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Abstract In 2011, the Danish government published an energy strategy for Denmark where one of the main targets are that Denmark should be a fossil-free society by 2050. Calculations show, that in order to reach this goal it is necessary to reduce the energy consumption of the existing building stock by 50% on average. Since a 50% reduction is obviously not possible for all buildings, those that can should aim for a so-called "deep energy renovation", i.e. reducing the energy consumption to a level corresponding to that of new buildings or even more. This paper describes two case studies where multi-story apartment buildings have undergone deep energy renovation. "Traneparken" where the expected energy use after renovation aimed at a level corresponding to that of a new building according to the Danish Building Regulations from 2015. "Sems Have" where the aim was to go even further and meet the requirements expected for new buildings in 2020, i.e. corresponding to the Danish "nearly zero energy"-definition according to the EPBD. The paper reports on calculations and measurements of energy savings, the economy of the projects and looks at the added benefits or co-benefits that residents, housing association and society in general have achieved in addition to significant energy savings. [ABSTRACT FROM AUTHOR]

One of the main problems for adopting smart thermostats is consumers’ expectations about smart thermostats. Generally, the interfaces in smart thermostats and smart devices in the energy market are designed without consideration for the expectations of the customers or are not adjusting their operation according to the consumers’ expectations and behavior. Moreover, the business model does not consider one part of the product as the main link between customers and value propositions. This study shows a structure for creating a smart interface based on consumers’ expectations and shows an extension of the CANVAS business model. Furthermore, the paper re-defines the term “smart” in electric devices as the ability to adjust the system in order to reach the expectations of the consumer and to save energy. This term is not only defined in terms of saving energy but also it includes the customer’s expectations. If the system is only smart to control the temperature and save energy, the customer’s expectations may not always be achieved; thus, the smart devices are not successfully adopted in households. The design is based on artificial neural networks and a fuzzy logic controller to achieve the consumer’s expectations. The results show the interface operation on each block. The classification systems have to operate to detect changes in the customer’s market segment. The fuzzy logic controller tries to reach the customer’s expectations in order to move the customer into the energy saving market. This expectation interface tries to motivate designers to focus on consumer’s expectations for smart devices in the energy market. Not only are the energy requirements important to design a smart thermostat, but also the consumer’s expectations to create a successful smart thermostat in the electric market. Smart thermostats can reduce the consumption of electrical energy, but they need to be accepted. This interface provides an effective manner to connect the consumer’s expectations with the consumption of energy. This papers shows a proof of concept about intelligent interfaces. [ABSTRACT FROM AUTHOR]

Energy poverty can be understood as the inability of a household to secure socially and materially the necessitated level of energy services in the home. This condition is described as either energy or fuel poverty and it has been recognized by the EU's so called “Third Energy Package”. The work in this field has identified a number of household-level factors that influence the likelihood of experiencing domestic deprivation, with particular emphasis being placed on understanding how education levels correlates to the phenomenon. In that perspective, and in order to study the dynamics of energy poverty in Greece, a questionnaire was prepared and distributed mainly by means of in-situ interviews and, in exceptional cases, in remote sessions. The evidence presented in this paper is based on a comprehensive study of 762 questionnaires mainly for Western Macedonia (43.6%) and Central Macedonia (42.6%), Greece. Using the quantitative data gathered, we measure the energy vulnerability concerning the quality of the housing–dwelling, the heating system, indoor thermal comfort and the net-income. The research is, to our knowledge, the first attempt to analyze residential energy, habitants’ behavior, and attitudes in the middle of the economic crisis in North Greece. It has been determined, that the middle class has become the most vulnerable class in that sense. A further scope of this paper is not only to present this data, which prove that domestic energy deprivation appears not only in Southern but also in Northern Greece, but also to discuss measures that can be adopted in order mitigate energy and social vulnerability of the middle class. [ABSTRACT FROM AUTHOR]

Abstract Beyond the definition and measurement of energy poverty, which have mainly attracted research interest over the last decades, attention has recently begun to turn to a broader notion of energy vulnerability. So far, this has mostly been approached on a theoretical base, suggesting the incorporation of broader socio-economic aspects into the energy poverty framework. However, the quantitative measurement of energy vulnerability is still an unexplored field of research. In this paper, the "Vulnerability Index" is developed, which, based on stochastic analysis, quantifies the vulnerability of a population to the energy poverty ratio, compared to a reference population. Moreover, Sensitivity Analysis quantifies the particular contribution of various parameters to the problem, by determining their weighting factors. As case study, the vulnerability of Greek mountainous regions with respect to the country level was studied. The results showed that households living in mountainous regions are more vulnerable versus those of the whole country, at 89.7%. It was also found that energy policy should focus on raising incomes of mountainous population and, afterwards, on energy saving measures and reduction of heating cost in mountains. The methodology suggested can address social inequalities of vulnerable population groups, in terms of energy poverty. [ABSTRACT FROM AUTHOR]

In this paper a model for choosing the proper modular configuration of a point-focus concentrating thermo-photovoltaic (CPV/T) system according to the domestic user energy demands, is presented. The main aim is to evaluate several modular configuration solutions in terms of energy and economic performances and space occupied. First of all, the main CPV/T system components are chosen: optics, solar cells and tracking system. A point-focus system with parabolic mirrors, triple-junction cells and dual-axis tracking system is considered. The choice of the proper CPV/T system configuration is realized considering an equations system that defines the electric and thermal performances in terms of solar radiation, cells number and concentration factor. The choice model presented in this paper allows to configure, referring to different Italian zones, the CPV/T system under several working conditions minimizing spaces and costs. It is observed that CPV/T modules with a lower cells number allow high flexibility to satisfy the loads. The high concentration level determines interesting solutions related to a domestic application from the energy and economic point of view, above all in southern Italy, during the CPV/T system life cycle. Finally, CPV/T systems allow a significant reduction of CO 2 emissions due to the primary energy savings. [ABSTRACT FROM AUTHOR]

Policy makers have realized that without significant increases in the energy efficiency and notable reductions in the energy use of the household sector, it will be impossible to lower carbon dioxide emissions and mitigate the risks of climate change at the global level. The energy demand in residential buildings is influenced by several parameters, such as national economic growth, climate and weather, demographic structure, and technological development. In this paper, we analyze the determinants of electricity and natural gas consumptions in Italy during the period from 2004 to 2013. We provide estimates of price and income elasticities of the demand for both the energy sources in the residential sector. The role played by both energy price and household income is worth attention because it provides evidence for the occurrence of the direct rebound effect. Therefore, the economic drivers of the energy demand are important to improve the policies meant to reduce greenhouse gas emissions and contrast the global warming. [ABSTRACT FROM AUTHOR]

Industrial facilities account for 33% of the annual energy usage within the United States [17] and this large sector of the domestic energy budget presents significant opportunities for energy efficiency. In order to effectively analyze energy savings opportunities in industrial facilities, adequate baseline models of energy usage in the facilities are needed. Multiple methods of creating baseline energy models have been used in commercial and residential buildings, however, few of these techniques have been made applied to develop baseline energy models in industrial facilities. The paper investigates the application of standard regression models used for commercial and residential buildings to industrial facilities using sparse energy consumption data. An analysis of the effectiveness of three parameter cooling (3PC) and cooling degree day (CDD) regression models to develop baseline energy usage models in industrial facilities from commonly available utility bill data is presented. Two case studies are investigated: in both case studies a comparison between 3PC model and CDD model is presented. In both cases the baseline regression models meet the recommended NMBE from the ASHRAE Guideline 14. A method to determine process equipment energy usage and cooling end use due to internal loads is presented. [ABSTRACT FROM AUTHOR]

In the tourism industry, hotels and homestay facilities account for considerable amounts of energy consumption and CO 2 emissions. Unlike other types of buildings, occupancy has significant fluctuations over time, while mostly being ignored or using a simple assumption based on energy use intensity or setting the occupancy levels. Due to the lack of occupancy rate information, great uncertainties exist in hotel operations, which leads to erroneous estimates of energy consumption in existing hotel buildings. This paper examines hotel operation practices in China with real occupancy rate data which is critical for reducing the uncertainty of estimating energy consumption patterns. Specifically, this study proposes a two-stage comprehensive and quantitative performance assessment approach for the homestay hotel building considering the system's energy and economic performance simultaneously. Regarding energy performance, there are two key facets to consider: renewable energy penetration and grid impact performance. Additionally, the economic performance (annual income and extra annual investment) of various energy portfolios is evaluated using break-even analysis. The impacts of large fluctuation in occupancy rate on electrical loads are considered and assessed in typical homestay hotels. The proposed assessment approach can comprehensively quantify the impacts of the photovoltaics (PV) areas and battery capacities on the system performance in terms of energy and economics. According to the results of the occupancy-based assessment, the ideal PV area and battery capacity are 400 m2 and 16 kWh, respectively, as opposed to the optimal energy portfolios (PV area 600 m2 and battery capacity 24 kWh) determined from conventional assessment results. [ABSTRACT FROM AUTHOR]

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

The Swedish energy performance certificates for single-family housing provide rich information on energy consumption and various physical attributes. They also include estimates of the energy conservation potentials resulting from implementing cost-efficient energy saving measures. By matching the certificates issued for single-family houses in 2009 and 2010, with socio-economic data about the residents, local climate data and information about recent improvements of the building we have created a unique database, which can be used to explore a wide variety of questions related to energy consumption and conservation. One aim of this paper is to assess the role for energy consumption played by socio-economic characteristics of the residents as compared to physical attributes of the house. Another is to estimate the influence of housing attributes and climate on the “engineering estimates” of the conservation potentials. Our results show that while the quantitative impact of physical attributes dominate the energy use for heating and cooling, the opposite holds for household electricity. The assessed conservation potential, amounting to 15% of the energy consumption, is significantly related to both the housing attributes and the use of energy. The results also indicate a need to improve the information provided by the performance certificates. [ABSTRACT FROM AUTHOR]

Buildings account for a large share of energy consumption and greenhouse gas emission. Numerous methods have been applied to operate buildings more efficiently. However, the embodied energy and carbon are identified increasingly important in terms of sustainability throughout building life cycle. In traditional building structural design approach, the engineers pay little attention on environmental aspect which has been recognised as one of the most important factors to consider in modern integrated building design approach. The emergence of Semantic Web technologies provides more opportunities to assist structural engineers in improving building sustainability. The study presented in this paper investigates how ontology and Semantic Web rules can be used in a knowledge-based system, to represent information about structural design and sustainability, and to facilitate decision-making in design process by recommending appropriate solutions for different use cases. A prototypical system named OntoSCS (Ontology for Sustainable Concrete Structure), including a Web Ontology Language (OWL) ontology as knowledge base and SWRL rules providing reasoning mechanism, is developed to offer optimised structural design solutions and selections of material suppliers. Embodied energy and CO 2 are used in the system as indicators to evaluate sustainability of structure. Both ontology reasoner and case studies are employed for system validation. [ABSTRACT FROM AUTHOR]

Energy consumption has long been emphasized as an important policy issue in today's economies. In particular, the energy efficiency of residential buildings is considered a top priority of a country's energy policy. The paper proposes a genetic programming-based framework for estimating the energy performance of residential buildings. The objective is to build a model able to predict the heating load and the cooling load of residential buildings. An accurate prediction of these parameters facilitates a better control of energy consumption and, moreover, it helps choosing the energy supplier that better fits the energy needs, which is considered an important issue in the deregulated energy market. The proposed framework blends a recently developed version of genetic programming with a local search method and linear scaling. The resulting system enables us to build a model that produces an accurate estimation of both considered parameters. Extensive simulations on 768 diverse residential buildings confirm the suitability of the proposed method in predicting heating load and cooling load. In particular, the proposed method is more accurate than the existing state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Approximately 27% of the European energy consumption is caused by the domestic sector, where 19% of the end use energy demand is caused by electric devices. To investigate the factors at play, a stochastic bottom-up model for the generation of electric load profiles is introduced in this paper. The model is designed for investigating the effects of occupant behaviour, appliance stock and efficiency on the electric load profile of an individual household. For each activity of a person in the household, an electric appliance is used, and its electricity consumption is linked to measured electric load traces with a time resolution of 10 s. Probability distributions are incorporated for when and how often an appliance is operated. Duration of operation is given as probability density conditional on the start time. Shared use of an appliance by multiple persons is included in the model. Seasonal effects are considered by using changing probability sets during the course of the year. For validation, seven subgroups, which reflect typical household configurations, were formed and tested against measured field data from 430 households in 9 different cities across Germany. The results showed an accuracy of 91% and a correlation of up to 0.98. [ABSTRACT FROM AUTHOR]

Abstract: Better energy efficiency of ground coupled heat pump systems in comparison with traditional applications leads to continued growth in the number of installations for space conditioning. The solution with vertical heat exchangers is the most widespread. The design of the borehole heat exchangers (BHEs) is a nodal point, both from an energy efficiency and an economic point of view. In literature, several methods to design these systems are available. However, to promote their application, easy-to-use procedures are required; furthermore designers very often are discouraged from the use of not-open or complicated computational tools. Among the literature models, the ASHRAE method is surely the simplest procedure and, as a consequence, it is suitable for this goal. In this approach, sizing of the BHE length is strongly affected by the parameter named penalty temperature, which is an index to evaluate the long-term behaviour of the borehole field. In this paper, a review of this index is reported and in addition a new approach for its evaluation is presented. Furthermore, a detailed analysis of the proposed method is performed on a real case-study building with only heating conditioning. [Copyright &y& Elsevier]

Abstract: Estimation of energy performance indexes, like the heating curve or the energy signature, requires robust regression of the heating losses on the outdoor temperature. The solution proposed in this paper is to use the range between the 1st and the 3rd quartile of the quantile–quantile (q–q) plot to check if the heating losses and the outdoor temperature have the same distribution and, if yes, to perform the regression in this range of the q–q plot. The result is a model that conserves its prediction performance for data sets of the outdoor temperature different of those used for parameter identification. The robust model gives the overall heat transfer coefficient and the base temperature, and it may be used to estimate the energy consumption for data sets of the outdoor temperature coming from different time—space locations. [Copyright &y& Elsevier]

Abstract: Through a case study, this research explores an approach, which uses computer simulation technology, to evaluate different energy conservation alternatives and to assist facility managers to select reliable and feasible solutions. The subject facility is located in the Southeast region of the United States. One of the major challenges and operation goals of the General Services Administration, who manages the facility, is for that facility to achieve the Energy Star designation. However, due to the complexity of the facility, the requirements from building occupants, as well as other difficulties, finding a path for optimizing the operation of the facility in order to achieve the Energy Star designation is not always easy. This project uses eQuest, a simulation software tool, to create a “virtual environment”, in which the operations of the HVAC (heating ventilation air-conditioning) system and the lighting of the facility are studied. Subsequently, recommendations initially made by experts through traditional energy audit approaches are evaluated in the “virtual environment” in order to determine the best solution to achieve the goal of the facility managers. This paper discusses major aspects of the project, including the challenges, the values and the limitations of applying computer simulation techniques in such a facility with complicated structural, occupancy and operation features. [Copyright &y& Elsevier]