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Much effort has been put in tightening the building regulations. Though, the energy usage for domestic hot water stayed unchanged constituting a bigger share of the energy pie over the years. Due to the cost, timeframe, and workload associated with instrumentation and installation, the vast majority of the DHW measurements are limited to the household level. This paper introduces a high resolution measuring technique for DHW consumption and its application in a single family house. By applying this technique, we are able to measure the duration, flow and temperature of each water draw event in the house and thus create both the temporal and spatial DHW consumption profiles. The results indicated that the duration of draws varies significantly between tapping places, i.e. the draws in the shower and in the kitchen have an average duration of 300 sec. and 20 sec., respectively. The high resolution metering system was able to record the inefficient use of DHW, at periods when the water temperature was not meeting the users’ requirements, e.g. the wasted energy at the shower depending on the usage patter varies between 25% and 42%. The measured temperature range of DHW in the household is between 52°C (kitchen) and 21°C (sink in utility room).

In Europe, one of the most sustainable solutions to supply heat to buildings is district heating. It has good acceptance in the Northern countries, a low-carbon footprint, and can easily integrate intermittent renewable energy sources when coupled to the electrical grid. Even though district heating is seen as a vital element for a sustainable future, it requires extensive planning and long-term investments. To increase the understanding of the district heating network performance and the demand-side dynamics of the connected buildings, several countries, including Denmark, have installed smart heat meters in different cities. In that context, this paper presents several methodologies to analyze the datasets from the smart heat meters installed in a small Danish town. The first method is concerning data curation to remove the anomalies and missing data points. The second method analyses measured variables (heat consumption, outdoor temperature, wind speed, and global radiation) to acquire new knowledge on the building characteristics. These results were compared with the values given by the energy performance certificates of a smaller sample of 41 households. Finally, to communicate and visualize the analysis outputs in a user-friendly way, an interactive web interface tool has been created.

For a very long time activities related to efficient domestic hot water (DHW) production and distribution have been neglected and left behind due to an insignificant share in total energy use for buildings. It is in recent years that DHW has emerged as one of the key energy factors in the total energy use in buildings and its share is continuously increasing as energy use in other segments is continuously decreasing, for example space heating, ventilation, and energy for lighting. It becomes suddenly undeniable that efforts in the field of energy-efficient DHW must be strengthened, and as such, there is increased activity in the field. However, the work reported is very dispersed and fragmented. The objective of this review article is to collect and present recent works related to improve performance of a DHW system in terms of energy. The scope and content of the paper aims to address the topics of high relevance to the field, these are shift towards the new situation in which DHW becomes a significant energy use responsible factor in buildings, distribution and weighting of losses related to DHW systems and purpose of DHW use. The article focuses on novel actions to obtain energy-efficient DHW in the following domains: DHW production, DHW distribution and circulation, wastewater heat recovery, and control strategies. The article finishes with conclusions.

International audience; This paper aims to visualize how the planned electrification of heat demand together with the utilization of energy flexibility in buildings will influence the performance of local electricity network. Thereby, the work contributes to the research on smart energy system in the residential sector. The flexibility service is provided by two demand-side-management strategies a) activation of the thermal mass to modulate load profile of a heat pump, b) control of household appliances' starting times. Three configurations of load mix in the local electricity network are investigated: a) domination of non-renovated houses, b) with equal share of high and low heat demand houses, c) domination of energy efficient houses. The model is soft-coupled and anchored in existing low voltage (LV) network and existing residential buildings. The energy flexible buildings enhance the LV network performance, by decreasing the afternoon peaks, without compromising the occupants’ thermal comfort. The highest impact is for the LV network dominated by energy efficient houses. There are also new challenges, namely the newly created peak loads and transformer overloading during night time. It is a consequence of uniform price signal sent to all flexible customers and electrification of heating demand without parallel improvement of energy performance.

The focus on reducing buildings energy consumption is gradually increasing, and the optimization of a building’s performance and maximizing its potential leads to great challenges between architects and engineers. In this study, we collaborate with a group of architects on a design project of a new office building located in Aarhus, Denmark. Building geometry, floor plans and employee schedules were obtained from the architects which is the basis for this study. This study aims to simplify the iterative design process that is based on the traditional trial and error method in the late design phases and improve the collaboration efficiency. Monte Carlo Simulation method is adopted to simulate both the energy performance and indoor climate of the building. Building physics parameters, including characteristics of facades, walls, windows, etc., are taken into consideration, and thousands of combinations of these parameters are screened to find those can achieve the design criteria. The software Be15 and BSim are used as two-step solvers to process the calculation of energy consumption and indoor environment. A solution pool is then obtained for architects to choose from, see Fig. 2 and 3. All these solutions can fulfil the requirements and leaves additional design freedom for the architects. This study utilizes global design exploration with Monte Carlo Simulations, in order to form feasible solutions for architects and improves the collaboration efficiency between architects and engineers.

During recent years, the research in reduction of energy use in buildings has focused primarily on decrease of space heating needs, energy for ventilation and recently cooling, whereas domestic hot water (DHW) has been overlooked. In 2013, the energy use for DHW was estimated at 16% of total heat requirement in EU28 households, but in new energy-efficient buildings this share is documented to be around 40–50%. Generally, however, there is limited knowledge of DHW. This paper presents a simple methodology, which enables calculation of the mean hourly and the daily profiles of DHW demand from hourly values of the building total heat demand, and thus contributes to gaining a better understanding of the DHW usage. The method is validated with data from single-family houses and apartments and afterwards applied to dataset consisting of hourly total heat consumption readings from 38 single-family houses delivered by district heating. The method gives satisfying results when the DHW usage during summer is at least at the same level as the space heating demand, which is the case in apartments and in the energy-efficient houses. The standard deviation was used as preliminary classification criterion for deciding if the method can or cannot be applied. Two limits were found σ > 240 for apartments and σ < 800 for single-family houses.

As demand response and energy flexibility are often suggested as key principles to facilitate high levels of renewable energy sources into energy markets, different studies evaluated the potential impact of energy flexibility in buildings. Nonetheless, due to differences in definition and quantification methodologies for energy flexibility, comparing results between such studies is difficult. With a review and applied evaluation of existing definitions and quantification methodologies this paper aims at assessing the applicability, benefits and drawbacks of each quantification methodology. The conducted review shows that energy flexibility definitions found in the literature have their particularities despite sharing the same principle that energy flexibility is the ability to adapt the energy profile without jeopardizing technical and comfort constraints. The survey of quantification methodologies reveals two main approaches to quantify energy flexibility. A first approach quantifies energy flexibility indirectly using past data and assuming a specific energy system and/or energy market context. The second approach directly predicts the energy flexibility that a building can offer to the energy system in a bottom-up manner. While applications for both approaches were identified, this paper focuses on the latter. By applying methodologies that follow this second approach to a common case study, three common properties of energy flexibility were observed: i) the temporal flexibility; ii) the amplitude of power modulation; iii) and the associated cost.

The increasing global energy demand, the foreseen reduction of available fossil fuels and the increasing evidence off global warming during the last decades have generated a high interest in renewable energy sources. However, renewable energy sources, such as wind and solar power, have an intrinsic variability that can seriously affect the stability of the energy system if they account for a high percentage of the total generation. The Energy Flexibility of buildings is commonly suggested as part of the solution to alleviate some of the upcoming challenges in the future demand-respond energy systems (electrical, district heating and gas grids). Buildings can supply flexibility services in different ways, e.g. utilization of thermal mass, adjustability of HVAC system use (e.g. heating/cooling/ventilation), charging of electric vehicles, and shifting of plug-loads. However, there is currently no overview or insight into how much Energy Flexibility different building may be able to offer to the future energy systems in the sense of avoiding excess energy production, increase the stability of the energy networks, minimize congestion problems, enhance the efficiency and cost effectiveness of the future energy networks. Therefore, there is a need for increasing knowledge on and demonstration of the Energy Flexibility buildings can provide to energy networks. At the same time, there is a need for identifying critical aspects and possible solutions to manage this Energy Flexibility, while maintaining the comfort of the occupants and minimizing the use of non-renewable energy. In this context, the IEA (International Energy Agency) EBC (Energy in Buildings and Communities program) Annex 67: “Energy Flexible Buildings” was started in 2015. The article presents the background and the work plan of IEA EBC Annex 67 as well as already obtained results. Annex 67 is a corporation between participants from 16 countries: Austria, Belgium, Canada, China, Denmark, Finland, France, Germany, Ireland, Italy, The Netherlands, Norway, Portugal, Spain, Switzerland and UK. ispartof: Energy and Buildings vol:155 pages:25-34 status: published

The objective is to present a high-resolution model of household electricity use developed based upon a combination of measured and statistical data. It is a bottom-up model, which uses the 1-min cycle power use characteristics of a single appliance as the main building block. The effect of parameters, such as the number of occupants and their attitude towards energy use is included in the model. Moreover, the model accounts for phenomena related to unexpected weather conditions and local/national events, e.g. TV shows. The main aim of model is to generate high-resolution household load profiles for investigation of flexibility potential of domestic appliances and network modelling. The model is validated with two datasets of 1-h and 5-min data from 89 to 16 households, respectively. The comparison between measured and modelled values indicates that model well captures the characteristics of domestic electricity load profiles on a daily as well seasonal basis. For high-resolution data, the model represents well the differences in demand between households of dissimilar size as well as the diversity of demand between households of the same size. For the individual household, the high-end power consumption is under-represented since the timing of peaks is more diverse in the model.