<p dir="ltr">Distributed energy resources (DERs), such as rooftop solar generation and energy storage systems, are becoming more prevalent in distribution systems. DERs are connected to the distribution system via power electronic converters, introducing faster dynamics in the system. Understanding the system dynamics under a high penetration of inverter-based DERs is critical for power system researchers and practitioners, driving the development of modeling techniques and simulation software. Aiming to reduce computational complexity, existing tools and techniques often employ various approximations. Meanwhile, modern advancements in computational hardware capabilities provide opportunities to include the faster time-scale dynamics. To address this, the primary objective of this thesis is to develop an open-source Python simulation package, Dynamic Simulation using Sparse Tableau Approach in Python, DynaSTPy (pronounced “dynasty”), capable of capturing the dynamics of all components in a distribution feeder. The distribution feeder is modeled as a system of Differential-Algebraic Equations (DAEs). Further, each component in the feeder is modeled based on the Sparse Tableau Approach (STA), which involves the representation of component model equations using sparse matrices, facilitating a systematic procedure to model the components and construct the system DAEs. In sinusoidal steady state, the DAEs can be represented in phasor form, extending the approach to perform power flow analysis of distribution feeders.</p>

Species distribution maps can provide important information to focus conservation efforts and enable spatial management of human activities. Two sympatric marine predators, grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina), have overlapping ranges but contrasting population dynamics around the UK; whilst grey seals have generally increased, harbour seals have shown significant regional declines. A robust analytical methodology was developed to produce maps of grey and harbour seal usage estimates with corresponding uncertainty, and scales of spatial partitioning between the species were found. Throughout their range, both grey and harbour seals spend the majority of their time within 50 km of the coast. The scalability of the analytical approach was enhanced and environmental information to enable spatial predictions was included. The resultant maps have been applied to inform consent and licensing of marine renewable developments of wind farms and tidal turbines. For harbour seals around Orkney, northern Scotland, distance from haul out, proportion of sand in seabed sediment, and annual mean power were important predictors of space-use. Utilising seal usage maps, a framework was produced to allow shipping noise, an important marine anthropogenic stressor, to be explicitly incorporated into spatial planning. Potentially sensitive areas were identified through quantifying risk of exposure of shipping traffic to marine species. Individual noise exposure was predicted with associated uncertainty in an area with varying rates of co-occurrence. Across the UK, spatial overlap was highest within 50 km of the coast, close to seal haul outs. Areas identified with high risk of exposure included 11 Special Areas of Conservation (from a possible 25). Risk to harbour seal populations was highest, affecting half of all SACs associated with the species. For 20 of 28 animals in the acoustic exposure study, 95% CI for M-weighted cumulative Sound Exposure Levels had upper bounds above levels known to induce Temporary Threshold Shift. Predictions of broadband received sound pressure levels were underestimated on average by 0.7 dB re 1μPa (± 3.3). An analytical methodology was derived to allow ecological maps to be quantitatively compared. The Structural Similarity (SSIM) index was enhanced to incorporate uncertainty from underlying spatial models, and a software algorithm was developed to correct for internal edge effects so that loss of spatial information from the map comparison was limited. The application of the approach was demonstrated using a case study of sperm whales (Physeter macrocephalus, Linneaus 1758) in the Mediterranean Sea to identify areas where local-scale differences in space-use between groups and singleton whales occurred. SSIM is applicable to a broad range of spatial ecological data, providing a novel tool for map comparison.

Die fortgeschrittene Phase der Energiewende ist, neben einer zunehmenden Notwendigkeit zur Systemintegration, vor allem geprägt durch das Zutage treten grundsätzlicher Richtungsentscheidungen – der Schwerpunkt verschiebt sich also vom ‚Ob‘ zum ‚Wie‘. Heutige Infrastrukturentscheidungen begründen dabei ganz unterschiedliche Energiezukünfte, welche wiederum über sozio-technische Pfadabhängigkeiten auf Dauer gestellt werden. Die Arbeit rückt zunächst die hierfür maßgeblichen Stellschrauben in den Vordergrund und beleuchtet deren wirtschaftliche und technische Grundlagen sowie die Bandbreite konkurrierender politischer Steuerungsoptionen. Auf dieser Datengrundlage wird im Rahmen einer Clusteranalyse die Aktualisierung des politikfeldspezifischen Akteurskoalitionsmodells vorgeschlagen. Im Mittelpunkt steht dabei die strukturbildende Unterscheidung zwischen einer eher zentralen und einer eher dezentralen Energiezukunft. Die so skizzierte ‚Landkarte der Energiewende‘ ist weiterhin eingebettet in eine Untersuchung des Energiediskurses auf Akteurs- und Medienebene sowie durch eine Politikfeldanalyse, in der aktuelle steuerungspolitische Problemstellungen und Handlungsmuster auf Basis technologischer Fallbeispiele beleuchtet werden. Die Arbeit ist ein Ergebnis der Forschung im interdisziplinären Boysen-TU Dresden Graduiertenkolleg „Nachhaltige Energiesysteme – Interdependenz von technischer Gestaltung und gesellschaftlicher Akzeptanz.“

The increasing share of renewable energies in the power sector influences the economic viability of investments in new conventional power plants. Many studies have investigated these issues by considering power plant operation or the long-term development of the power plant fleet. However, power plant decommissioning, investment and operation are intrinsically linked. This doctoral thesis therefore presents a modelling framework for an integrated consideration of power plant decommissioning, investment and operation. In a case study focusing on Germany, the effects of the integration of renewable energies on power plant decommissioning, investment and operation are evaluated in the context of different assumptions regarding the remaining lifetime of nuclear power plants. With regard to the use of nuclear power, a phase-out scenario and a scenario with lifetime extension of nuclear power plants (by on average 12 years) are considered. The results show that static decommissioning (i.e. considering fixed technical lifetimes) underestimates the capacity available in the power sector in the scenario without lifetime extension since retrofit measures (versus decommissioning) are not taken into account. In contrast, capacity available in the case of nuclear lifetime extension is overestimated since mothballing (versus regular operation) is not considered. If the impact on decommissioning decisions of profit margins accrued during power plant operation are considered (“dynamic decommissioning”), the electricity price reduction effect due to a lifetime extension is reduced by more than half in comparison to static decommissioning. Scarcity situations do not differ significantly between the scenarios with and without lifetime extension with dynamic decommissioning; in contrast, there is a significantly higher need for imports without lifetime extension with static decommissioning. The case study demonstrates that further system flexibility is needed for the integration of renewable energies. It can be further concluded that the share of flexible power plants is higher with the phase-out of nuclear power plants. With regard to the decommissioning dynamics, the phase-out can be considered as beneficial for the economic viability of fossil power plants. Furthermore, the phase-out does not, overall, lead to environmental disadvantages in the medium term, but may be beneficial in the long run since lock-in effects are avoided. Further research is required with regard to the consideration of future flexibility options and a new market design. / Der steigende Anteil erneuerbarer Energien beeinflusst die Wirtschaftlichkeit von Investitionen in neue konventionelle Kraftwerke. Zahlreiche Studien haben diese Aspekte in Bezug auf den Kraftwerksbetrieb oder die langfristige Entwicklung des Kraftwerksparks untersucht. Stilllegungen, Investitionen und Betrieb im Kraftwerkspark bedingen jedoch einander. Aus diesem Grund wird in dieser Doktorarbeit ein Modellierungsansatz für eine integrierte Betrachtung von Kraftwerksstilllegung, -investition und -betrieb vorgestellt. In einer Fallstudie für Deutschland werden die Auswirkungen einer Integration erneuerbarer Energien auf Kraftwerksstilllegung, -investition und -betrieb im Zusammenhang mit unterschiedlichen Annahmen über die Restlaufzeit von Kernkraftwerken untersucht. Bezogen auf die Nutzung der Kernenergie wird hierbei ein Ausstiegsszenario sowie ein Laufzeitverlängerungsszenario (Verlän-gerung der Laufzeit um durchschnittlich 12 Jahre) betrachtet. Die Ergebnisse zeigen, dass die statische Stilllegung (d.h. die Betrachtung fester technischer Lebensdauern) im Fall eines Verzichts auf die Laufzeitverlängerung die im Kraftwerkspark verfügbare Leistung unterschätzt, da Retrofit-Maßnahmen (im Vergleich zur Stilllegung) nicht berücksichtigt werden. Die verfügbare Leistung im Falle einer Laufzeitverlängerung wird dagegen überschätzt, da die Möglichkeit der Kaltreserve (im Vergleich zum regulären Betrieb) vernachlässigt wird. Werden die Rückwirkungen der im Betrieb erwirtschaftbaren Deckungsbeiträge auf Stilllegungsentscheidungen (“dynamische Stilllegung”) betrachtet, so wird der strompreissenkende Effekt durch die Laufzeitverlängerung im Vergleich zur statischen Stilllegung mehr als halbiert. Knappheitssitutationen unterscheiden sich nicht wesentlich mit und ohne Laufzeitverlängerung im Fall der dynamischen Stilllegung, während bei statischer Stilllegung ohne Laufzeitzeitverlängerung ein deutlich größerer Importbedarf besteht. Die Fallstudie zeigt, dass weitere Systemflexibilitäten für die Integration erneuerbarer Energien benötigt werden. Der Anteil flexibler Kraftwerke ist größer im Fall des Kernenergieausstiegs. Der Kernenergieausstieg wirkt sich in Bezug auf die Stilllegungsdynamik positiv auf die Wirtschaftlichkeit fossiler Kraftwerke aus. Insgesamt führt der Kernenergieausstieg zu keinen mittelfristig nachteiligen Umwelteffekten, er kann sich jedoch langfristig positiv auswirken, da Lock-in-Effekte vermieden werden. Es besteht weiterer Forschungsbedarf in Bezug auf die Berücksichtigung künftiger Flexibilitätsoptionen und ein neues Marktdesign.

Die fortgeschrittene Phase der Energiewende ist, neben einer zunehmenden Notwendigkeit zur Systemintegration, vor allem geprägt durch das Zutage treten grundsätzlicher Richtungsentscheidungen – der Schwerpunkt verschiebt sich also vom ‚Ob‘ zum ‚Wie‘. Heutige Infrastrukturentscheidungen begründen dabei ganz unterschiedliche Energiezukünfte, welche wiederum über sozio-technische Pfadabhängigkeiten auf Dauer gestellt werden. Die Arbeit rückt zunächst die hierfür maßgeblichen Stellschrauben in den Vordergrund und beleuchtet deren wirtschaftliche und technische Grundlagen sowie die Bandbreite konkurrierender politischer Steuerungsoptionen. Auf dieser Datengrundlage wird im Rahmen einer Clusteranalyse die Aktualisierung des politikfeldspezifischen Akteurskoalitionsmodells vorgeschlagen. Im Mittelpunkt steht dabei die strukturbildende Unterscheidung zwischen einer eher zentralen und einer eher dezentralen Energiezukunft. Die so skizzierte ‚Landkarte der Energiewende‘ ist weiterhin eingebettet in eine Untersuchung des Energiediskurses auf Akteurs- und Medienebene sowie durch eine Politikfeldanalyse, in der aktuelle steuerungspolitische Problemstellungen und Handlungsmuster auf Basis technologischer Fallbeispiele beleuchtet werden. Die Arbeit ist ein Ergebnis der Forschung im interdisziplinären Boysen-TU Dresden Graduiertenkolleg „Nachhaltige Energiesysteme – Interdependenz von technischer Gestaltung und gesellschaftlicher Akzeptanz.“

<p>  </p> <p>Organic-inorganic halide perovskites are at the brink of commercialization as the next generation of light-absorbing materials for solar energy harvesting devices. Perovskites have large absorption coefficients, long charge-carrier lifetimes and diffusion lengths, and a tunable absorption spectrum. Furthermore, these materials can be low-temperature solution-processed, which transfers to low-cost manufacturing and cost-competitive products. The remarkable material properties of perovskites enable a broad product-market fit, encompassing traditional and new applications for solar technology. Perovskites can be deposited on flexible substrates for flexible solar cells, applied in thermochromic windows for power generation and building cooling, or tuned for tandem solar cell application to include in high-performance solar panels. However, perovskites are intrinsically unstable, which has so far prevented their commercialization. Despite large research efforts, including over two thousand publications per year, perovskite solar cells degrade in under one year of operation. In a saturated research field, new ideas are needed to inspire alternative approaches to solve the perovskite stability problem. In this dissertation, we detail research efforts surrounding the concept of a self-healing perovskite solar cell.</p> <p>     A self-healing perovskite solar cell can be classified with two distinctions: mechanically healing and molecularly healing. First, mechanically self-healing involves the material’s ability to recover its intrinsic properties after mechanical damage such as tares, lacerations, or cracking. This type of healing was unique to the organic polymer community and ultra-rare in semiconducting materials. By combining a self-healing polymer with perovskite material, we developed a self-healing semiconducting perovskite composite material which can heal using synergistic grain growth and solid-state diffusion processes at slightly elevated temperatures. The material is demonstrated in flexible solar cells with improved bending durability and a power conversion efficiency reaching 10%. The addition of fluidic polymer enables macroscopic perovskite material movement, which is otherwise brittle and rigid. The results inspire the use of polymer scaffolds for mechanically self-healing solar cells.</p> <p>     The second type of healing, molecular healing, involves healing defects within the rigid crystal domains resulting from ion migration. The same phenomenon which leads to device degradation, also assists the recovery of the device performance after resting the device in the dark. During device operation, perovskite ions diffuse in the perovskite lattice and accumulate at the device interfaces where they undergo chemical reactions or leave the perovskite layer, ultimately consuming the perovskite precursors. The photovoltaic performance can be recovered if irreversible degradation is limited. Ideally, degradation and recovery can match day and night cycling to dramatically extend the lifetime of perovskite solar cells. In this dissertation, we introduce the application of chalcogenide chemistry in the fabrication of perovskite solar cells to control the thin film crystallization process, ultimately to reduce defects in the perovskite bulk and introduce surface functionality which extends the device stability. This new strategy will help improve molecularly self-healing perovskite solar cell by reducing irreversible degradation. Lastly, we present a few other new ideas to inspire future research in perovskite solar cells and assist in the commercialization of the next generation of photovoltaics.</p>

No description available.

<p dir="ltr">The urgent global shift towards decarbonization necessitates the development of robust frameworks to navigate the complex technological, financial, and regulatory challenges emerging in the clean energy transition. Furthermore, the increased adoption of renewable energy sources (RES) is correlated to the exponential growth in weather data research over the last few years. This circular relationship, where big data drives renewable growth, which feeds back the data pipeline, serves as the primary focus of this study: the development of computational tools across diverse spatial and temporal scales for the optimal design and operation of renewable energy-based systems. Two scales are considered, differentiated by their primary objectives and techniques used. </p><p dir="ltr"> In the first one, the integration of probabilistic forecasts into the operations of RES microgrids (MGs) is studied in detail. It is revealed that longer scheduling horizons can reduce dispatch costs but at the expense of forecast accuracy due to increased prediction accuracy decay (PAD). To address this, a novel method that determines how to split the time horizon into timeblocks to minimize dispatch costs and maximize forecast accuracy is proposed. This forms the basis of an optimal rolling horizon strategy (ORoHS) which schedules distributed energy resources over varying prediction/execution horizons. Results offer Pareto-optimal fronts, showing the trade-offs between cost and accuracy at varying confidence levels. Solar power proved more cost-effective than wind power due to lower variability, despite wind’s higher energy output. The ORoHS strategy outperformed common scheduling methods. In the case study, it achieved a cost of \$4.68 compared to \$9.89 (greedy policy) and \$9.37 (two-hour RoHS). The second study proposes the Caribbean Energy Corridor (CEC) project, a novel, ambitious initiative that aims to achieve total grid connectivity between the Caribbean islands. The analysis makes use of thorough data procedures and optimization methods for the resource assessment and design tasks needed to build such an infrastructure. Renewable energy potentials are quantified under different temporal and spatial coverages to maximize usage. Prioritizing offshore wind development, the CEC’s could significantly surpass anticipated growth in energy demand, with an estimated installed capacity of 34 GW of clean energy upon completion. The corridor is modeled as an HVDC grid with 32 nodes and 31 links. Underwater transmission is optimized with a Submarine-Cable-Dynamic-Programming (SCDP) algorithm that determines the best routes across the bathymetry of the region. It is found that the levelized cost of electricity remains on the low end at \$0.11/kWh, despite high initial capital investments. Projected savings reach \$ 100 billion when compared with ”business-as-usual” scenarios and the current social cost of carbon. Furthermore, this infrastructure has the potential to create around 50,000 jobs in construction, policy, and research within the coming decades, while simultaneously establishing a robust and sustainable energy-water nexus in the region. Finally, the broader implications of these works are explored, highlighting their potential to address global challenges such as energy accessibility, prosperity in conflict zones, and sharing these discoveries with the upcoming generations.</p>

The goal of the thesis is firstly to get all the information about the initial state of solved block of flats, which is located on the street Merhautova 76/954 in Brno – Černá pole, in terms of constructions, energy consumption and initial state of heating system. In the second part of the thesis, where are discussed the possibilities of reduction of energy consumption, variant drafts of reduction of energy consumption and their financial costs and the choice of optimal variant. Third part deals with assement of solved block of flats in terms of sustainable built environment by using tool to rate buildings in terms of sustainable built environment - SBToolCZ, evaluation of possibility to use renewables. In the end are written summaries and recommendations.