Search

• The paper has a focus on energy consumption habits and trends using statistical methods. • Occupants' behavior is monitored using smart metering system and awareness surveys. • The impact of a serious game on occupant's behavior is evaluated. The paper has a focus on energy consumption habits, trends and intervention strategies in residential buildings, mainly through the serious game approach with a combination of direct consumer feedback through smart metering. More than 150 homes in France and Spain have been involved in the research experiment and the consumption habits of approximately 50 homes were deeply analyzed. The applied methods, processes, results and findings of the monitoring data analysis are presented in the paper with two aims. First, consumption profiles and trends were determined for apartment homes with regard to heating, domestic hot water and electric consumption. Second, the impact of a serious game experiment was assessed comparing energy consumption, indoor air temperature and users' habits (based on questionnaires) before and after launching the experiment. [ABSTRACT FROM AUTHOR]

Countries in Eastern-Europe have similar characteristics due to their common historical and economic backgrounds. A large part of the housing stock has been built during the Soviet era, applying uniform solutions and similar standards, but similarities extend to other periods as well. On the other hand, the differences should also be noted – although the climate is mainly continental, there are significant variations between South and North and between mountainous and flat areas. In this paper, a detailed comparative analysis is presented for Bulgaria, Serbia, Hungary and the Czech Republic. The results are based on the residential building typologies developed within the TABULA/EPISCOPE project co-funded by the Intelligent Energy Europe Programme. Typical building types will be presented, covering building structures and systems. Important energy performance indicators are identified and compared, supported by available statistical data about the housing stock. The added value of the paper consists of the analysis of heterogeneous data sources and collecting and comparing the information of the housing stock under a common comparison framework of building typology data between countries, and the contribution in the harmonization of the building typology approach. [ABSTRACT FROM AUTHOR]

• Classical load matching indicators are incapable of advising photovoltaic capacity. • Novel indicators with technical optima are introduced for PV sizing. • Self-production can be a useful metric for maximizing renewable share on-site. • Grid-liability indicator is practical when planning off-grid sites. Integration of renewable energy sources in energy systems is crucial in achieving climate goals. Transformation of the power system – decentralization and prosumerism has led to the spread of domestic power plants taking part in the process. Mismatch problem of these predominantly grid-connected systems are typically described with load matching indicators. Most commonly used self-consumption and self-sufficiency metrics, though come with limits. One of the greatest is that they are monotone as the function of the capacity of photovoltaics implemented, making them uncapable of suggesting a technical optimum for system size. The scope of this study is to introduce two novel indicators with technical optima those can serve as a sizing principle for domestic photovoltaic plants for different approaches. First, self-production metric is introduced which allocates photovoltaic capacity that delivers maximum renewable utilization on-site and second, grid-liability reveals an optimum from the perspective of minimizing grid usage. A reference building is studied with two control approaches to observe both the existing and indicators. As a base scenario, a water heater with classical control is simulated, while in the second case, demand side management is achieved via improved rule-based control, aiming to store surplus photovoltaic power production. Simulations reveal that the optimum capacity of the photovoltaics from the perspective of both self-production and grid-liability is much lower than the capacity (of 6.57 kWp) that would cover the annual electricity demands of the observed household. In case of the traditional control, self-production leads to an optimal photovoltaic capacity of 4.38 kWp, while grid-liability to a 0.73 kWp. With improved control, optimal capacities are much closer, 2.92 and 2.19 kWp respectively. [ABSTRACT FROM AUTHOR]

This paper describes a methodology developed for determining the solar energy potential of large scale urban areas based on building typology. As a result of the method, the solar yield at the roof can be determined, taking into account shading obstructions and assembly distances. In the model the utilized as well as the collected energy is calculated, taking into account the energy losses by unused energy, energy delivery and energy storage. A main pillar of the method is the building typology that classifies buildings according to roof characteristics and other geometric factors influencing the domestic hot water demand. For each building type the following outputs are calculated: the solar yield, the maximum potential energy that can be produced by roof-integrated photovoltaic panels, the maximum potential energy that can be covered by solar thermal collectors and the realistic energy produced by solar thermal collectors taking into account economical considerations. Based on the model, urban-level solar potential estimations can be carried out with the use of digital cartography at low costs. Such an estimation is presented in a case study for Debrecen, Hungary, but the model can be adapted to any settlement with different building types or climatic conditions. [ABSTRACT FROM AUTHOR]

Highlights: [•] We set up a methodology for adaptation and mitigation strategies of cities. [•] The methodology is based on a generalized residential building typology. [•] Assessing the mitigation potential by refurbishment according to regulations. [•] Estimating the vulnerability to wind storms of residential buildings. [•] A case study is implemented in Hungary. [Copyright &y& Elsevier]

Energy production and consumption is a key element in future development which is influenced both by the technical possibilities available and by decision makers. Sustainability issues are closely linked in with energy policy, given the desire to increase the proportion of renewable energy. According to the Horizon 2020 climate and energy package, European Union (EU) member countries have to reduce the amount of greenhouse gases they emit by 20%, to increase the proportion of renewable energy to 20% and to improve energy efficiency by 20% by 2020. In this study we aim to assess the opportunities available to exploit solar radiation on roofs with Light Detection And Ranging (LiDAR) and photogrammetry techniques. The surveyed area was in Debrecen, the second largest city in Hungary. An aerial LiDAR survey was conducted with a density of 12 points/m 2 , over a 7 × 1.8 km wide band. We extracted the building and roof models of the buildings from the point cloud. Furthermore, we applied a low-cost drone (DJI Phantom with a GoPro camera) in a smaller area of the LiDAR survey and also created a 3D model: buildings and roof planes were identified with multiresolution segmentation of the digital surface models (DSM) and orthophoto coverages. Building heights and building geometry were also extracted and validated in field surveys. 50 buildings were chosen for the geodetic survey and the results of the accuracy assessment were extrapolated to other buildings; in addition to this, 100 building heights were measured. We focused primarily on the roofs, as these surfaces offer possible locations for thermal and photovoltaic equipment. We determined the slope and aspect of roof planes and calculated the incoming solar energy according to roof planes before comparing the results of the point cloud processing of LiDAR data and the segmentation of DSMs. Extracted roof geometries showed varying degrees of accuracy: the research proved that LiDAR-based roof-modelling is the best choice in residential areas, but the results of the drone survey did not differ significantly. Generally, both approaches can be applied, because the solar radiation values calculated were similar. The aerial techniques combined with the multiresolution processing demonstrated can provide a valuable tool to estimate potential solar energy. [ABSTRACT FROM AUTHOR]

[Display omitted] In the present research, a high-resolution, detailed electric load dataset was assessed, collected by smart meters from nearly a thousand households in Hungary, many of them single-family houses. The objective was to evaluate this database in detail to determine energy consumption profiles from time series of daily and annual electric load. After representativity check of dataset daily and annual energy consumption profiles were developed, applying three different clustering methods (k-means, fuzzy k-means, agglomerative hierarchical) and three different cluster validity indexes (elbow method, silhouette method, Dunn index) in MATLAB environment. The best clustering method for our examination proved to be the k-means clustering technique. Analyses were carried out to identify different consumer groups, as well as to clarify the impact of specific parameters such as meter type in the housing unit (e.g. peak, off-peak meter), day of the week (e.g. weekend, weekday), seasonality, geographical location, settlement type and housing type (single-family house, flat, age class of the building). Furthermore, four electric user profile types were proposed, which can be used for building energy demand simulation, summer heat load and winter heating demand calculation. [ABSTRACT FROM AUTHOR]