No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Modelling of Thermal Energy Demand in Smart Buildings
... Wall insulation from the inside is considered incorrect, but it cannot be completely ruled out. Regardless of the opinion and evidence of the majority, each landowner makes his own decision.The only case when the installation of insulation from the inside is fully justified is the insulation of the foundations, because there is soil on the outside [12].Insulation of exterior walls can reduce operating costs with individual heating or heating rooms with central heating. It should be insulated only from the outside, and it is recommended to use extruded or highdensity polystyrene foam as a heater. ...
... The output power at a given hour of the day calculates with the outside temperature at that time. For the next stage, a model for thermal demand of the buildings similar to the one presented in [22] will be used, providing a building adapted demand for the heat pump. ...
In recent years, the trend to provide more and more energy from renewable sources and less from conventional forms of electricity production reduces worldwide carbon emissions. In general, this is welcome but it also introduces new challenges. The diversity of electrical energy production grows and puts stress on the grid, its operators, and energy distribution planning. New ways for compensating the introduced instabilities are needed. Energy communities can address distributed production issues by adjusting the local demand as good as locally possible. This paper presents a methodology for simulating an energy community controller to test mechanism for smoothing grid load by aggregating available flexibilities of energy community members on a communal level. The controller tries to minimize load from or to the community by using different flexibilities and prediction algorithms within the community.
... To this direction, this paper develops a simple and accurate method based on ISO 52016-01 for the computation of hourly heating and cooling energy needs in different types of buildings. The method was firstly presented and evaluated for a multi-apartment block in [52]. While in this work, the model is evaluated in two different instances of residential buildings, the robustness of the method ensures its applicability for other types of premises as well. ...
Over the last decades, the growing energy consumption of commercial and residential buildings has considerably increased the energy-related carbon dioxide (CO
<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>
) emissions. At EU level, the Energy Performance of Buildings Directive (EPBD) has introduced the transformation of buildings into nearly zero energy buildings (nZEBs) that cover the majority of their low energy demand by on-site renewable energy sources. In this direction, the project PV-ESTIA “Enhancing storage integration in buildings with Photovoltaics” aims at developing and validating various optimal energy management strategies in buildings equipped with Photovoltaics (PV) and storage systems. One of the main requirements for the application of the developed strategies is the accurate computation of energy consumption, and particularly, of heating and cooling energy needs. In this paper, a simple and accurate model based on the “grey-box” concept is proposed for the computation of hourly thermal energy needs in different types of premises by using the standard ISO 52016-1:2017. The method’s performance is evaluated by comparing the results with those of other simulation programs for ten European cities with climatic variations. It is concluded that the proposed model presents high accuracy on the computation of the operative temperature, since it considers the air temperature, as well as the temperatures and the areas of the internal surfaces. Finally, any deviations with the other simulation tools are due to differences in the internal air temperature, weather data, as well as the approaches of ventilation and shading effects.
This ENTRANZE working paper presents the main results of the heating and cooling loads’ analysis and the energy demand for representative building types. The main con-tributors in this project are the end-use Efficiency Research Group of Politecnico di Mi-lano (IT), the National Renewable Energy Centre (ES) and the Energy Economics Group from the Vienna University of Technology. Based on the definition of building types3 and in partial overlap with the cost-optimality analysis4, the results obtained within this Task (2.2) for several reference cases are used to calibrate the thermal calculation module in the model Invert/EE-Lab. With this model the thermal loads and energy needs (for heating, cooling and DHW) of all building types in investigated EU countries can be derived, which is the basis for the development of scenarios and policy analyses in work package 4. The calculation activities presented in this paper are carried out using a dynamic tool (EnergyPlus) adopting a common methodology of simulation. There are 4 different base cases (single family house, apartment block, office and school) in 10 relevant European cities with high relevance and characterised by different climatic conditions. The selected base cases referred to are national building stocks from 1960 to 1970. An online data tool prepared by the whole ENTRANZE consortium reflecting detailed thermal charac-teristics of building types. ENTRANZE is a European project that in principle covers all EU-27 countries. The geo-graphical scope of the project is divided into target countries, focus countries and other countries. In terms of the scope, this deliverable (D2.3) focuses on the nine following countries: Austria, Bulgaria, Czech Republic, Finland, France, Germany, Italy, Romania and Spain. The report is structured as follows: Chapter 1 discusses the methodology used for esti-mating the thermal energy needs within the ENTRANZE Project. Furthermore, it defined the reference buildings and key climatic conditions. Chapter 2 shows the results obtained by the dynamic simulation. In Chapter 3, the results using a simplified tool (spreadsheet) based on the Standard EN ISO 13790 and the results from the dynamic simulation are compared with the outcomes of the thermal module in Invert/EE-Lab. Finally, the differ-ences of the described approaches are concluded and discussed.
Global Status Report 2017: Towards a zero-emission, efficient, and resilient buildings and construction sector
- Une Iea
Towards a zero-emission, efficient, and resilient buildings and construction sector
- Une Iea
IEA and UNE, "Global Status Report 2017: Towards a zero-emission,
efficient, and resilient buildings and construction sector," tech. rep.,
2017.
Directive (EU) 2018/844 of the European Parliament and of the Council of 30 May on the energy performance of buildings and Directive 2012/27/EU on energy efficiency
European Commission, "Directive (EU) 2018/844 of the European
Parliament and of the Council of 30 May on the energy performance
of buildings and Directive 2012/27/EU on energy efficiency," Official
Journal of the European Union, pp. 75-91, 2018.