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Prosumers have a different interaction with the distribution network in comparison with traditional consumers. They have a bi-directional power exchange with the grid, meaning they receive from as well as deliver electricity to the network. The emergence of prosumers is expected to challenge the way network operators control the residential low-voltage (LV) distribution networks. Commonly, the metering of received and delivered electricity at the residential level is conducted on 1-hour basis, thus only hourly load/generation profiles are available for the system operators to conduct the power system impact analysis. Yet, it is relatively difficult to have an accurate prediction of the real system performance if the intra-hour phenomena are not considered. A better estimation requires employment of higher temporal resolution profiles during the power system studies. To address these challenges, which future smart cities and communities might face, this paper presents a methodology for generating 1-minute load profiles based on the hourly readings from smart meters. Secondly, it demonstrates gain in information about LV network by employing the high resolution profiles for power system impact analysis. Finally, it highlights the problems of smart residential networks with high share of prosumers for two LV network scenarios during winter and summer weeks.

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.

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.

District heating has been found to be a key component of future and reliable smart energy grids comprising 100% of renewable energy sources for countries with dominant heating season. However, these systems face challenges that require a deeper understanding of the coupling between the distribution networks and the connected buildings, to enable demand-side management and balance the intermittence of renewables. In recent years, many smart energy meters have been installed on the heating systems of Danish dwellings connected to district heating, and the first yearly measurement data sets of large building clusters are now available. This article presents the methodology for the pre-processing and cluster analysis (K-means clustering) of a one-year-long smart energy meter measurement data from 1665 Danish dwellings connected to district heating. The aim is to identify typical household daily profiles of heat energy use, return temperature, and temperature difference between the supply and the return fluid. The study is performed with the free software environment “R”, which enables the rapid extraction of information to be shared with professionals of the building and energy sectors. After presenting the preliminary results of the clustering analysis, the article closes with the future work to be conducted on this study case.

There is little specific knowledge of actual temperature conditions in buildings. This paper contributes with results from a detailed long-term monitoring campaign of temperature conditions in 17 households. Furthermore, these measurements are combined with qualitative interviews with 22 occupants in 16 households, on their heating practices. Implications for the assessment of the heat demand flexibility potential are discussed, and it is suggested that including occupants in future experiments can be a way to reach the full potential of buildings flexibility potential to a renewable energy sources dependent energy system. Quantitative data show that temperature conditions vary with time and space within each dwelling and between dwellings. In the same apartment, the temperature difference between spaces can be 7 K. The living rooms have the most homogeneous temperature distribution during 24 h period and the bedrooms most significant variations. Qualitative data indicate that aspects of: Activities performed by occupants; Caring for things, others and oneself; Comfort; Convenience; Natural and material surroundings affect occupants’ heating practices.

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.

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

Intermittent energy resources challenge the ways in which the existing energy system operates. Studies suggest that residential buildings can provide a flexibility service for district heating (DH) systems. This technique involves load shifting by heating buildings to higher temperatures at times when energy is more readily available, thus diminishing heating needs at times of peak demand or when energy is scarce. Based on three Future Workshops (FWs) where DH professionals and other relevant DH stakeholders participated and discussed this topic, this paper reports on the extent to which these actors see energy flexibility as a realistic future development, and on what they see as key potentials and challenges in that regard. Preliminary results indicate that the mix of the actors and the specific local context greatly influence how this topic is understood, emphasizing the importance of including local context in investigations of energy flexibility. FW participants included representatives from DH companies, municipalities, building associations, technology developers, etc. The FWs were conducted at three different localities of Denmark: Copenhagen, Aalborg and Sønderborg, i.e. the national capital, a regional capital and a smaller city, respectively.

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.

Today’s HVAC systems in the building sector become more and more complex in order to fulfill the increasing standard of the indoor environment, which typically have many components, sub-systems, and controls. Commissioning is a quality-oriented process to verify and document that the performance of buildings and HVAC systems fulfill the defined objectives and criteria. This study demonstrates the commissioning process in a campus building in Denmark. By analyzing the monitored date from BMS and on-site measurements, some fault operations and controls in the HVAC systems are identified, for example, improper setpoint for heating and ventilation, fault location of temperature and CO2 sensors, too high return temperature for district heating, etc. A building simulation model is developed and validated in order to test the optimization strategies and evaluate the energy conservation potential. An energy saving ranges from 20%-42% is realized after the implementation of the optimization strategies.