In the last decades terms like Global Warming and Sustainable development have arisen. The anthropogenic green house gases emissions have raised the concentration of CO2 in the atmosphere to levels that might lead to a high increase in the average temperature in Earth. One of the most effective ways to fight against this phenomenon is to promote clean renewable energies. Among them, solar energy has the biggest developing potential and has proved to be an efficient and cost-effective energy source for different applications; one of them being the production of Domestic Hot Water and Space Heating. The aim of this Thesis is to study the possibilities to provide a single family house with hot water and space heating in an environmental friendly way. To do so, a solar system with biomass support will be designed for a single family house in northern Spain. The building has total energy demand of 20.5 MWh a year, of which 18 MWh correspond to space heating and 2.5 MWh to domestic hot water. The chosen solution for the building includes 12 solar collectors with a total area of 23.4 m2, a biomass boiler with a nominal power of 30 kW and a 32 kW oil boiler. Additionally, a radiant floor system was used as it perfectly adapts to the low temperature of the solar system. The result is an installation working with an 85% of renewable energies. This high share of renewable energy entails savings of 2,000 liters of oil a year, avoiding the emission of 4.5 tones of CO2 to the atmosphere every year. The economic calculations show that the pay back of the investment is 10 years with a Internal Rate of Return of 13%. Therefore, it can be said that, for this particular building and due to the governmental subsidies granted, solar energy is a cost effective alternative to provide the basic energy needs of a house.

In Sweden, there are about 0.5 million single-family houses that are heated by electricity alone, and rising electricity costs force the conversion to other heating sources such as heat pumps and wood pellet heating systems. Pellet heating systems for single-family houses are currently a strongly growing market. Future lack of wood fuels is possible even in Sweden, and combining wood pellet heating with solar heating will help to save the bio-fuel resources. The objectives of this thesis are to investigate how the electrically heated single-family houses can be converted to pellet and solar heating systems, and how the annual efficiency and solar gains can be increased in such systems. The possible reduction of CO-emissions by combining pellet heating with solar heating has also been investigated. Systems with pellet stoves (both with and without a water jacket), pellet boilers and solar heating have been simulated. Different system concepts have been compared in order to investigate the most promising solutions. Modifications in system design and control strategies have been carried out in order to increase the system efficiency and the solar gains. Possibilities for increasing the solar gains have been limited to investigation of DHW-units for hot water production and the use of hot water for heating of dishwashers and washing machines via a heat exchanger instead of electricity (heat-fed appliances). Computer models of pellet stoves, boilers, DHW-units and heat-fed appliances have been developed and the parameters for the models have been identified from measurements on real components. The conformity between the models and the measurements has been checked. The systems with wood pellet stoves have been simulated in three different multi-zone buildings, simulated in detail with heat distribution through door openings between the zones. For the other simulations, either a single-zone house model or a load file has been used. Simulations were carried out for Stockholm, Sweden, but for the simulations with heat-fed machines also for Miami, USA. The foremost result of this thesis is the increased understanding of the dynamic operation of combined pellet and solar heating systems for single-family houses. The results show that electricity savings and annual system efficiency is strongly affected by the system design and the control strategy. Large reductions in pellet consumption are possible by combining pellet boilers with solar heating (a reduction larger than the solar gains if the system is properly designed). In addition, large reductions in carbon monoxide emissions are possible. To achieve these reductions it is required that the hot water production and the connection of the radiator circuit is moved to a well insulated, solar heated buffer store so that the boiler can be turned off during the periods when the solar collectors cover the heating demand. The amount of electricity replaced using systems with pellet stoves is very dependant on the house plan, the system design, if internal doors are open or closed and the comfort requirements. Proper system design and control strategies are crucial to obtain high electricity savings and high comfort with pellet stove systems. The investigated technologies for increasing the solar gains (DHW-units and heat-fed appliances) significantly increase the solar gains, but for the heat-fed appliances the market introduction is difficult due to the limited financial savings and the need for a new heat distribution system. The applications closest to market introduction could be for communal laundries and for use in sunny climates where the dominating part of the heat can be covered by solar heating. The DHW-unit is economical but competes with the internal finned-tube heat exchanger which is the totally dominating technology for hot water preparation in solar combisystems for single-family houses. / <p>QC 20100916</p>

Předkládaná práce se zabývá způsobem ohřevu teplé vody v novém bytovém domě. Teoretická část práce se věnuje jednotlivým způsobům ohřevu teplé vody, popisuje zásobníkové i průtokové způsoby ohřevu, přičemž hlavní důraz je kladen na variantu se zásobníky teplé vody. Hlavním cílem práce je posoudit dvě nabízející se řešení zajištění ohřevu vody ve zvoleném objektu, tedy elektrické zásobníkové ohřevy v jednotlivých bytech a centrální ohřev teplé vody nepřímo napojeným na plynové kotle, a vyhodnotit výhodnější variantu.

This thesis's main objective is to conduct a comparison study between measured values and simulated results of a demonstrator, of the intelligent home energy management (iHEM) project. The comparison helps to validate the simulation. TRNSYS software is used for the design. In this study, only the thermal energy side of the project is considered. In which system-level (both domestic hot water (DHW), space heating (SH)) and component level (solar collector, gas boiler) are considered as the parameters to compare. An attempt is made to optimize both system-level and component-level simulation outputs with measured values by adopting measured boundary conditions as simulation inputs.During the comparison, the DHW loop simulation design is modified. The measured data were given as input files for simulation, replacing the estimated values used before. This is done to optimize the simulation output with measured data. In the space heating loop (SH), the simulated building model’s parameters were changed to optimize the SH demand. After the system-level validation and optimization, the component level comparison is carried out. For this, the simulation output of solar thermal collectors and gas boiler are compared with measured values. The solar collector loop in the simulation is modified to optimize the simulated results. The seasonal and yearly efficiencies of the collector have been calculated. Solar supply fraction and gas boiler supply fraction is also determined. For the comparison, graphs are plotted for three different weeks, representing the spring, summer, and winter months of 2018.The final optimized simulation output of DHW demand is 7% less than the measured value. Even after optimizing the Space heating loop (SH), the simulated building demand is 17% more heat than the demonstrator building. The simulation's solar collector output is optimized close to the measured values. The simulated gas boiler produces 19% more than the demonstrator system to meet excess SH demand in the simulation (including losses). The overall yearly collector efficiency calculated for measured and simulated values are 58% and 50%, respectively. The estimated solar collector supply fraction and gas boiler supply fraction is 26%, 76% for measured, and 23%, 81% for simulation, respectively.

This thesis's main objective is to conduct a comparison study between measured values and simulated results of a demonstrator, of the intelligent home energy management (iHEM) project. The comparison helps to validate the simulation. TRNSYS software is used for the design. In this study, only the thermal energy side of the project is considered. In which system-level (both domestic hot water (DHW), space heating (SH)) and component level (solar collector, gas boiler) are considered as the parameters to compare. An attempt is made to optimize both system-level and component-level simulation outputs with measured values by adopting measured boundary conditions as simulation inputs.During the comparison, the DHW loop simulation design is modified. The measured data were given as input files for simulation, replacing the estimated values used before. This is done to optimize the simulation output with measured data. In the space heating loop (SH), the simulated building model’s parameters were changed to optimize the SH demand. After the system-level validation and optimization, the component level comparison is carried out. For this, the simulation output of solar thermal collectors and gas boiler are compared with measured values. The solar collector loop in the simulation is modified to optimize the simulated results. The seasonal and yearly efficiencies of the collector have been calculated. Solar supply fraction and gas boiler supply fraction is also determined. For the comparison, graphs are plotted for three different weeks, representing the spring, summer, and winter months of 2018.The final optimized simulation output of DHW demand is 7% less than the measured value. Even after optimizing the Space heating loop (SH), the simulated building demand is 17% more heat than the demonstrator building. The simulation's solar collector output is optimized close to the measured values. The simulated gas boiler produces 19% more than the demonstrator system to meet excess SH demand in the simulation (including losses). The overall yearly collector efficiency calculated for measured and simulated values are 58% and 50%, respectively. The estimated solar collector supply fraction and gas bo

In dieser Arbeit wird ein Modell für die Simulation des Verbraucherverhaltens in Haushalten entwickelt. Das Ziel ist die Erstellung von Lastprofilen für den Strom- und Wasserverbrauch. Das Modell wird in einem Programm implementiert. Die Ergebnisse werden anschließend validiert und verschiedene Kenngrößen mit Literaturwerten verglichen. Abschließend wird eine Parameterstudie durchgeführt, um den Einfluss verschiedener Faktoren wie z.B. das Arbeitszeitmodell oder die Feiertagsmodellierung auf Lastprofile zu quantifizieren. Das Modell basiert auf einem Bedürfnismodell aus der Psychologie und ermöglicht den Verzicht auf die Errechnung von Aktivitäts-Wahrscheinlichkeitsverteilungen. / In this thesis a model for the simulation of the behaviour of people in residential households is introduced. The goal is to generate load profiles for residential electricity and water consumption. The model is implemented as a Windows program. The results are validated and various metrics are compared with literature values. A parameter study is performed to quantify the influence of various factors such as the working hours or the influence of holidays on the load profile. The model is based on a desire model from the field of psychology and makes it possible to avoid calculating any probabilty distributions.

In dieser Arbeit wird ein Modell für die Simulation des Verbraucherverhaltens in Haushalten entwickelt. Das Ziel ist die Erstellung von Lastprofilen für den Strom- und Wasserverbrauch. Das Modell wird in einem Programm implementiert. Die Ergebnisse werden anschließend validiert und verschiedene Kenngrößen mit Literaturwerten verglichen. Abschließend wird eine Parameterstudie durchgeführt, um den Einfluss verschiedener Faktoren wie z.B. das Arbeitszeitmodell oder die Feiertagsmodellierung auf Lastprofile zu quantifizieren. Das Modell basiert auf einem Bedürfnismodell aus der Psychologie und ermöglicht den Verzicht auf die Errechnung von Aktivitäts-Wahrscheinlichkeitsverteilungen.:Inhaltsverzeichnis 1 Einleitung 1.1 Motivation 1.2 Ziel der Arbeit 2 Einordnung 3 Wissensstand 3.1 Lastprofile 3.1.1 VDEW-Standard-Lastprofile 3.1.2 Referenzlastprofile von Ein- und Mehrfamilienhäusern für den Einsatz von KWK-Anlagen (VDI 4655) 3.1.3 BDEW-Standardlastprofile Gas 3.1.4 IEA Annex 42 Lastkurven 3.2 Lastprofilgeneratoren 3.2.1 Methoden 3.2.2 Auswahl der Beispiele 3.2.3 Lastprofilgenerator nach Stokes 3.2.4 Lastprofilgenerator nach IEA Annex 42 3.2.5 Lastprofilgenerator nach Jordan 3.2.6 Lastprofilgenerator nach NREL 3.2.7 Lastprofilgenerator nach Walker und Pokoski 3.2.8 Lastprofilgenerator nach Capasso 3.2.9 Lastprofilgenerator nach Widen et al. 3.2.10 Lastprofilgenerator nach Richardson 3.2.11 Lastprofilgenerator nach Metz 3.2.12 Lastprofilgenerator nach Fischer 3.2.13 Zusammenfassung der Lastprofilgeneratoren 3.3 Verhaltenssimulation 3.3.1 Rational Choice Model 3.3.2 Verhaltensmodell nach D. Dörner 3.4 Hausinfrastrukturmodelle 3.4.1 Heizung und Kühlung 3.4.2 Modellierung in TRNSYS 4 Das Modell des bLPG 4.1 Bedürfnismodell 4.2 Modellierung eines einzelnen Haushalts 4.2.1 Desires 4.2.2 Person 4.2.3 Load Types 4.2.4 Devices 4.2.5 Time Profile 4.2.6 Time Limits 4.2.7 Affordances 4.2.8 Berechnungsbeispiel Aktivitätenauswahl 4.2.9 Zusammenfassung der Modellierung eines Haushalts 4.3 Verbesserung der Modellqualität 4.3.1 Locations 4.3.2 Holidays 4.3.3 Geographic Locations 4.3.4 Subaffordances 4.3.5 Temperature Profiles und Date Based Profiles 4.3.6 Vacations 4.3.7 Autonome Geräte 4.4 Houses und Settlements 4.4.1 House Types 4.5 Abstraktion der Geräte 4.6 Abstraktion Haushaltsdefinition 4.7 Elemente für Auswertungen 4.8 Zusammenfassung des Modells des bLPG 5 Implementierung 5.1 Allgemeines 5.2 Historie 5.3 Features 5.4 Struktur 5.5 User Interface 5.6 Database 5.7 CalcController 5.8 Calculation 5.8.1 Aktivitätswahl 5.8.2 Protokollierung 5.8.3 House Infrastructure 5.9 ChartCreator 5.10 SimulationEngine.Exe 5.11 Verwendete Bibliotheken 5.12 Zusammenfassung der Implementierung 6 Modellierung der vordefinierten Haushalte 6.1 Datenbasis und Modellierung 6.2 Vordefininierte Elemente 6.3 Namensschema 6.4 Erfahrungen bei der Erstellung der vordefinierten Haushalte 6.5 Zusammenfassung 7 Validierung 7.1 Einzelner Haushalt 7.1.1 Aktivitäten - Rasterdiagramme 7.1.2 Aktivitäten - Zeit pro Affordanz 7.1.3 Summe des Stromverbrauchs 7.1.4 Verlauf des Lastprofils 7.1.5 Wasserverbrauch 7.1.6 Integration von Photovoltaik 7.1.7 Lichtbedarf 7.1.8 Zusammenfassung CHR03 7.2 Vordefinierte Haushalte 7.2.1 Stromverbrauch 7.2.2 Verhaltensgesteuerter Anteil am Stromverbrauch 7.2.3 Zeitverbrauch der Aktivitäten 7.2.4 Eigenverbrauchsquote mit einer Photovoltaik-Anlage 7.2.5 Jahresdauerlinien 7.3 Validierung einer Siedlung 7.3.1 Gleichzeitigkeitsfaktor des Stromverbrauchs 7.3.2 Vergleich einer Siedlung mit dem H0-Profil 7.4 Fazit 8 Anwendungsmöglichkeiten und Ergebnisse 8.1 Integration von Photovoltaik und Batterien 8.2 Parameterstudie 8.2.1 Vergleichskriterien 8.2.2 Einfluss von Brückentagen 8.2.3 Einfluss von Urlaubsreisen 8.2.4 Einfluss des Rentneranteils 8.2.5 Einfluss von Schichtarbeitern 8.2.6 Einfluss von Arbeitslosigkeit 8.2.7 Einfluss der Energieintensitätseinstellung 8.2.8 Einflussgröße Beleuchtung 8.3 Zusammenfassung der Parameterstudie 9 Ausblick 9.1 Verbesserungspotenziale der Implementierung 9.2 Verbesserungspotenziale der Datenbasis 9.3 Zusammenfassung des Ausblicks 10 Zusammenfassung Anhänge Anhang A Website Anhang B LoadProfileGenerator Manual Literaturverzeichnis / In this thesis a model for the simulation of the behaviour of people in residential households is introduced. The goal is to generate load profiles for residential electricity and water consumption. The model is implemented as a Windows program. The results are validated and various metrics are compared with literature values. A parameter study is performed to quantify the influence of various factors such as the working hours or the influence of holidays on the load profile. The model is based on a desire model from the field of psychology and makes it possible to avoid calculating any probabilty distributions.:Inhaltsverzeichnis 1 Einleitung 1.1 Motivation 1.2 Ziel der Arbeit 2 Einordnung 3 Wissensstand 3.1 Lastprofile 3.1.1 VDEW-Standard-Lastprofile 3.1.2 Referenzlastprofile von Ein- und Mehrfamilienhäusern für den Einsatz von KWK-Anlagen (VDI 4655) 3.1.3 BDEW-Standardlastprofile Gas 3.1.4 IEA Annex 42 Lastkurven 3.2 Lastprofilgeneratoren 3.2.1 Methoden 3.2.2 Auswahl der Beispiele 3.2.3 Lastprofilgenerator nach Stokes 3.2.4 Lastprofilgenerator nach IEA Annex 42 3.2.5 Lastprofilgenerator nach Jordan 3.2.6 Lastprofilgenerator nach NREL 3.2.7 Lastprofilgenerator nach Walker und Pokoski 3.2.8 Lastprofilgenerator nach Capasso 3.2.9 Lastprofilgenerator nach Widen et al. 3.2.10 Lastprofilgenerator nach Richardson 3.2.11 Lastprofilgenerator nach Metz 3.2.12 Lastprofilgenerator nach Fischer 3.2.13 Zusammenfassung der Lastprofilgeneratoren 3.3 Verhaltenssimulation 3.3.1 Rational Choice Model 3.3.2 Verhaltensmodell nach D. Dörner 3.4 Hausinfrastrukturmodelle 3.4.1 Heizung und Kühlung 3.4.2 Modellierung in TRNSYS 4 Das Modell des bLPG 4.1 Bedürfnismodell 4.2 Modellierung eines einzelnen Haushalts 4.2.1 Desires 4.2.2 Person 4.2.3 Load Types 4.2.4 Devices 4.2.5 Time Profile 4.2.6 Time Limits 4.2.7 Affordances 4.2.8 Berechnungsbeispiel Aktivitätenauswahl 4.2.9 Zusammenfassung der Modellierung eines Haushalts 4.3 Verbesserung der Modellqualität 4.3.1 Locations 4.3.2 Holidays 4.3.3 Geographic Locations 4.3.4 Subaffordances 4.3.5 Temperature Profiles und Date Based Profiles 4.3.6 Vacations 4.3.7 Autonome Geräte 4.4 Houses und Settlements 4.4.1 House Types 4.5 Abstraktion der Geräte 4.6 Abstraktion Haushaltsdefinition 4.7 Elemente für Auswertungen 4.8 Zusammenfassung des Modells des bLPG 5 Implementierung 5.1 Allgemeines 5.2 Historie 5.3 Features 5.4 Struktur 5.5 User Interface 5.6 Database 5.7 CalcController 5.8 Calculation 5.8.1 Aktivitätswahl 5.8.2 Protokollierung 5.8.3 House Infrastructure 5.9 ChartCreator 5.10 SimulationEngine.Exe 5.11 Verwendete Bibliotheken 5.12 Zusammenfassung der Implementierung 6 Modellierung der vordefinierten Haushalte 6.1 Datenbasis und Modellierung 6.2 Vordefininierte Elemente 6.3 Namensschema 6.4 Erfahrungen bei der Erstellung der vordefinierten Haushalte 6.5 Zusammenfassung 7 Validierung 7.1 Einzelner Haushalt 7.1.1 Aktivitäten - Rasterdiagramme 7.1.2 Aktivitäten - Zeit pro Affordanz 7.1.3 Summe des Stromverbrauchs 7.1.4 Verlauf des Lastprofils 7.1.5 Wasserverbrauch 7.1.6 Integration von Photovoltaik 7.1.7 Lichtbedarf 7.1.8 Zusammenfassung CHR03 7.2 Vordefinierte Haushalte 7.2.1 Stromverbrauch 7.2.2 Verhaltensgesteuerter Anteil am Stromverbrauch 7.2.3 Zeitverbrauch der Aktivitäten 7.2.4 Eigenverbrauchsquote mit einer Photovoltaik-Anlage 7.2.5 Jahresdauerlinien 7.3 Validierung einer Siedlung 7.3.1 Gleichzeitigkeitsfaktor des Stromverbrauchs 7.3.2 Vergleich einer Siedlung mit dem H0-Profil 7.4 Fazit 8 Anwendungsmöglichkeiten und Ergebnisse 8.1 Integration von Photovoltaik und Batterien 8.2 Parameterstudie 8.2.1 Vergleichskriterien 8.2.2 Einfluss von Brückentagen 8.2.3 Einfluss von Urlaubsreisen 8.2.4 Einfluss des Rentneranteils 8.2.5 Einfluss von Schichtarbeitern 8.2.6 Einfluss von Arbeitslosigkeit 8.2.7 Einfluss der Energieintensitätseinstellung 8.2.8 Einflussgröße Beleuchtung 8.3 Zusammenfassung der Parameterstudie 9 Ausblick 9.1 Verbesserungspotenziale der Implementierung 9.2 Verbesserungspotenziale der Datenbasis 9.3 Zusammenfassung des Ausblicks 10 Zusammenfassung Anhänge Anhang A Website Anhang B LoadProfileGenerator Manual Literaturverzeichnis

This master’s thesis deals with utilization of waste heat from heating plant Spitalka. The aim of the thesis is to explain the general principle of the operation of the heating plants, respectively the heating circuit, then to describe the operation of heating plant Spitalka and to try to identify possible sources of waste heat. Other goals are to make the calculation of waste heat and to make the proposal for its utilization. The final aim of the thesis was to design technological device for utilization of waste heat and to carry out economic evaluation. The master’s thesis describes the principle of functioning of the heating circuit. It explains the issue of combined heat and power production, the principle of functioning of the main technological elements, but also the ecology of operation or distribution of heat through the district heating. Then there is a description of the heating plant Spitalka. The thesis also deals with the water treatment and the description of the technological circuit from the beginning to the distribution to the customer. Next, the waste heat source is identified as water in a closed cooling circuit. The amount of this heat energy is calculated and suggestions for its possible utilization are made. As an application, there are selected two systems, heating and domestic hot water heating. The heating is made by heat pump. Based on the calculations, a heating system using two heat pumps in a bivalent way of connection was designed. In conclusion, the results of the design of the heating system are summarized and an economic evaluation is carried out.

The aim of this master project is to design a nzeb kindergarten and primary school in Škrdlovice. The building has three parts: kindergarten and primary school with 2 above–ground floors and basements are connected with a single canteen. The canteen has a flat extensive green roof, while the kindergarten and primary school have saddle roof. The kindergarten has two identical floors with playrooms, locker rooms, bed and toy storage, teacher’s office, and bathrooms. First floor of the primary school contains locker room, teacher’s’ offices, it classroom, afterschool centre, and toilets. Three classrooms, headmaster’s office, and toilets are in the second floor. The building is designed using Xella building system. The external load–bearing walls, slabs, and internal non–bearing walls are made of aerated concrete blocks. The internal load–bearing are made of lime–sand blocks. The building is insulated with non–fibrous mineral panels. The project includes design of lightning, HVAC, DHW, and photovoltaics systems. The project also includes a study of three structural details including 3D models in BIM software and their thermal assessment. The project was designed using BIM software Revit.