

The building sector continues to register a significant rise in energy demand and environmental impact, notably in developing countries. A considerable proportion of this energy is required during the operational phase of buildings for interior heating and cooling, leading to a necessity of building performance improvement. A holistic approach in building design and construction represents a step to moderate construction costs in conjunction with reduced long-term operating costs and a low impact on the environment. The present paper presents an experimental evaluation of the energy efficiency of a building under real climate conditions; the building, which represents a holistically designed modular laboratory, is located in a moderate continental temperate climate, characteristic of the south-eastern part of the Pannonian Depression, with some sub-Mediterranean influences. Considerations for the holistic design of the building, including multi-object optimization and integrated design with a high regard for technology and operational life are described. The paper provides a genuine overview of the energy efficiency response of the building during six months of operational use through a monitored energy management system. The energetic analysis presented in the paper represents an intermediary stage as not all the energetic users were installed nor all the energetic suppliers. However, the results showed a reliable thermal response in the behaviour of recycled-PET thermal wadding used as insulation material in the building and for the intermediary stage in which the building has only secondary energy users, the energetic balance proves its efficiency, keeping the buffer stock of energy high values over 90%. [ABSTRACT FROM AUTHOR]

The building sector is the largest consumer of energy, but there are still major scientific challenges in this field. The façade, being the interface between the exterior and interior space, plays a key role in the energy efficiency of a building. In this context, this paper focuses on a ventilated bioclimatic wall for nearly zero-energy buildings (NZEB). The aim of this study is to investigate an experimental setup based on a hot box for the characterization of the thermal performances of the ventilated wall. A specific ventilated prototype and an original thermal metrology are developed. This paper presents the ventilated prototype, the experimental setup, and the experimental results on the thermal performances of the ventilated wall. The influence of the air space thickness and the air flow rate on the thermal performances of the ventilated wall is studied. [ABSTRACT FROM AUTHOR]

Targeting existing residential buildings for retrofit improvement presents significant prospects for global reduction of energy-usage and carbon footprints. Energy consumption of the existing single-family building in the hot-humid climate zone needs to be targeted for improvement due to their potential energy-savings and sizeable market share. This paper proposes and evaluates energy savings and cost-effectiveness of a whole building retrofit package for single-family residential buildings built between 1950 and 1970. The study outlined a survey conducted using the clustering data mining technique on Florida Single-Family Residential (SFR) homes to determine the essence of the building envelope, patterns of construction, and Heating, Ventilation, and Air-Conditioning (HVAC) systems. The evaluation of the energy efficiency measures (EEMs) effectiveness is performed utilizing Autodesk Revit and a Six-Step modeled framework. This framework consists of baseline model development, validation of the model with an actual case study building, identification of potential EMMs, evaluation of EEMs individually and incorporating the selected EMMs into retrofit package and maximizing the energy-saving and cost-effectiveness of the proposed retrofit package. The study develops proposed retrofit improvement package detailing replacement & improvement EEMs, implementation cost, annual energy savings (kWh), cost-saving ($), and payback period (years) for each individual EEM as well as the combined/total energy improvement package. The paper further explored the usage of solar photovoltaics (PV) energy generation options to offset the remaining energy-use after the implementation of the proposed retrofit package. [ABSTRACT FROM AUTHOR]

With the continuous implementation of a plan for reconstruction of "Beautiful Countryside" in China, the rural environment and appearance of rural houses have been significantly improved. However, those houses in cold areas of China have great trouble with indoor temperature and heating-related energy consumption. After investigating the current situation of the layout, building envelope, indoor temperature, and energy consumption of the rural houses renovated by the plan of "Beautiful Countryside" in Shandong Province, this paper puts forward the improvement measures of raising indoor temperature and reducing energy consumption. On this basis, a typical rural house was selected, and DesignBuilder was utilized to simulate the effects before and after the application of different renovation measures for this house. The results show that the main way to raise indoor temperature and reduce energy consumption is to improve the thermal insulation performance of the building envelope, including renovation of the roof, exterior walls, doors and windows, and attached sunspace. In addition, combined with the achievements of "Beautiful Countryside" reconstruction, this paper shall propose specific renovation practices which are suitable for different rural houses. Based on the level of economic development in rural areas, it also puts forward some feasible renovation paths for different rural areas, and further provides references for other areas to carry out relevant work in the future. [ABSTRACT FROM AUTHOR]

The paper overviews the current energy demand trends in the building sector for the Arab region using reported historical energy consumption. Moreover, the paper describes the current energy efficiency policies and regulations for all the Arab countries specific to both residential and commercial buildings. Finally, the paper evaluates potential benefits for large-scale energy efficiency programs specific to new and existing building stocks within the Arab region using a bottom-up analysis approach. The analysis of the available energy consumption for all the Arab countries has shown that the Arab region presents a significant variation in energy consumption levels between its sub-regions and countries. Indeed, the Arab region includes oil-producing countries such as Saudi Arabia with the largest energy use per capita in the World with over 9000 kWh/person of electricity used annually in buildings. However, the same region has the least developed countries such as Sudan and Yemen with the lowest energy use per capita in the World with barely 100 kWh/person/year of electrical consumption. The review of the existing regulations has indicated that several Arab countries have not implemented any energy efficiency codes and standards for building envelope, lighting, heating and cooling equipment, and appliances. A cost-effectiveness analysis has indicated that the Arab region can incur significant benefits in upgrading the energy efficiency of its new and existing buildings especially its households. Specifically, the adoption and the enforcement of stringent energy efficiency codes for new residential and commercial buildings can result in a reduction of 12.7 TWh/year in final annual energy consumption for the Arab region. Moreover, retrofit programs targeting existing buildings can save up to 470 TWh or a third of the building sector final energy consumption per year after 2030. Combining comprehensive energy efficiency requirements for new buildings and extensive retrofit programs for existing buildings would reduce the total final energy consumption of the building sector in the Arab region by 600 TWh by 2030 and by 900 TWh by 2050 if all the energy programs start to be implemented by 2020. [ABSTRACT FROM AUTHOR]

Interpretable and scalable data-driven methodologies providing high granularity baseline predictions of energy use in buildings are essential for the accurate measurement and verification of energy renovation projects and have the potential of unlocking considerable investments in energy efficiency worldwide. Bayesian methodologies have been demonstrated to hold great potential for energy baseline modelling, by providing richer and more valuable information using intuitive mathematics. This paper proposes a Bayesian linear regression methodology for hourly baseline energy consumption predictions in commercial buildings. The methodology also enables a detailed characterization of the analyzed buildings through the detection of typical electricity usage profiles and the estimation of the weather dependence. The effects of different Bayesian model specifications were tested, including the use of different prior distributions, predictor variables, posterior estimation techniques, and the implementation of multilevel regression. The approach was tested on an open dataset containing two years of electricity meter readings at an hourly frequency for 1578 non-residential buildings. The best performing model specifications were identified, among the ones tested. The results show that the methodology developed is able to provide accurate high granularity baseline predictions, while also being intuitive and explainable. The building consumption characterization provides actionable information that can be used by energy managers to improve the performance of the analyzed facilities. [ABSTRACT FROM AUTHOR]

Buildings account for 40% of the energy consumption and 31% of the CO2 emissions in the United States. Energy retrofits of existing buildings provide an effective means to reduce building consumption and carbon footprints. A key step in retrofit planning is to predict the effect of various potential retrofits on energy consumption. Decision-makers currently look to simulation-based tools for detailed assessments of a large range of retrofit options. However, simulations often require detailed building characteristic inputs, high expertise, and extensive computational power, presenting challenges for considering portfolios of buildings or evaluating large-scale policy proposals. Data-driven methods offer an alternative approach to retrofit analysis that could be more easily applied to portfolio-wide retrofit plans. However, current applications focus heavily on evaluating past retrofits, providing little decision support for future retrofits. This paper uses data from a portfolio of 550 federal buildings and demonstrates a data-driven approach to generalizing the heterogeneous treatment effect of past retrofits to predict future savings potential for assisting retrofit planning. The main findings include the following: (1) There is high variation in the predicted savings across retrofitted buildings, (2) GSALink, a dashboard tool and fault detection system, commissioning, and HVAC investments had the highest average savings among the six actions analyzed; and (3) by targeting high savers, there is a 110–300 billion Btu improvement potential for the portfolio in site energy savings (the equivalent of 12–32% of the portfolio-total site energy consumption). [ABSTRACT FROM AUTHOR]

A building energy performance gap can be illustrated as the difference between the theoretical (methodologically defined) and the actual energy consumption. In EU countries, Energy Performance Certificates are issued when buildings are constructed, sold, or leased. This information is the first step in order to evaluate the energy performance of the building stock. In Serbia, when issuing an energy certificate, the adopted national methodology recognizes only energy consumption for heating. The main purpose of this paper is to evaluate the energy gap and estimate the relevance of an Energy Performance Certificate to meet the national energy efficiency or carbon target. An Energy Performance Certificate determines the theoretical residential and commercial building energy efficiency or its "design intent". This research stresses the necessity of measuring and achieving reductions in actual energy consumption through system regulation and consumers' self-awareness in buildings. The research compares the performance of the building stock (135) that is connected to the District Heating System (DHS), with its own integrated heat meter, to Individual Gas Boiler (IGB) systems (18), in the city of Novi Sad, Serbia, built after 2014. For the purpose of comparing energy consumption, 16 buildings were selected that are very similar in terms of design, operation, and location. The data used are derived from metered consumption data, official evidence of city service companies, and Energy Performance Certificates of the considered buildings. We have determined that IGB systems have a much wider specific annual performance gap (11.19–101 kWh/m2a) than the buildings in the DHS (3.16–18.58 kWh/m2a). [ABSTRACT FROM AUTHOR]

For decades, among other industries, the construction sector has accounted for high energy consumption and emissions. As the energy crisis and climate change have become a growing concern, mitigating energy usage is a significant issue. The operational and end of life phases are all included in the building life cycle stages. Although the operation stage accounts for more energy consumption with higher carbon emissions, the embodied stage occurs in a time-intensive manner. In this paper, an attempt has been made to review the existing methods, aiming to lower the consumption of energy and carbon emission in the construction buildings through optimizing the construction processes, especially with the lean construction approach. First, the energy consumption and emissions for primary construction materials and processes are introduced. It is followed by a review of the structural optimization and lean techniques that seek to improve the construction processes. Then, the influence of these methods on the reduction of energy consumption is discussed. Based on these methods, a general algorithm is proposed with the purpose of improving the construction processes' performance. It includes structural optimization and lean and life cycle assessments, which are expected to influence the possible reduction of energy consumption and carbon emissions during the execution of construction works. [ABSTRACT FROM AUTHOR]

The paper provides a methodology for the optimal control of heating, ventilation, and air conditioning (HVAC) systems used in public buildings, with the purpose of obtaining high comfort and safety standards along with energy efficiency. The combination of the two concurrent objectives of minimizing energy use and guaranteeing high standards of occupant comfort is obtained by means of multi-objective optimization, in which a comfort model is combined along with a dynamic energy model of the building. The use of dynamic setpoints for the HVAC and the inclusion of comfort indicators represent a step forward, compared to the current design and operation procedures suggested by technical standards. The utilization of the proposed methodology is tested with reference to a case study, represented by an academic building used by the University of Pisa for educational purposes, whose extensive and variable occupancy can help to emphasize the importance of comfort in the operation of HVAC systems in different climatic conditions and with different occupancy profiles. We show how this optimization brings interesting results in terms of energy-saving (up to 30%), obtaining an increased comfort level (of more than 25%) compared to the operating conditions suggested by technical standards. [ABSTRACT FROM AUTHOR]

In the rapidly growing economies of Southeast Asia, energy consumption and energy costs in buildings continue to increase. Over the past decade, energy consumption from the commercial building sector in Thailand has increased at an average of 4% per annum and currently represents over 30% of total electricity consumption, second only to the industrial sector. Buildings that exist today will continue to represent most of both energy and greenhouse gas (GHG) emissions from the built environment, with newly constructed buildings representing only a small additional portion. This paper analyzes the environmental, technical, and financial characteristics of energy efficiency retrofit activities in commercial buildings in Thailand through detailed case studies of forty-two projects undertaken over the past 8 years. Our findings suggest that retrofits provide significant opportunities to reduce energy use, energy costs, and GHG emissions while also validating the economic feasibility of investments into such retrofit activities. Through this detailed analysis of past retrofit projects in Thailand, we found that the marginal abatement costs (MAC) relating to the key energy conservation measures (ECM) implemented within these retrofit projects all have negative costs. However, although these findings demonstrate positive economics and should be sufficient to instigate widespread adoption, in reality, this is not taking place. It is evident that greater public policy and leadership are needed to stimulate growth in the building retrofit sector to take advantage of the opportunities and benefits that building retrofits offer. [ABSTRACT FROM AUTHOR]

The integration of multi-energy systems to meet the energy demand of buildings represents one of the most promising solutions for improving the energy performance of the sector. The energy flexibility provided by the building is paramount to allowing optimal management of the different available resources. The objective of this work is to highlight the effectiveness of exploiting building energy flexibility provided by thermostatically controlled loads (TCLs) in order to manage multi-energy systems (MES) through model predictive control (MPC), such that energy flexibility can be regarded as an additional energy source in MESs. Considering the growing demand for space cooling, a case study in which the MPC is used to satisfy the cooling demand of a reference building is tested. The multi-energy sources include electricity from the power grid and photovoltaic modules (both of which are used to feed a variable-load heat pump), and a district cooling network. To evaluate the varying contributions of energy flexibility in resource management, different objective functions—namely, the minimization of the withdrawal of energy from the grid, of the total energy cost and of the total primary energy consumption—are tested in the MPC. The results highlight that using energy flexibility as an additional energy source makes it possible to achieve improvements in the energy performance of an MES building based on the objective function implemented, i.e., a reduction of 53% for the use of electricity taken from the grid, a 43% cost reduction, and a 17% primary energy reduction. This paper also reflects on the impact that the individual optimization of a building with a multi-energy system could have on other users sharing the same energy sources. [ABSTRACT FROM AUTHOR]

The construction sector is a great contributor to global warming both in new and existing buildings. Minimum energy buildings (MEBs) demand as little energy as possible, with an optimized architectural design, which includes passive solutions. In addition, these buildings consume as low energy as possible introducing efficient facilities. Finally, they produce renewable energy on-site to become zero energy buildings (ZEBs) or even plus zero energy buildings (+ZEB). In this paper, a deep analysis of the energy use and renewable energy production of a social dwelling was carried out based on data measurements. Unfortunately, in residential buildings, most renewable energy production occurs at a different time than energy demand. Furthermore, energy storage batteries for these facilities are expensive and require significant maintenance. The present research proposes a strategy, which involves rescheduling energy demand by changing the habits of the occupants in terms of domestic hot water (DHW) consumption, cooking, and washing. Rescheduling these three electric circuits increases the usability of the renewable energy produced on-site, reducing the misused energy from 52.84% to 25.14%, as well as decreasing electricity costs by 58.46%. [ABSTRACT FROM AUTHOR]

The trend in energy consumption, with a particular focus on heating and cooling demand, is an issue that is relevant to the promotion of new energy policies and more efficient energy systems. Moreover, heating and cooling energy demand is expected to rise in the next several decades, mainly due to climate change as well as increasing incomes in developing countries. In this context, the building sector is currently a relevant energy-intensive economic sector in Morocco; it accounts for 33% of the country's total energy demand (as the sector with the second highest energy demand, after the transport sector), with the residential sector accounting for 25% and the tertiary sector accounting for 8%. Aiming to reduce energy dependence and promote sustainable development, the Moroccan government recently issued a comprehensive plan to increase the share of renewables and improve energy efficiency. This strategy includes novel thermal building regulations promoted by the Moroccan Agency for Energy Efficiency. This paper analyzes the thermal behavior and heating-cooling energy demand of a residential building located in Tangier (Morocco) as a case example, based on the country's new thermal regulations and considering specific climatological conditions. A comparison with common Moroccan residential buildings as well as with those in nearby countries with similar meteorological conditions but significant differences in terms of energy demand regulation and requirements, such as Spain, is also included. Simulations were carried out using the DesingBuilder and EnergyPlus Software packages. According to the results, the last building thermal regulation requirements in Morocco need to be revised and extended in order to achieve the energy efficiency objectives established by the Moroccan government for 2030. [ABSTRACT FROM AUTHOR]

The construction sector is a great contributor to global warming both in new and existing buildings. Minimum energy buildings (MEBs) demand as little energy as possible, with an optimized architectural design, which includes passive solutions. In addition, these buildings consume as low energy as possible introducing efficient facilities. Finally, they produce renewable energy on-site to become zero energy buildings (ZEBs) or even plus zero energy buildings (+ZEB). In this paper, a deep analysis of the energy use and renewable energy production of a social dwelling was carried out based on data measurements. Unfortunately, in residential buildings, most renewable energy production occurs at a different time than energy demand. Furthermore, energy storage batteries for these facilities are expensive and require significant maintenance. The present research proposes a strategy, which involves rescheduling energy demand by changing the habits of the occupants in terms of domestic hot water (DHW) consumption, cooking, and washing. Rescheduling these three electric circuits increases the usability of the renewable energy produced on-site, reducing the misused energy from 52.84% to 25.14%, as well as decreasing electricity costs by 58.46%. [ABSTRACT FROM AUTHOR]

The trend in energy consumption, with a particular focus on heating and cooling demand, is an issue that is relevant to the promotion of new energy policies and more efficient energy systems. Moreover, heating and cooling energy demand is expected to rise in the next several decades, mainly due to climate change as well as increasing incomes in developing countries. In this context, the building sector is currently a relevant energy-intensive economic sector in Morocco; it accounts for 33% of the country's total energy demand (as the sector with the second highest energy demand, after the transport sector), with the residential sector accounting for 25% and the tertiary sector accounting for 8%. Aiming to reduce energy dependence and promote sustainable development, the Moroccan government recently issued a comprehensive plan to increase the share of renewables and improve energy efficiency. This strategy includes novel thermal building regulations promoted by the Moroccan Agency for Energy Efficiency. This paper analyzes the thermal behavior and heating-cooling energy demand of a residential building located in Tangier (Morocco) as a case example, based on the country's new thermal regulations and considering specific climatological conditions. A comparison with common Moroccan residential buildings as well as with those in nearby countries with similar meteorological conditions but significant differences in terms of energy demand regulation and requirements, such as Spain, is also included. Simulations were carried out using the DesingBuilder and EnergyPlus Software packages. According to the results, the last building thermal regulation requirements in Morocco need to be revised and extended in order to achieve the energy efficiency objectives established by the Moroccan government for 2030. [ABSTRACT FROM AUTHOR]

Rain falling from the sky is viewed as a clean energy source with a great potential, owing to the large amount of it and its zero pollution nature, the fact that it has scattered raindrops, and its characteristic rainfall concentration that promotes extensive research on harvesting and utilization. Here, we introduce a new approach to harvest rainwater on rooftops called the Rain-Power Utilization System, which is composed of an initial rainwater disposal system and multistage energy conversion system. Initial rainwater is discharged into a split-flow pipe due to its poor quality and impurities. Additionally, clean rainwater is accumulated in a storage pipe until the water level reaches a specified height, triggering siphonage for energy conversion. The same process is repeated in other storage pipes connected in series. Function relations among physical and dimension parameters have been established for further studies. A kind of simplified optimization algorithm has been proposed considering the maximum instantaneous power under the constraint of a permitted vacuum and maximum energy generation per unit length to find the model with an optimal height combination (hu, hd). The experimental prototype developed in proportion is used to verify theoretical research and conduct error analysis to establish an equation of annual energy generation for a high-rise building. Without building extra tanks, this paper presents an innovative approach to maximizing the use of energy in rain for high-rise buildings based on a siphon. [ABSTRACT FROM AUTHOR]

Building energy performance benchmarking increases awareness and enables stakeholders to make better informed decisions for designing, operating, and renovating sustainable buildings. In the era of nearly zero energy buildings, the embodied energy along with operational energy use are essential for evaluating the environmental impacts and building performance throughout their lifecycle. Key metrics and baselines for the embodied energy intensity in representative Hellenic houses are presented in this paper. The method is set up to progressively cover all types of buildings. The lifecycle analysis was performed using the well-established SimaPro software package and the EcoInvent lifecycle inventory database, complemented with national data from short energy audits carried out in Greece. The operational energy intensity was estimated using the national calculation engine for assessing the building's energy performance and the predictions were adapted to obtain more realistic estimates. The sensitivity analysis for different type of buildings considered 16 case studies, accounting for representative construction practices, locations (climate conditions), system efficiencies, renovation practices, and lifetime of buildings. The results were used to quantify the relative significance of operational and embodied energy, and to estimate the energy recovery time for popular energy conservation and energy efficiency measures. The derived indicators reaffirm the importance of embodied energy in construction materials and systems for new high performing buildings and for renovating existing buildings to nearly zero energy. [ABSTRACT FROM AUTHOR]

It is well known that nowadays a significant part of the total energy consumption is related to buildings, so research for improving building energy efficiency is very important. This paper presents our investigations about the dimensioning of horizontal overhangs in order to determine the minimum annual consumption of building primary energy for heating, cooling and lighting. In this investigation, embodied energy for horizontal roof overhangs was taken into account. The annual simulation was carried out for a residential building located in the city of Belgrade (Serbia). Horizontal overhangs (roof and balcony) are positioned to provide shading of all exterior of the building. The building is simulated in the EnergyPlus software environment. The optimization of the overhang size was performed by using the Hooke Jeeves algorithm and plug-in GenOpt program. The objective function minimizes the annual consumption of primary energy for heating, cooling and lighting of the building and energy spent to build overhangs. The simulation results show that the building with optimally sized roof and balcony overhangs consumed 7.12% lessprimary energy for heating, cooling and lighting, compared to the house without overhangs. A 44.15% reduction in cooling energy consumption is also achieved. [ABSTRACT FROM AUTHOR]

Considering the critical amount of power consumption in public buildings, sustainable energy use in the workplace can present an opportunity to tackle the worldwide problem of climate change. A systematic literature review revealed that, though the majority of scientific papers emphasize the importance of appliances and new technologies, human behavior in this area is not less significant. It can contribute to the reduction of energy use and CO2 emissions and address a number of environmental issues. The main purpose of this work is to analyze and compare the research performed on the topic of the determinants of sustainable energy consumption and investigate their impacts on the behavior of employees in three public buildings in Greece. The questionnaire survey discloses that, despite the organizations paying the bill, the employees believe that saving energy at work is important. The results also show that female employees feel more responsible for energy problems, such as the exhaustion of energy sources or global warming. Finally, a regression analysis affirms that the willingness to save a substantial amount of energy at the workplace is greater when employees have higher personal norms, that is, they feel morally obliged to consider the environment and nature in their daily behavior. [ABSTRACT FROM AUTHOR]

Building energy code compliance is the crucial link between the actual energy savings and the efficiency prescribed in energy codes. A research project aiming to identify opportunities to reduce energy consumption in new single-family residential construction by increasing compliance with the building energy code was conducted in several states of the United States. The study was comprised of three phases: (1) a baseline study to document typical practice and identify opportunities for improvement based on empirical data gathered from the field; (2) an education and training phase targeting the opportunities identified; and (3) a post-study to assess whether a reduction in average state-wide energy use could be achieved following the education and training phase. We proposed a novel methodology based on large-scale building energy simulation inferred by limited field data to assess the performance of a large population of homes. This paper presents the methodology, findings, and results of this study. The state-wide average energy consumption decreased at Phase III from Phase I for five of the seven states involved in the analysis. The measure-level savings potential analysis shows an overall reduction. Overall, the training and education phase plays a recognizable role in improving compliance with building energy codes. [ABSTRACT FROM AUTHOR]

Reduction of the primary energy consumption is a crucial challenge for the building sector due to economic and environmental issues. Substantial savings could be achieved within the household. In this paper, we investigate the energy performance of a single-family house located in the temperate climate. The assessment is based on the comprehensive thermal diagnostic of the building performed on-site and via computational analyses. The on-site measurements included diagnostics of the building envelope, heat source, heating and domestic hot water system, ventilation system, and indoor environmental quality. Analyses confirmed that the studied building, which was built in 2008, meets the legislation requirements for the primary energy usage at that time and nowadays. However, results show discrepancies between energy performance obtained through on-site measurements and computational methods following regulations. Partially, discrepancies are a result of differences on normative values and how the building is operated in practice. It is also showed how important the role in the assessment of energy consumption through measurements is played by the measurement period. [ABSTRACT FROM AUTHOR]

Currently, enhancing sustainability, and in particular reducing energy consumption, is a huge challenge for manufacturing enterprises. The vision of the fourth industrial revolution (so-called "industry 4.0") is not only to optimize production and minimize costs, but also to reduce energy consumption and enhance product life-cycle management. To address this challenge, a multi-agent architecture aimed at elaborating predictive and reactive energy-efficient scheduling through collaboration between cyber physical production and energy systems is proposed in this paper. Smart, sustainable decision tools for cyber physical production systems (CPPS) and cyber physical energy systems (CPES) are proposed. The decision tools are data-driven, agent-based models with dynamic interaction. The main aim of agent behaviours in the cyber part of CPPS is to find a predictive and reactive energy-efficient schedule. The role of agents in CPES is to control the energy consumption of connected factories and switch between the different renewable energy sources. Dynamic mechanisms in CPPS and CPES are proposed to adjust the energy consumption of production systems based on the availability of the renewable energy. The proposed approach was validated on a physically distributed architecture using networked embedded systems and real-time data sharing from connected sensors in each cyber physical systems. A series of instances inspired from the literature were tested to assess the performance of the proposed method. The results prove the efficiency of the proposed approach in adapting the energy consumption of connected factories based on a real-time energy threshold. [ABSTRACT FROM AUTHOR]

Building envelopes can play a significant role in controlling energy consumption, especially in hot regions because of the wide variety of envelope materials and technologies that have been developed. Currently, because of the high rise in energy prices, especially with the high demand of fossil energy in the building sector worldwide, using curtain walls for maintaining adequate lighting in public buildings could lead to higher energy consumption because of the continuous exposure to the sun in hot regions. For this reason, studying the use of renewable or smart alternatives in the building sector to ensure a cleaner, greener environment by deploying sustainable technology in order to reduce energy demand and support economic long-term solutions would be important for solving such a problem. This paper aims at studying the use of renewable energy technologies and alternatives; represented in new building integrated photovoltaics (BIPVs) technology that could be integrated within building skin to reduce energy demand. The methodology follows a quantitative comparative approach, using an energy simulation software to study two different types of BIPV technology (BISOL Premium BXO 365 Wp monocrystalline and BXU 330 Wp, polycrystalline) on an existing building by retrofitting a part of its curtain wall. This is to conclude the energy saving percentage and feasibility of both alternatives. [ABSTRACT FROM AUTHOR]

With growing urbanization, it has become necessary to manage this growth smartly. Specifically, increased electrical energy consumption has become a rapid urbanization trend in China. A building model based on a neural network was proposed to overcome the difficulties of analytical modelling. However, increased amounts of data, repetitive computation, and training time become a limitation of this approach. A simplified model can be used instead of the full order model if the performance is acceptable. In order to select effective data, Mean Impact Value (MIV) has been applied to select meaningful data. To verify this neural network method, we used real electricity consumption data of a shopping mall in China as a case study. In this paper, a Bayesian Regularization Neural Network (BRNN) is utilized to avoid overfitting due to the small amount of data. With the simplified data set, the building model showed reasonable performance. The mean of Root Mean Square Error achieved is around 10% with respect to the actual consumption and the standard deviation is low, which reflects the model's reliability. We also compare the results with our previous approach using the Levenberg–Marquardt back propagation (LM-BP) method. The main difference is the output reliability of the two methods. LM-BP shows higher error than BRNN due to overfitting. BRNN shows reliable prediction results when the simplified neural network model is applied. [ABSTRACT FROM AUTHOR]