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• 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]

• 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]

For active solar systems, such as solar collectors and PV panels it is important to estimate the possible thermal or electric energy production. The energy output of these devices depends on several factors. In this paper different models for estimating the available solar radiation were analyzed. The models selected for evaluation were the Liu-Jordan, the Hay and the Reindl et al. models. There are studies evaluating such models, but evaluations were not performed for Central and Eastern European locations, only for regions with different climatic conditions. Present study focuses on the Central and Eastern European region with it's specific continental climate. In order to evaluate the models, a major city of the region, Budapest, was selected. In Eastern Europe usually only the monthly and yearly values of solar radiation are available and applied in engineering practice. However, in many cases more detailed data are required. Hence the aim of this paper is also to highlight the importance of available daily data for modeling. For solar collectors and PV panels, the optimal orientation is to the south and the optimal tilt angle is assumed to be approximately 45° in the region. The calculated daily values were compared to measured data. The solar radiation was measured on a 45° tilted, south oriented surface in Budapest. The dataset used for the global radiation calculations was provided by the Hungarian Meteorological Service. [ABSTRACT FROM AUTHOR]

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]