The Mbesese Initiative for Sustainable Development (MISD) is a group aiming to help eliminate extreme poverty in Africa by creating educational opportunity. One project that the group is currently doing is to build Same Polytechnic College (SPC) in Tanzania. As part of the project, this thesis aims to study and analyze the electrical power system and distribution for the college. Based on the projected load profile of the college and high potential for solar generation in Tanzania, several different power systems utilizing local utility AC electricity and/or photovoltaic (PV) DC electricity are explored and simulated for their feasibility and performance. Analysis of each design is presented and compared to determine the most viable system based on reliability, costs, and space. Results of the study indicate that over designing the DC system may generate wasteful energy while under designing the DC system may cause the overall system to rely heavily on the AC power grid. Ultimately, this thesis demonstrates that integrating a 58.9% DC system mixed with AC system offers the highest payback while efficiently utilizing the PV system, the battery system, and provided land.

Yes / Electricity Suppliers in competitive electricity markets commonly respond to prices changes which are fluctuating over time, but most consumers respond to the price changes as reflected on their electricity bills. Almost all consumers pay fixed tariffs for their consumption without distinctions based on usage time, so these consumers have had no incentives to reduce their use during the peak times. This paper aims to analyze the influence of different tariff schemes on consumer behaviours in UK domestic buildings. A realistic half hourly electricity load profile for different types of UK households that based mainly on public reports and statistics has been generated. This load profile data were used to help calculate the expected change in consumers' bills under standard tariffs offered from different suppliers to what the cost of electricity would be under time varying tariff (economy7 tariff) and to estimate of how much consumers would shift their load in response to price changes without changing total consumption, for which the results are presented and discussed / MSCRC

<p>This thesis gives a systematic description of theEnvironmental Load Profile (ELP), an environmental assessmenttool developed for the urban environment. The purpose of thework was to improve the stringency of the system boundaries andfunctional units of the tool. This was achieved by putting theELP structure in the context of Life Cycle Assessment (LCA)with a special emphasis on system boundaries. To create animproved scientific base for the ELP, a comparative study wasconducted using an evaluative framework for conceptual andanalytical approaches. Here, the ELP tool is compared with foursimilar environmental assessment tools for the builtenvironment.</p><p>Since, energy use in the operation phase is an importantfactor for the overall environmental performance of buildings,a sensitivity analysis was performed to investigate how theselection of heat and electricity mix affects the results of anenvironmental assessment of buildings. Four modes ofelectricity production and two modes of heat production wereapplied on three buildings with different technical systems intheir heat supply. The results show that the choice ofelectricity mix has a great influence on the outcome of anenvironmental assessment (EA) and it is suggested that both anaverage and marginal electricity mix should be applied inEA´s of the built environment. Further, it is argued thatconsequences of assumptions made should be explicitlycommunicated in the EA report, to allow the decision-makersrather than the analysts to make the final evaluation.</p><p>The ELP is primarily developed to follow up theenvironmental goal‘twice as good’and assess theenvironmental performance of Hammarby Sjöstad, a newcity-district in southern Stockholm. The city-district is builtas a continuation of the inner Stockholm and the first part ofthe project, called Sickla Udde, is nearly finished. The ELPtool was applied in a first case study to answer the questionof how far Sickla Udde has reached in achieving the goal. Theassessment indicates that compared to a reference districtbased on the technology used in 1990, the environmentalperformance of Sickla Udde has reached the goal‘twice asgood’for some environmental load categories and 30percent for others. Although these findings are preliminary,they indicate a development in the right direction. Measurestaken contributing to largest environmental improvements are: amore efficient energy production (improved district heating)and use (e.g. lower U-values in the buildings, energy efficientappliances, heat exchange of ventilation air) and improvedsewage treatment. The results also demonstrate that theenvironmental load from domestic transports can be of the samemagnitude as from the buildings situated within thecity-district. Hence, resources spent to decrease environmentalload in the planning process should primarily be divoted toimproving domestic transportation systems and on optimising theoperational phase of the buildings.</p><p><b>Keywords:</b>environmental assessment, urban district,environmental load profile, Hammarby Sjöstad, life cycleassessment, LCA, environmental management, builtenvironment</p>

Morgongåva is an urban centre in Sweden, with several challenges in the electrical power grid. In order to use the power grid more efficiently, this report investigates potentials of installing a battery energy storage system (BESS). Focus lies on finding economic and technical benefits of reducing power peaks, which occur during high demand hours when transmitting energy is more expensive. This method is referred to as peak shaving. Further, economic calculations if installing a BESS are based on electricity pricing data. Calculations regarding technical benefits are based on net power demand data. Further, the study shows that the usage of the grid, which was measured with the load factor, would increase and thus allow installation of more power sources and connecting more load to the grid. The load factor was estimated to increase by an average of 2.12 percent each month in 2019. In one year, the economic profit was estimated to be 91,000 kr. The conclusion is that there are economic profits for Sala-Heby Energi of installing a BESS, but more importantly a BESS has technical consequences in the power grid. Where technical benefits are important in order to reach the goals of Agenda 2030 but also to obtain a more reliable grid for the customers. A sensitivity analysis shows that the model is robust. Thus, the conclusion is that Sala-Heby Energi and the local electricity grid in Morgongåva would benefit from installing a BESS.

This thesis gives a systematic description of theEnvironmental Load Profile (ELP), an environmental assessmenttool developed for the urban environment. The purpose of thework was to improve the stringency of the system boundaries andfunctional units of the tool. This was achieved by putting theELP structure in the context of Life Cycle Assessment (LCA)with a special emphasis on system boundaries. To create animproved scientific base for the ELP, a comparative study wasconducted using an evaluative framework for conceptual andanalytical approaches. Here, the ELP tool is compared with foursimilar environmental assessment tools for the builtenvironment. Since, energy use in the operation phase is an importantfactor for the overall environmental performance of buildings,a sensitivity analysis was performed to investigate how theselection of heat and electricity mix affects the results of anenvironmental assessment of buildings. Four modes ofelectricity production and two modes of heat production wereapplied on three buildings with different technical systems intheir heat supply. The results show that the choice ofelectricity mix has a great influence on the outcome of anenvironmental assessment (EA) and it is suggested that both anaverage and marginal electricity mix should be applied inEA´s of the built environment. Further, it is argued thatconsequences of assumptions made should be explicitlycommunicated in the EA report, to allow the decision-makersrather than the analysts to make the final evaluation. The ELP is primarily developed to follow up theenvironmental goal‘twice as good’and assess theenvironmental performance of Hammarby Sjöstad, a newcity-district in southern Stockholm. The city-district is builtas a continuation of the inner Stockholm and the first part ofthe project, called Sickla Udde, is nearly finished. The ELPtool was applied in a first case study to answer the questionof how far Sickla Udde has reached in achieving the goal. Theassessment indicates that compared to a reference districtbased on the technology used in 1990, the environmentalperformance of Sickla Udde has reached the goal‘twice asgood’for some environmental load categories and 30percent for others. Although these findings are preliminary,they indicate a development in the right direction. Measurestaken contributing to largest environmental improvements are: amore efficient energy production (improved district heating)and use (e.g. lower U-values in the buildings, energy efficientappliances, heat exchange of ventilation air) and improvedsewage treatment. The results also demonstrate that theenvironmental load from domestic transports can be of the samemagnitude as from the buildings situated within thecity-district. Hence, resources spent to decrease environmentalload in the planning process should primarily be divoted toimproving domestic transportation systems and on optimising theoperational phase of the buildings. <b>Keywords:</b>environmental assessment, urban district,environmental load profile, Hammarby Sjöstad, life cycleassessment, LCA, environmental management, builtenvironment / NR 20140805

Access to electricity might in some parts of the world seem evident. However, Ethiopia struggles to provide its large and growing population with electricity. Although around all the households in the capital Addis Ababa are connected to the electricity grid, the grid is unreliable and results in daily outages. As the photovoltaic (PV) potential in Addis Ababa on the other hand is great, this thesis examines the feasibility and profitability of decentralized PV adoption with battery and hydrogen storage respectively. Based on an ongoing construction project in the sub-city Yeka, Addis Ababa, a reference building was used to simulate the PV systems with battery and hydrogen storage. Furthermore, a load profile based on time-use diaries was developed and used in the simulations, as data on household electric consumption was non-existent. The load profile resulted in an average daily use of 1341 kWh and a 165 kW peak for all of the 130 apartments in the reference building. The results of the simulations indicated that neither of the two systems were feasible nor profitable to implement on the reference building. The PV-system with battery storage was cheaper and required less installed PV capacity, however the cost of energy for both systems was significantly higher than the current cost of energy in Ethiopia. The installed PV capacity of both systems exceeded the maximum capacity that was feasible on the reference building.

Yes / This paper presents a method of generating realistic electricity load profile data for the UK domestic buildings. The domestic space heating and domestic hot water have been excluded in this study. The information and results of previous investigations and works that is available in public reports and statistics have been used as input data when modeling of domestic energy consumption. A questionnaire survey was conducted to find out what occupants do in different times of the day in order to get probabilistic estimates of usage of electrical household. The daily energy demand load profile of each appliance can be predicted using this method. A measured data set is also applied for comparison, and verification. Our analysis shows that the generated load profiles have a good agreement with real data. The daily load profile from individual dwelling to community can be predicted using this method.

Efficiency is a driving constraint for electrical power systems as global energy demands are ever increasing. Followed by the introduction of diesel generators, electricity has become available in more locations than ever. However, operating a diesel generator on its own is not the most energy efficient. This is because the high crest factor loads, of many applications, decrease the fuel efficiency of a hydrocarbon generator. To understand this, we need to understand how an electrical load affects a generator. Starting with a load profile, a system designer must choose a generator to meet peak demand, marking the first instance where a load profile has influence over a generator. This decision will insure that brownouts do not occur, but, this will lead to poor energy efficiency. We say this because a generator is most energy efficient under heavier loads, meaning, during lighter loads, more fuel will be consumed to produce the same amount of energy. While this may be fine if the peak load was close to the average load, however, the actual crest factor for a typical residential load profile is much higher. This gap between peak and average load means that a generator will spend most of its time operating at its most inefficient point. To compensate for this, and reduce fuel consumption, the Mechatronics Lab at Virginia Tech has developed a mobile hybrid power system (MHPS) to address this problem. The solution was to augment a diesel generator with a battery pack. This allowed us to constrain the generator so that it only operates with fixed efficiency. It is the theory behind this system that will be covered in this thesis. / Master of Science

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