The problem addressed in this thesis is the delevitation modelling of an active magnetic bearing (AMB) supported rotor. A system model needs to be developed that models the highly non-linear interaction of the rotor with the backup bearings (BBs) during a delevitation event. The model should accurately predict forward and backward whirl as well as the system forces experienced. To this end, the severity of rotor delevitation events should be characterised. The contributions of the research include a more comprehensive model of a cross-coupled flexible rotor-AMB-BB system, a method to obtain repeatable experimental results, two methods for quantifying the severity of a rotor-drop (RDQ and Vval) and the simulation of forward whirl. A simulation model (BBSim) was developed to predict the behaviour of a rotor in rolling element BBs in an AMB system during a rotor delevitation event. The model was validated using a novel rotor delevitation severity quantification method (Vval) to compare experimental and simulated results. In this study the force impulse values as the rotor impacts the BBs are seen as critical to monitor, as an indication of rotor drop severity. The novel quantification method was verified by comparing the impulse values of delevitation events to the values obtained for the same delevitation events using the novel quantification method. The simulation model (BBSim) was developed by integrating and cross coupling various simpler models to obtain a model that could accurately predict the behaviour of a rotor during a delevitation event. A plethora of simulation results were generated for various initial conditions. The simulation results were used to perform a parametric study, from which the effects that certain design parameters have on the severity of rotor delevitation events are determined. The novel quantification method results presented in this research compared well to the impulse values. Since most AMB systems that have BBs do not have force measurement capabilities, the development of the novel quantification method enables the quantification of rotor drop severity solely based on position data. The simulation model BBSim was found to accurately predict the behaviour of a rotor during a delevitation event. The parametric study completed using BBSim revealed that the severity of rotor delevitation events is less sensitive to the bearing stiffness than the bearing damping. The parametric study also found that the severity of a delevitation event is slightly sensitive to the angle of delevitation. The friction factor between the rotor and the inner-race of the rolling element bearings moderately influences the severity of the rotor delevitation event. The inertia of the rolling element bearing’s inner-race and balls influences the behaviour in a complex manner, where the inertia should be kept as low as possible for actively braked rotors, and should be higher for free running rotors. The unbalance of the rotor plays a major role in the severity of rotor delevitation events. A rotor with a high unbalance usually tends to go into forward whirl, whereas low unbalance could promote the development of backward whirl if the inertia of the inner-race and the friction factor between the inner-race and the rotor are excessively large. Some of the recommended future work to be done on BBSim Include investigations into load sharing, various failure modes of AMBs, the effect that rotor circularity has on the stability of AMB control and an investigation into forward whirl. Envisaged improvements that can be made to BBSim are the inclusion of an axial rotor AMB and BB model, cross-coupled with the existing BBSim model. Other improvements could be the inclusion of thermal modelling and the ability to simulate other types of BBs. Future experimental work could include a comparison of simulated and experimental results of larger systems and using the developed quantification methods to refine the defined threshold values for the safe operation of AMB systems. / PhD, North-West University, Potchefstroom Campus, 2014 / Appendix C is attached seperately because of the size of the pdf (920 MB). If it is too large to download, please loan the hardcopy with the CD from the Loan desk in the Ferdinand Postma Library.

The problem addressed in this thesis is the delevitation modelling of an active magnetic bearing (AMB) supported rotor. A system model needs to be developed that models the highly non-linear interaction of the rotor with the backup bearings (BBs) during a delevitation event. The model should accurately predict forward and backward whirl as well as the system forces experienced. To this end, the severity of rotor delevitation events should be characterised. The contributions of the research include a more comprehensive model of a cross-coupled flexible rotor-AMB-BB system, a method to obtain repeatable experimental results, two methods for quantifying the severity of a rotor-drop (RDQ and Vval) and the simulation of forward whirl. A simulation model (BBSim) was developed to predict the behaviour of a rotor in rolling element BBs in an AMB system during a rotor delevitation event. The model was validated using a novel rotor delevitation severity quantification method (Vval) to compare experimental and simulated results. In this study the force impulse values as the rotor impacts the BBs are seen as critical to monitor, as an indication of rotor drop severity. The novel quantification method was verified by comparing the impulse values of delevitation events to the values obtained for the same delevitation events using the novel quantification method. The simulation model (BBSim) was developed by integrating and cross coupling various simpler models to obtain a model that could accurately predict the behaviour of a rotor during a delevitation event. A plethora of simulation results were generated for various initial conditions. The simulation results were used to perform a parametric study, from which the effects that certain design parameters have on the severity of rotor delevitation events are determined. The novel quantification method results presented in this research compared well to the impulse values. Since most AMB systems that have BBs do not have force measurement capabilities, the development of the novel quantification method enables the quantification of rotor drop severity solely based on position data. The simulation model BBSim was found to accurately predict the behaviour of a rotor during a delevitation event. The parametric study completed using BBSim revealed that the severity of rotor delevitation events is less sensitive to the bearing stiffness than the bearing damping. The parametric study also found that the severity of a delevitation event is slightly sensitive to the angle of delevitation. The friction factor between the rotor and the inner-race of the rolling element bearings moderately influences the severity of the rotor delevitation event. The inertia of the rolling element bearing’s inner-race and balls influences the behaviour in a complex manner, where the inertia should be kept as low as possible for actively braked rotors, and should be higher for free running rotors. The unbalance of the rotor plays a major role in the severity of rotor delevitation events. A rotor with a high unbalance usually tends to go into forward whirl, whereas low unbalance could promote the development of backward whirl if the inertia of the inner-race and the friction factor between the inner-race and the rotor are excessively large. Some of the recommended future work to be done on BBSim Include investigations into load sharing, various failure modes of AMBs, the effect that rotor circularity has on the stability of AMB control and an investigation into forward whirl. Envisaged improvements that can be made to BBSim are the inclusion of an axial rotor AMB and BB model, cross-coupled with the existing BBSim model. Other improvements could be the inclusion of thermal modelling and the ability to simulate other types of BBs. Future experimental work could include a comparison of simulated and experimental results of larger systems and using the developed quantification methods to refine the defined threshold values for the safe operation of AMB systems. / PhD, North-West University, Potchefstroom Campus, 2014 / Appendix C is attached seperately because of the size of the pdf (920 MB). If it is too large to download, please loan the hardcopy with the CD from the Loan desk in the Ferdinand Postma Library.

The deployment of Renewable Energy (RE)-based generation has experienced a sustained global growth in the recent decades, driven by many countries' interest in reducing greenhouse gas emissions and dependence on fossil fuel for electricity generation. This trend is also observed in remote off-grid systems (isolated microgrids), where local communities, in an attempt to reduce fossil fuel dependency and associated economic and environmental costs, and to increase availability of electricity, are favouring the installation of RE-based generation. This practice has posed several challenges to the operation of such systems, due to the intermittent and hard-to-predict nature of RE sources. In particular, this thesis addresses the problem of reliable and economic dispatch of isolated microgrids, also known as the energy management problem, considering the uncertain nature of those RE sources, as well as loads. Isolated microgrids feature characteristics similar to those of distribution systems, in terms of unbalanced power flows, significant voltage drops and high power losses. For this reason, detailed three-phase mathematical models of the microgrid system and components are presented here, in order to account for the impact of unbalanced system conditions on the optimal operation of the microgrid. Also, simplified three-phase models of Distributed Energy Resources (DERs) are developed to reduce the level of complexity in small units that have limited impact on the optimal operation of the system, thus reducing the number of equations and variables of the problem. The proposed mathematical models are then used to formulate a novel energy management problem for isolated microgrids, as a deterministic, multi-period, Mixed-Integer Nonlinear Programming (MINLP) problem. The multi-period formulation allows for a proper management of energy storage resources and multi-period constraints associated with the commitment decisions of DERs. In order to obtain solutions of the energy management problem in reasonable computational times for real-time, realistic applications, and to address the uncertainty issues, the proposed MINLP formulation is decomposed into a Mixed-Integer Linear Programming (MILP) problem, and a Nonlinear programming (NLP) problem, in the context of a Model Predictive Control (MPC) approach. The MILP formulation determines the unit commitment decisions of DERs using a simplified model of the network, whereas the NLP formulation calculates the detailed three-phase dispatch of the units, knowing the commitment status. A feedback signal is generated by the NLP if additional units are required to correct reactive power problems in the microgrid, triggering a new calculation MINLP problem. The proposed decomposition and calculation routines are used to design a new deterministic Energy Management System (EMS) based on the MPC approach to handle uncertainties; hence, the proposed deterministic EMS is able to handle multi-period constraints, and account for the impact of future system conditions in the current operation of the microgrid. In the proposed methodology, uncertainty associated with the load and RE-based generation is indirectly considered in the EMS by continuously updating the optimal dispatch solution (with a given time-step), based on the most updated information available from suitable forecasting systems. For a more direct modelling of uncertainty in the problem formulation, the MILP part of the energy management problem is re-formulated as a two-stage Stochastic Programming (SP) problem. The proposed novel SP formulation considers that uncertainty can be properly modelled using a finite set of scenarios, which are generated using both a statistical ensembles scenario generation technique and historical data. Using the proposed SP formulation of the MILP problem, the deterministic EMS design is adjusted to produce a novel stochastic EMS. The proposed EMS design is tested in a large, realistic, medium-voltage isolated microgrid test system. For the deterministic case, the results demonstrate the important connection between the microgrid's imbalance, reactive power requirements and optimal dispatch, justifying the need for detailed three-phase models for EMS applications in isolated microgrids. For the stochastic studies, the results show the advantages of using a stochastic MILP formulation to account for uncertainties associated with RE sources, and optimally accommodate system reserves. The computational times in all simulated cases show the feasibility of applying the proposed techniques to real-time, autonomous dispatch of isolated microgrids with variable RE sources.

The motion of ocean waves can be captured and converted into usable electricity. This indicates that wave power has the potential to supply electricity to grids like wind or solar power. A point absorbing wave energy converter (WEC) system has been developed for power production at Uppsala University. This system contains a semi-submerged buoy on the water surface driving a linear synchronous generator placed on the seabed. The concept is to connect many small units together, to form a wave farm for large-scale electricity generation. A lot of effort has gone into researching how to enhance the power absorption from each WEC unit. These improvements are normally done separately for the buoy, the generator or the electrical system, due to the fact that modelling the dynamic behavior of the entire WEC system is complicated and time consuming. Therefore, a quick, yet simple, assessment tool is needed.  This thesis focuses on studying the use of the equivalent circuit as a WEC system modelling tool. Based on the force analysis, the physical elements in an actual WEC system can be converted into electrical components. The interactions between the regular waves, the buoy, and the Power Take-off mechanism can be simulated together in one circuit network. WEC performance indicators like the velocity, the force, and the power can be simulated directly from the circuit model. Furthermore, the annual absorbed electric energy can be estimated if the wave data statistics are known. The linear and non-linear equivalent circuit models developed in this thesis have been validated with full scale offshore experimental results. Comparisons indicate that the simplest linear circuit can predict the absorbed power reasonably well, while it is not so accurate in estimating the peak force in the connection line. The non-linear circuit model generates better estimations in both cases. To encourage researchers from different backgrounds to adapt and apply the circuit model, an instruction on how to establish a non-linear equivalent circuit model is supplied, as well as on how to apply the model to accelerate the decision making process when planning a WEC system.

Over the past decades, the concepts and methods for reliability assessment have evolved from analysing the ability of individual components to operate without faults and as intended during their lifetime, into the comprehensive approaches for evaluating various engineering strategies for system planning, operation and maintenance studies. The conventional reliability assessment procedures now receive different perspectives in different engineering applications and this thesis aims to improve existing approaches by incorporating in the analysis: a) a more detailed and accurate models of LV and MV networks and their reliability equivalents, which are important for the analysis of transmission and sub-transmission networks, b) the variations in characteristics and parameters of LV and MV networks in different areas, specified as “generic” UK/Scottish highly-urban, urban, sub-urban and rural network models, c) the relevant requirements for network reliability performance imposed by Regulators on network operators, d) the actual aggregate load profiles of supplied customers and their correlation with typical daily variations of fault probabilities and repair times of considered network components, and e) some of the expected “smart grid” functionalities, e.g., increased use of network automation and reconfiguration schemes, as well as the higher penetration levels of distributed generation/storage resources. The conventional reliability assessment procedures typically do not include, or only partially include the abovementioned important factors and aspects in the analysis. In order to demonstrate their importance, the analysis presented in the thesis implements both analytical and probabilistic reliability assessment methods in a number of scenarios and study cases with improved and more detailed “generic” LV and MV network models and their reliability equivalents. Their impact on network reliability performance is analysed and quantified in terms of the frequency and duration of long and short supply interruptions (SAIFI and SAIDI), as well as energy not supplied (ENS). This thesis addresses another important aspect of conventional approaches, which often, if not always, provide separate indicators for the assessment of system-based reliability performance and for the assessment of customer-based reliability performance. The presented analysis attempts to more closely relate system reliability performance indicators, which generally correspond to a fictitious “average customer”, to the actual “best-served” and “worst-served” customers in the considered networks. Here, it is shown that a more complex metric than individual reliability indicators should be used for the analysis, as there are different best-served and worst-served customers in terms of the frequency and duration of supply interruptions, as well as amounts of not supplied energy. Finally, the analysis in the thesis considers some aspects of the anticipated transformation of existing networks into the future smart grids, which effectively require to re-evaluate the ways in which network reliability is approached at both planning and operational stages. Smart grids will feature significantly higher penetration levels of variable renewable-based distributed generation technologies (with or without energy storage), as well as the increased operational flexibility, automation and remote control facilities. In this context, the thesis evaluates some of the considered smart grid capabilities and functionalities, showing that improved system reliability performance might result in a deterioration of power quality performance. This is illustrated through the analysis of applied automation, reconfiguration and automatic reclosing/remote switching schemes, which are shown to reduce frequency and duration of long supply interruptions, but will ultimately result in more frequent and/or longer voltage sags and short interruptions. Similarly, distributed generation/storage resources might have strong positive impact on system reliability performance through the reduced power flows in local networks and provision of alternative supply points, even allowing for a fully independent off-grid operation in microgrids, but this may also result in the reduced power quality levels within the microgrids, or elsewhere in the network, e.g. due to a higher number of switching transfers and transients.

Intensive Care Units (ICUs) host patients in critical condition who are being monitored by sensors which measure their vital signs. These vital signs carry information about a patient’s physiology and can have a very rich structure at fine resolution levels. The task of analysing these biosignals for the purposes of monitoring a patient’s physiology is referred to as physiological condition monitoring. Physiological condition monitoring of patients in ICUs is of critical importance as their health is subject to a number of events of interest. For the purposes of this thesis, the overall task of physiological condition monitoring is decomposed into the sub-tasks of modelling a patient’s physiology a) under the effect of physiological or artifactual events and b) under the effect of drug administration. The first sub-task is concerned with modelling artifact (such as the taking of blood samples, suction events etc.), and physiological episodes (such as bradycardia), while the second sub-task is focussed on modelling the effect of drug administration on a patient’s physiology. The first contribution of this thesis is the formulation, development and validation of the Discriminative Switching Linear Dynamical System (DSLDS) for the first sub-task. The DSLDS is a discriminative model which identifies the state-of-health of a patient given their observed vital signs using a discriminative probabilistic classifier, and then infers their underlying physiological values conditioned on this status. It is demonstrated on two real-world datasets that the DSLDS is able to outperform an alternative, generative approach in most cases of interest, and that an a-mixture of the two models achieves higher performance than either of the two models separately. The second contribution of this thesis is the formulation, development and validation of the Input-Output Non-Linear Dynamical System (IO-NLDS) for the second sub-task. The IO-NLDS is a non-linear dynamical system for modelling the effect of drug infusions on the vital signs of patients. More specifically, in this thesis the focus is on modelling the effect of the widely used anaesthetic drug Propofol on a patient’s monitored depth of anaesthesia and haemodynamics. A comparison of the IO-NLDS with a model derived from the Pharmacokinetics/Pharmacodynamics (PK/PD) literature on a real-world dataset shows that significant improvements in predictive performance can be provided without requiring the incorporation of expert physiological knowledge.

It is widely accepted that correct system modeling and identification are among the most important issues power system operators face when managing instability and post-contingency scenarios. The latter is usually performed involving special computational tools that allow the operator to forecast, prevent system failure and take appropriate actions according to protocols for different contingency cases in the system. To ensure that operators make the correct simulation-based decisions, the power system models have to be validated continuously. This thesis investigates power system modeling, identification and validation problems that are formulated and based on data provided by operators, and offers new methods and deeper insight into stages of an identification cycle considering the specifics of power systems. One of the problems this thesis tackled is the selection of a modeling and simulation environment that provides transparency and possibility for unambiguous model exchange between system operators. Modelica as equation-based language fulfills these requirements. In this thesis Modelica phasor time domain models were developed and software-to-software validated against conventional simulation environments, i.e. SPS/Simulink and PSAT in MATLAB. Parameter estimation tasks for Modelica models require a modular and extensible toolbox. Thus, RaPiD Toolbox, a framework that provides system identification algorithms for Modelica models, was developed in MATLAB. Contributions of this thesis are an implementation of the Particle Filter algorithm and validation metrics for parameter identification. The performance of the proposed algorithm has been compared with Particle Swarm Optimization (PSO) algorithm when combined with simplex search and parallelized to get computational speed up. The Particle Filter outperformed PSO when estimating turbine-governor model parameters in the Greek power plant model relying on real measurements. This thesis also analyses different model structures (Nonlinear AutoRegressive eXogenous (NARX) model, Hammerstein-Wiener model, and high order transfer function) that are selected to reproduce nonlinear dynamics of a Static VAR Compensator (SVC) under incomplete information available for National Grid system operator. The study has shown that standard SVC model poorly reproduces the measured dynamics of the real system. Therefore, black-box mathematical modeling and identification approach has been proposed to solve the problem. Also, the introduced combination of first-principle and black-box approach has shown the best output fit. The methodology following identification cycle together with model order selection and model validation issues was presented in detail. Finally, one of the major contributions is a new method to formulate the uncertainty of parameters estimated in the form of a multimodal Gaussian mixture distribution that is estimated from the Particle Filter output by applying statistical methods to select the standard deviations. The proposed methodology gives additional insight into power system properties when estimating the parameters of the model. This allows power system analysts to decide on the design of validation tests for the chosen model. / Det är allmänt accepterat att korrekt modellering och identifiering av systemet är bland de mest viktiga utmaningarna som kraftsystemoperatörer ställs inför när de hanterar scenarior med instabiliteter och oförutsedda händelser. Det senare är vanligen hanterat med speciella beräkningsverktyg som låter operatören förutse utvecklingen och utföra lämpliga åtgärder enligt de protokoll som finns vid olika systemhändelser. För att försäkra sig om att operatörer tar de korrekta, simuleringsbaseda besluten måste kraftsystemsmodellen kontinuerligt valideras. Denna avhandling undersöker problem inom modellering, identifiering och validering av kraftsystem, formulerade och baserade på data tillhandahållet av operatörer, samt erbjuder nya metoder och fördjupade insikter i delar av en identifieringscykel som beaktar kraftsystemets. Ett av de problem som denna avhandling tar upp är val av en programmiljö för simulering och modellering som ger transparens och möjlighet till otvetydigt modellutbyte mellan systemoperatörer. Modelica är ett ekvationsbaserat programspråk som uppfyller dessa krav. I denna avhandling utvecklades enfasekvivalenter i Modelica som blev validerade mot konventionella program för simulering, såsom SPS/Simulink och PSAT i MATLAB. Parameterestimering i Modelica-modellerna kräver en modulär och utbyggbar verktygslåda. Därför har verktyget RaPiD Toolbox, som tillhandahåller systemidentifieringsalgoritmer för Modelica-modeller, utvecklats i MATLAB. Bidrag från denna avhandling är en implementation av ett partikelfilter (en sekventiell Monte Carlo-metod) och valideringsmetrik för parameteridentifiering. Prestandan i den föreslagna algoritmen har jämförts med partikelsvärmoptimering (PSO) då den är kombinerad med simplexsök och parallellisering. Partikelfiltret överträffade PSO när modellparametrar i turbinregulatorn i ett grekiskt kraftverk skulle estimeras utifrån verklig mätdata.  Avhandling analyserar också olika modellstrukturer (NARX, Hammerstein-Wiener-modeller, och överföringsfunktioner med höga ordningstal) som används för att reproducera den ickelinjära dynamiken hos statiska reaktiv effekt-kompenserare (SVC) vid ofullständig information som är tillgänglig för systemoperatören National Grid. Undersökningen visar att den vanliga SVC-modellen är dålig på att reproducera den verkliga, uppmätta dynamiken. Genom att matematiskt modellera problemet som en svart låda har en identifieringsmetod föreslagits. Vidare, genom att kombinera modelleringen som en svart låda med fysikaliska principer har givit den bästa anpassningen till utdata. Metodologin för identifieringscykeln tillsammans med valet av modellkomplexitet och svårigheter med modellvalidering har utförligt presenterats. Slutligen, ett av de främsta bidragen är en ny metod för att formulera osäkerheten i parameteruppskattningarna i form av en blandning av normalfördelningar med flera typvärden som estimeras med partikelfiltrets utdata genom att använda statistiska metoder för att välja standardavvikelsen. Detta ger kraftsystemanalytiker möjlighet att utforma valideringstest för den valda modellen. / <p>QC 20171121</p> / EU FP7 iTesla project

With the motivation to mitigate the effects caused by one of humankind’s biggest challenges, climate change, the purpose of this minor field study was to examine the prospects of renewable energy technologies as part of a larger ambition to offer clean and affordable energy for all, in line with United Nations Sustainable Development Goals. The study was conducted for El Alamein in Egypt, a city under construction that will house four million residents. By combining a field study and an interview with literature search, the information needed for an energy system model was gathered. The modelling system OSeMOSYS was thereafter used to calculate the most cost-efficient electricity mix for the model period of 2020 to 2040, based on different scenarios and technologies. The total discounted cost and amount of emissions were thereafter compared between the scenarios, and the most cost-efficient scenario at reducing emissions was identified. Of the scenarios that were compared to the reference case, the one where 50 % of the electricity was produced from renewables in 2040 proved to be the most cost-efficient option. In addition, this scenario was also the most cost efficient at reducing emissions by a large margin. Regarding the renewable technologies, solar photovoltaics, which represented a majority of the renewable electricity production, was evidently the most cost-efficient technology as well as the one with the highest potential for future implementation, followed by onshore wind power. Moreover, concentrating solar power and waste to energy were proven to have a lower potential. The conclusions drawn were that the city of El Alamein could get a substantial part of its electricity from renewables and that solar PV was the best technology for that purpose. The final conclusion was that there might exist great potential for renewable energy in Egypt. / Med ambitionen att försöka lindra konsekvenserna av vad som idag är en av människans största utmaningar, klimatförändringen, är syftet med denna minor field study att utvärdera förutsättningarna för förnyelsebara energitekniker i Egypten. Detta ligger i linje med en större ambition att erbjuda ren och prisvärd energi i enlighet med de globala hållbarhetsmålen. Fältstudien utfördes i Egypten och omfattade en ny stad under konstruktion, El Alamein, som förväntas hushålla fyra miljoner invånare. En fältstudie och tillhörande intervju kombinerades med en litteraturundersökning för att erhålla nödvändig information som sedan användes i modelleringen av energisystemet. Modelleringsverktyget OSeMOSYS användes för att erhålla den mest kostnadseffektiva energimixen för åren 2020 till 2040, baserat på ett flertal olika scenarier och tekniker. Den totala diskonterade kostnaden samt mängden utsläpp jämfördes mellan de olika scenarierna, och det mest kostnadseffektiva scenariot för att minska utsläpp identifierades. Av de scenarier som jämfördes med referensfallet, så var scenariot där förnyelsebara energitekniker stod för 50 % av elproduktionen år 2040 den mest kostnadseffektiva energimixen för att tillfredsställa behovet samt för att minska mängden utsläpp. Av de förnyelsebara energiteknikerna så visade sig solceller, som stod för en majoritet av den förnyelsebara produktionen, vara den mest kostnadseffektiva tekniken då den i samtliga förnyelsebara scenarier prioriterades av modellen. Därmed visade sig den vara den tekniken med högst potential för framtida implementationer, följt av landbaserad vindkraft. Koncentrerad solkraft i form av soltorn visade sig inte vara kostnadseffektiv då den inte bidrog till produktionen i något scenario. Avfallsförbränningen, som bidrog minimalt till energimixen, saknade tillgång till den mängd bränsle som hade krävts för att den skulle kunnat stå för en större andel av produktionen. Därmed konstaterades det att båda dessa teknologier hade en låg potential för framtida implementationer. De slutsatser som drogs var att staden El Alamein kunde få en betydande del av sin elektricitet från förnyelsebara energikällor samt att solceller var mest lämpad för det syftet då den var mest kostnadseffektiv. Utöver dessa så drogs slutsatsen att det kan finnas stor potential för förnyelsebar energi i Egypten.

Zusammenfassung Um die ehrgeizigen politischen Ziele zur Reduzierung der Treibhausgasemissionen im Stromsektor zu erreichen, stimmen alle relevanten Energieszenarien überein, dass Deutschland kurz- bis mittelfristig bis 2035 seine Kapazitäten zur Erzeugung erneuerbarer Energien massiv ausbauen muss. Deutschland ist dabei wie viele andere Länder auch stark von fluktuierenden erneuerbaren Energiequellen (fEE) abhängig, insbesondere von der Wind- und Solarenergie. Die Spezifika der Stromerzeugung von fEE stellen neue und besondere Herausforderungen an ein zuverlässiges Stromversorgungssystem der Zukunft. Entsprechend hat die Erforschung der technischen Optionen bei der Integration großer Anteile von fEE in das Stromnetz in den letzten Jahren stark an Interesse gewonnen. Allerdings scheinen Energieszenarien die mit der schnellen technologischen Entwicklung einhergehenden Integrationsoptionen bisher nicht korrekt abzubilden. In der vorliegenden kumulativen Dissertation wurden ausgewählte technische Optionen für die Integration erneuerbarer Energiequellen in das Stromnetz im Rahmen einer Fallstudie für Deutschland sowie ausgewählter Übertragungsnetze in Deutschland untersucht. Zur Identifizierung und Bewertung der Integrationsmöglichkeiten, widmete sich die Arbeit den vielversprechendsten technischen Integrationsoptionen in Form von i.) systemfreundliche Auslegung von Wind- und Solaranalgen; ii.) optimale Kapazitätsanteile von Wind- und Solaranlagen, iii.) der räumlichen Allokation und Bewertung von Windenergieanlagen in herkömmlicher als auch systemfreundlicher Auslegung; iv.) und dem Beitrag welchen die flexible Stromerzeugung aus Bioenergie als Ergänzung zu steigenden Anteilen an fEE erbringen kann. Es wurde ein Methodenmix zur Beantwortung dieser Forschungsfragen genutzt, der von der numerischen Optimierung auf Basis von Zeitreihendaten über die räumliche Potenzialkartierung und Allokation bis hin zur multikriteriellen Entscheidungsanalyse reicht. Die Ergebnisse zeigen wie der Übergang zu einem von hohen Anteilen an vRES gekennzeichneten Stromversorgungssystem erleichtert werden kann. Darunter Möglichkeiten zur Beschleunigung des Umstiegs auf erneuerbare Energien mit deutlich reduzierten Erzeugungskapazitäten von Wind- und Solaranlagen, weniger negative Residuallasten und negativer residualer Energie, verbesserte Sektorenkopplung und die Potenziale der flexiblen Stromerzeugung aus Bioenergie als Ergänzung zu fEE.:Table of Contents Abstract Zusammenfassung Acknowledgements List of Publications List of Acronyms Table of Contents I. Introductory chapters 1. Introduction 1.1. Background 1.2. vRES in energy scenarios 1.3. Technical developments and options for the integration of vRES 2. Research questions 3. Methods applied in this PhD thesis 4. Discussion and conclusion 4.1. Summary of the main findings 4.2. Transferability of results and methods 4.3. Relevance and outreach 5. Appendix 6. Literature 7. Appended publications and the individual contribution to the publications 8. Curriculum Vitae (deleted) 9. Selbstständigkeitserklärung / Abstract: For Germany to achieve its ambitious political targets for the reduction of greenhouse gas emissions in the electricity sector, major energy scenarios and reports project that the country will have to expand its renewable power generation capacities massively by 2035. As is the case for many countries, Germany will have to heavily rely on variable renewable energy sources (vRES), especially wind and solar photovoltaics. The characteristics of power production from vRES pose challenges for a stable and reliable future power supply system. Accordingly, the research into the technical challenges of integrating large shares of vRES into the power system has therefore attracted much interest in recent years; however, major energy scenarios seem to not cover integration options associated with the fast development of vRES correctly and lag behind the fast development in renewable energy technology. In this cumulative thesis, selected technical options for the integration of renewable energy sources into the power supply system have been investigated in a case study of Germany and a selected transmission system in Germany. To identify and assess these emerging integration options, the research in this PhD thesis covers the most promising technical options for the integration of vRES in the form of i) system-friendly layouts of wind and solar PV; ii) optimal capacity mixes of vRES; iii) the spatial allocation of wind turbines and the impact assessment of wind turbine allocation; and iv) the contribution of flexible power generation from biomass to complement vRES. Therefore, a mix of methods has been applied, ranging from numerical optimization based on time series data, GIS potential mapping and allocation including a multi-criterial decision analysis. The results show how the investigated options can facilitate the transition for a power supply system dominated by high shares of vRES in the near to medium term. A faster energy transition with significantly reduced overall vRES power generation capacities, less Excess Energy (EE) generation, improved cross-sectorial energy provision and flexible bioenergy as a complement to vRES are the major findings of the investigated options in this thesis.:Table of Contents Abstract Zusammenfassung Acknowledgements List of Publications List of Acronyms Table of Contents I. Introductory chapters 1. Introduction 1.1. Background 1.2. vRES in energy scenarios 1.3. Technical developments and options for the integration of vRES 2. Research questions 3. Methods applied in this PhD thesis 4. Discussion and conclusion 4.1. Summary of the main findings 4.2. Transferability of results and methods 4.3. Relevance and outreach 5. Appendix 6. Literature 7. Appended publications and the individual contribution to the publications 8. Curriculum Vitae (deleted) 9. Selbstständigkeitserklärung

The 2050 national energy scenarios as planned by the DECC, academia and industry specify a range of different decarbonised supply side technologies combined with the electrification of transportation and heating. Little attention is paid to the household demand side; indeed within many scenarios a high degree of domestic Demand Side Management (DSM) is implicit if the National Grid is to maintain supply-demand balance. A top-down, bottom-up hybrid model named Shed-able Household Energy Demand (SHED) has been developed and the results of which presented within this thesis. SHED models six published national energy scenarios, including three from the Department for Energy and Climate Change, in order to provide a broad coverage of the possible energy scenario landscape. The objective of which is to quantify the required changes in current household energy demand patterns via DSM, as are implicit under these highly electricity dominated scenarios, in order to maintain electrical supply-demand balance at the national level. The frequency and magnitude of these required household DSM responses is quantified. SHED performs this by modelling eleven years of supply-demand dynamics on the hourly time step, based on the assumptions of the published energy scenarios as well as weather data from around 150 weather stations around the UK and National Grid historic electricity demand data. The bottom-up component of SHED is populated by 1,000 households hourly gas and electricity demand data from a recently released dataset from a smart metering trial in Ireland. This aggregate pool of households enables national domestic DSM dynamics to be disaggregated to the aggregate household level. Using household classifications developed by the Office for National Statistics three typical ' households are identified within the aggregate pool and algorithms developed to investigate the possible required responses from these three households. SHED is the first model of its kind to connect national energy scenarios to the implications these scenarios may have on households consumption of energy at a high temporal resolution. The analysis of the top-down scenario modelling shows significant periods where electrical demand exceeds supply within all scenarios, within many scenarios instances exist where the deficit is unserviceable due to lack of sufficient spare capacity either side of the deficit period. Considering the level of participation required within the modelled scenarios in order to balance the electricity system and the current lack in understanding of smart metering and Time-Of-Use (TOU) tariffs within households, it would seem there is a disconnect between the electricity system being planned, the role this system expects of households and the role households are willing to play.